The ideal candidate will contribute to alpha research, signal development, and strategy implementation in a dynamic and fast-paced environment. This role offers significant career growth.

Principal Responsibilities:

Work closely with the Senior Portfolio Manager to develop systematic macro strategies, focusing on alpha research, including idea generation, data preprocessing, statistical analysis, backtesting, and implementation.

Contribute to and enhance the internal research platform, including data pipelines, statistical learning tools, alpha analytics, and backtesting frameworks.

Independently explore and develop new alpha ideas while collaborating in a transparent and team-oriented environment.

Preferred Technical Skillset:

Strong research and programming skills, with proficiency in Python.

Solid experience with data analytics libraries (e.g., Pandas, SciPy, NumPy, Polars); extensive library-building experience is a plus.

Masters or PhD degree in a quantitative subject such as Applied Mathematics, Statistics, Physics, Engineering, Financial Engineering, Computer Science, or related field from a top-ranked university. Strong candidates with Bachelor's degree will also be considered.

Exceptional problem-solving abilities, intellectual curiosity (especially in alpha research), and a proactive research mindset.

Creativity and out-of-the-box thinking, combined with rigorous quantitative analysis.

Preferred Experience:

2+ years of experience in quantitative research with a focus on systematic macro strategies.

Preferred experience in hedge fund alpha research in commodities, FX, equity, and bond futures.

Experience in macro intraday strategies is a strong plus.

Experience in trading cost analysis is a plus.

Experience in machine learning is a plus.

Target Start Date:

Up to 12 months (strong preference for candidates who can start sooner)

Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. The estimated base salary range for this position is $150,000 to $200,000, which is specific to New York and may change in the future.

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Our technology teams are looking for Software Engineers with C++, Python, or Java to design, implement, and maintain systems supporting our technology business functions.

Candidate is expected to:

• Work closely with technology teams to develop requirements and specifications for varying projects
• Take part in the development and enhancement of the backend distributed system
• Apply AI/ML (deep learning, natural language processing, large language models) to practical and comprehensive technology solutions

Qualifications/Skills Required:

• 2-5 years of experience working with C++, Python, or Java
• Experience with ML libraries, Pandas, NumPy, FastAPI (Python), Boost (C++), Spring Boot (Java)
• Must be comfortable working in both Unix/Linux and Windows environments
• Good understanding of various design patterns
• Strong analytical and mathematical skills along with an interest/ability to quickly learn additional languages and quantitative concepts
• Solid communication skills
• Able to work collaboratively in a fast-paced environment with a passion to solving complex problems
• Detail oriented, organized, demonstrating thoroughness and strong ownership of work

Desirable Skills/Knowledge:

• Bachelor or Master's degree in Computer Science, Applied Mathematics, Statistics, Data Science/ML/AI, or a related technical or engineering field
• Demonstrable passion for developing LLM-powered products whether that is through commercial experience or open source/academic projects you have worked on in your own time
• Hands-on experience building ML and data pipeline architectures
• Understanding of distributed messaging systems
• Experience with Docker/Kubernetes, microservices architecture in a cloud environment (AWS, GCP preferred)
• Experience with relational and non-relational database platforms

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Scale is at the frontier of GenAI and human-AI collaboration. The Gen AI Ops Trust and Safety team is focused on safeguarding human authenticity and genuineness in AI training.

We are looking for a highly analytical Technical Program Manager (TPM) who leans heavily into fraud analytics and data-driven strategy to protect our ecosystem. This isn't a project management role. You will act as the lead investigative analyst and program owner for our fraud defense portfolio.

Your day-to-day will involve diving deep into complex datasets to uncover hidden fraud vectors, and then translating those analytical insights into scalable rules, policies, and operational programs. By utilizing AI coding tools at high velocity, you will build out analytics pipelines, dashboards, and detection logic to shift Trust and Safety from a reactive function to a strategic one that balances safety and growth.

Responsibilities

• Analyze large, messy behavioural events to identify ambiguous and constantly evolving fraud patterns across the contributor lifecycle.

• Translate your analytical findings into actionable detection logic. You will redesign rules, optimize thresholds, and decision flows to catch bad actors while minimizing friction for high-quality contributors.

• Establish robust KPIs, build tracking dashboards, and define offline evaluation frameworks (e.g., false positive monitoring, precision/recall analysis) to continuously measure the health of our risk strategy.

• Act as the connective tissue between data, operations, and engineering. You will use your analytical findings to implement technical execution, taking new detection capabilities from data prototype to production deployment.

• Leverage AI-assisted IDEs daily to rapidly write complex SQL queries, automate data pulls, and streamline your analytical workflows.

• Connect signals, data, and operations to see the full picture. Provide clear, direct communication regarding fraud trends and strategy shifts to both technical and non-technical partners.

Requirements

• 5-8 years of experience in risk strategy and fraud analytics. You have a battle-tested track record of reverse-engineering adversarial patterns, dismantling complex fraud vectors, and driving highly analytical Trust & Safety or TPM programs.

• Expert proficiency in SQL skills. You must be highly comfortable extracting insights from large datasets in noisy, adversarial environments.

• An execution-driven mindset focused on delivering measurable results, not just theoretical analysis. You are comfortable working in ambiguity and taking ownership from data problems to operational solutions.

• Strong proficiency with AI coding assistants to accelerate data exploration and query writing.

• Deep understanding of how to balance aggressive fraud detection with marketplace growth. You make decisions based on what's right for the business, not what's convenient.

Nice to haves:

• Solid Python skills (e.g., Pandas, NumPy) for advanced data manipulation and scripting

• Experience working in marketplace or gig-economy platforms is a plus

Compensation

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

Salary Range

The base salary range for this full-time position in the location of San Francisco is: $180,800-$226,000 USD

Benefits

You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact.

We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com.

Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Taniam is seeking an AI Research Scientist Intern for Summer 2026. This role reports to our Staff Data Scientist leading AI design, prototyping, and experimentation across Tanium products and solutions.

As an AI Research Scientist Intern, you will have the opportunity to work on challenging real-world problems, gain hands-on experience, and contribute to building intelligent systems that will shape the future of autonomous IT across endpoint management, exposure management, and security operations.

This is a hybrid position, which will require in person attendance several days each week in Durham, NC OR Emeryville, CA.

The hourly rate for this internship is $55 to $60 per hour. This hourly rate is an estimate for what Tanium will pay an intern. The actual rate offered may be adjusted based on a variety of factors, including but not limited to, education, skills, training, and experience.

In addition to an hourly rate, interns will be eligible for a housing stipend, 401k matching, and a monthly allowance for communications reimbursement.

Responsibilities

• Collaborate with data science and engineering teams to design and implement AI and machine learning (ML) algorithms that improve Tanium’s autonomous IT capabilities.

• Develop and evaluate ML models across a wide variety of use cases, including anomaly detection, threat identification, and performance optimization.

• Analyze large-scale endpoint data to extract meaningful insights and develop predictive models.

• Assist in building data pipelines to efficiently process and analyze endpoint data at scale.

• Conduct exploratory data analyses and visualizations to communicate findings and inform product development decisions.

• Document research, methodologies, and results to contribute to Tanium’s knowledge base.

• Stay up to date with the latest advancements in AI, ML, and endpoint management technologies.

Requirements

• Strong foundation in machine learning, data analysis, and statistics.

• Proficiency in Python.

• Familiarity with machine learning frameworks and libraries (e.g., PyTorch, scikit-learn, TensorFlow, numpy, scipy, pandas).

• Experience working with large datasets.

• Knowledge in one or more of the following areas:

• Statistics

• Anomaly detection

• Machine learning (classification/regression)

• Internals of large language models (LLMs)

• Agentic AI

• Strong problem-solving skills and the ability to work independently and collaboratively.

• Excellent communication skills and the ability to present complex ideas clearly.

• Passion for technology, cybersecurity, and autonomous systems.

Other qualifications:

• Authorized to work in the U.S. now and in the future

• Available to work full-time from June 8, 2024 to August 14, 2025

• A currently enrolled Master’s/ PhD degree candidate ideally studying Statistics, Machine Learning, or a related field with a 3.5+ GPA

• Graduating Spring 2027 or Fall 2026

• In accordance with Department of Defense requirements, applicants for this role must be a U.S. citizen, national, or resident pursuant to 8 U.S.C. 1101(a)(20) and 8 U.S.C. 1324b(a)(3)

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Responsibilities:

• Design, develop, and deploy Cresta's AI Agent solutions and proprietary models.
• Focus on practical AI challenges such as improving reasoning, planning capabilities, and evaluation in real-world scenarios.
• Collaborate with cross-functional teams including front-end and back-end software engineers to integrate AI Agents into Cresta's customer solutions.
• Lead initiatives to scale AI systems for production environments, ensuring performance and reliability across use cases.
• Contribute to solving cutting-edge problems in AI and help define the future roadmap for Cresta's AI Agents.
• Innovate and research ways to improve security, cost-efficiency, and reliability of AI systems.

Qualifications:

• Bachelor's or Master's Degree in Computer Science, Mathematics, or a related field.
• 2+ years of hands-on industry experience with AI and machine learning, preferably with experience working with LLMs in large-scale production environments.
• Solid knowledge of machine learning concepts and methods, especially those related to NLP, Generative AI, and working with LLMs.
• Practical knowledge of modern machine learning frameworks and technologies (e.g., PyTorch, Tensorflow, Hugging Face, NumPy), as well as experience with distributed systems and cloud-based AI infrastructure.
• Strong problem-solving and strategic thinking abilities, with a proven ability to lead cross-functional teams and work collaboratively to deliver innovative AI solutions in production.
• A passion for driving AI adoption and pushing the boundaries of AI technology into real-world applications, with an ability to mentor junior engineers and influence strategic decisions across the organization.

Perks & Benefits:

• We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family's needs.
• Paid parental leave to support you and your family.
• Monthly Health & Wellness allowance.
• Work from home office stipend to help you succeed in a remote environment.
• Lunch reimbursement for in-office employees.
• PTO: 3 weeks in Canada.

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We're excited to offer PhD machine learning engineering internships for the summer of 2026. As an intern, you'll contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.

Responsibilities

• Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
• Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
• Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
• Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
• Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.

Who We're Looking For

• A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2026 or spring/summer 2027.
• Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
• Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
• Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
• A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.

What We Offer

• Join us for an unforgettable summer internship and help shape the future of global commerce.
• At Stripe, you won't just be working on theoretical projects; you'll make a tangible impact on the world's economic infrastructure.

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About the Position

As a Data Scientist on the platform prediction team, you will translate our probability of success predictions into measurable portfolio-level outcomes. You will architect core systems that let us rigorously evaluate signals from our AI-driven predictions in public and private equities and our internal portfolio.

This role sits at the intersection of quantitative finance, healthcare data, and AI-driven drug development. If you're excited about applying portfolio construction and risk management fundamentals to one of the most consequential prediction problems in healthcare, this is the role.

Responsibilities

• Work with the team to implement and maintain core portfolio engine: order management system, execution simulation layer, portfolio construction service, and performance tracking
• Design risk frameworks that quantify exposure across a portfolio of drug development bets with radically different risk profiles, timelines, and failure modes
• Run rigorous backtesting experiments with strict temporal constraints to evaluate Formation strategies against baseline approaches and measure marginal signal from new evidence sources
• Coordinate across the organization to integrate internal Formation data sources (clinical trial data, genomic evidence, real-world data) and proprietary tooling into portfolio analytics pipelines
• Work with product and engineering teams to build dashboards and reporting that communicate portfolio performance, risk metrics, and strategy comparisons to both technical and executive stakeholders
• Collaborate with the broader data science team to ensure portfolio-level evaluation feeds back into model improvement and evidence prioritization

About You

We are looking for a highly motivated and experienced Data Scientist to join our team. The ideal candidate will have a strong background in data science, machine learning, and software development, with a proven track record of delivering high-quality results in a fast-paced environment.

Requirements

• MS or PhD in a quantitative field (statistics, finance, physics, computational science, engineering, or related)
• 1-3 years in a quantitative research, data science, or analytics role , finance, healthcare, academic research, or consulting all count; substantive internships qualify
• Strong Python programming skills with experience in data-intensive workflows (pandas, numpy, scipy)
• Solid grasp of core portfolio construction and risk concepts: position sizing, rebalancing, Sharpe ratio, drawdown, volatility, benchmark comparison
• Demonstrated ability to work with messy, real-world datasets , comfortable with data wrangling, deduplication, and quality assessment
• Clear communicator who can present quantitative results to both technical peers and business stakeholders

Preferred Qualifications

• Experience with backtesting frameworks or portfolio simulation (vectorbt, Backtrader, or custom implementations)
• Exposure to healthcare, pharma, or biotech data (clinical trials, claims data, -omics, real-world evidence)
• Familiarity with alternative data in a research or investment context
• Experience with probability-of-success modeling, drug development decision analysis, or health economics
• Comfort with LLMs or AI/ML pipelines in a production or research setting
• Familiarity with dashboard/visualization tools (Streamlit, Plotly, Dash) and pipeline orchestration (Dagster, Airflow)

Total Compensation Range: $154,500 - $202,000

**Compensation Individual compensation is determined by several factors, including role scope, geographic location, and skills & experience. Your offer will reflect where you fall within the range based on these considerations. In addition to base salary, we offer equity, comprehensive benefits, and generous perks. If the posted range doesn't match your expectations, we still encourage you to apply!

**Where We Hire Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with a hybrid model requiring 3 days per week in office. Applicants from the Research Triangle (NC) and San Francisco Bay Area may also be considered. Please apply only if you reside in these locations or are willing to relocate.

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You will carefully listen to stakeholder needs and then design rigorous math and physics analyses leading to clear and compelling value propositions.

You will work closely with related teams, including Systems Engineering, GNC, Propulsion, Communications, Flight Software, Mission Operations, and others.

This role is directly tied to ongoing, funded programs within Anduril’s Space Business Line. The programs require building and fielding a resilient, software-defined spacecraft systems across numerous mission threads.

We work with mission partners and customers to deploy reliable and robust capabilities on operationally relevant fielding timelines to meet complex challenges across the DOD and IC.

Responsibilities

• Develop model-driven analysis (and often the models themselves)
• Develop a deep understanding of transformational value of Anduril platform, autonomy, simulation, and perception products
• Use our advanced internal M&S capabilities to give our analyses an asymmetric advantage over competitors
• Convey the value through life of AI-powered distributed systems over traditional industrial offerings
• Provide rigorous analytical products which will be used to guide hardware engineering and convince stakeholders of our value advantage

Requirements

• Currently possesses and is able to maintain an active U.S. Secret security clearance
• Space Mission MS&A experience
• For example, working knowledge of constellation design, space trajectory design, and physics-level modeling across a wide variety of space missions
• Spacecraft & Payload MS&A experience, ability to perform physics-based trade-space analyses for spacecraft propulsion, power, thermal management, and payloads such as RADAR, SATCOM, and/or EOIR
• Outstanding communication skills to include visual presentation of complex data
• Strong background in orbital mechanics and space environment
• Proficiency with physics-math scripting (e.g., MATLAB, SIMULINK, Python+numpy, scipy)
• Strong engineering background, preferably in Astrodynamics, Aerospace Engineering, Dynamics and Controls Engineering, or other related engineering field

Preferred Qualifications

• 3+ years in a relevant Science/Engineering field
• Rendezvous Proximity Operations (RPO) Trajectory Design & Space Payloads experience
• Exceptional proficiency with physics-math scripting of your choice (e.g., MATLAB, SIMULINK, Python+numpy, scipy)
• Proficiency with STK and Astrogator
• Experience with genetic algorithms, machine learning, AI, and reinforcement learning algorithms

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Your expertise in computer vision algorithms, combined with your understanding of robotics principles, will be crucial in solving a wide variety of challenges involving visual perception, SLAM, motion planning, controls, and state estimation. This role requires not only technical expertise in computer vision and robotics but also the ability to make pragmatic engineering tradeoffs, considering the unique constraints of aerial platforms.

Your work will directly contribute to the seamless integration of Anduril's products, achieving critical outcomes in autonomous operations. This position demands strong systems-level knowledge and experience, as you'll be working on the intersection of computer vision, robotics, and autonomous systems.

If you are passionate about pushing the boundaries of computer vision in robotics, possess a 'Whatever It Takes' mindset, and can execute in an expedient, scalable, and pragmatic way while keeping the mission top-of-mind and making sound engineering decisions, then this role is for you.

Responsibilities:

• Work at the intersection of 3D perception and computer vision, developing robust algorithms that power real-time decision-making for autonomous aerial systems.

• Develop and implement advanced structure from motion and SLAM algorithms to create accurate 3D models from multiple camera inputs in real-time.

• Integrate perception outputs with path planning algorithms to enable autonomous navigation in complex, unstructured environments.

• Design experiments, data collection efforts, and curate training/evaluation sets to develop insights for both internal purposes and customers.

• Collaborate closely with robotics, software, and hardware teams to integrate perception algorithms into autonomous aerial systems.

• Work with vendors and government stakeholders to advance the state-of-the-art in perception and world modeling for autonomous aerial systems.

Required Qualifications:

• BS in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.

• Strong knowledge of 3D computer vision concepts, including multi-view geometry, camera models, photogrammetry, depth estimation, and 3D reconstruction techniques.

• Fluency in standard domain libraries (numpy, opencv, pytorch, etc).

• Proven understanding of data structures, algorithms, concurrency, and code optimization.

• Experience working with Python, PyTorch, or C++ programming languages.

• Experience deploying software to end customers, internal or external.

• Must be willing to travel 25%.

• Eligible to obtain an active U.S. Secret security clearance.

Preferred Qualifications:

• MS or PhD in Robotics, Computer Science, Engineering, or related field.

• Experience with perception systems for aerial robotics or other highly dynamic platforms.

• Experience with real-world sensor integrations, including LiDAR, RGB-D cameras, IR cameras, stereo cameras, or TOF cameras.

• Experience with GPU / CUDA programming for accelerated computer vision processing.

• Knowledge of path planning algorithms and their integration with perception systems in dynamic environments.

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While identifying solutions to customers' biggest challenges in big data, analytics, data engineering, and data science, you will work with the sales team to propose solutions to customers. You report to the Field Engineering Manager.

Your impact:

• You will become an expert in big data analysis in the architecture and design aspect.
• You will guide potential customers to adoption of Databricks.
• You will support customers by creating reference architectures, high-level deployment and migration plans, and demo applications.
• You will integrate Databricks and third-party applications to support customer architectures.
• You will lead workshops, seminars, and meetups to engage with the technical community.
• You will build successful relationships with clients in your assigned segment, providing both technical and business value.
• You will discover customer use cases,
• Optimize existing customers' Databricks environments,
• Engage in activities to improve Databricks products.

Requirements/Experience:

• Experience working with external clients in various industries as a pre-sales or post-sales professional.
• Experience demonstrating technical concepts, presenting, and using whiteboards.
• Experience designing and implementing architecture in public cloud (AWS, Azure, GCP).
• Experience working with enterprise accounts.
• Fluent communication in Japanese and business-level writing in English.
• Basic understanding of data domain or machine learning/AI domain, and SQL coding skills.

Desirable Experience/Skills:

• Understanding of a core strength in data engineering or data science in a customer-facing pre-sales or consulting role.
• Experience with big data technologies such as Apache Spark, AI, data science, Hadoop, Cassandra.
• Experience coding in Python, Scala, Java, or R using Apache Spark.
• Development experience in data domain or machine learning/AI domain, particularly in Python (Pandas, NumPy, etc.).

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You will collaborate closely with technical teams to support the development and refinement of new AI capabilities, with a primary focus on quantitative financial risk management domains. Your expertise will drive the selection and rigorous resolution of complex risk-related problems, including market risk modeling, credit and counterparty risk, liquidity and funding risk, operational and model risk, stress testing & scenario analysis, Value at Risk (VaR)/Expected Shortfall (ES), risk attribution, capital allocation (economic/regulatory), and enterprise-wide risk frameworks under regulatory regimes (Basel, Dodd-Frank, IFRS 9, etc.).

This role requires exceptional quantitative rigor, rapid adaptation to evolving guidelines, and the ability to deliver precise, technically sound critiques, derivations, and solutions in a fast-paced environment. As a Finance Risk Expert, you will directly support xAI's mission by helping train and refine frontier AI models. You will teach the models how risk professionals quantify uncertainties, model tail events, assess portfolio vulnerabilities, ensure regulatory compliance, perform stress testing, and make data-driven decisions to protect capital and maintain financial stability.

Your tasks may include recording audio walkthroughs of risk models, participating in video-based scenario reasoning, or producing detailed quantitative risk analysis traces. All outputs are considered work-for-hire and owned by xAI.

Responsibilities:

• Use proprietary annotation and evaluation software to deliver accurate labels, rankings, critiques, and comprehensive solutions on assigned projects
• Consistently produce high-quality, curated data that adheres to strict quantitative and regulatory standards
• Collaborate with engineers and researchers to develop and iterate on new training tasks, risk-specific benchmarks, and evaluation frameworks
• Provide constructive feedback to improve the efficiency, precision, and usability of annotation and data-collection tools
• Select and solve challenging problems from financial risk domains where you have deep expertise

Basic Qualifications:

• Master’s or PhD in a quantitative discipline: Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Econometrics, Risk Management, Operations Research, Physics, Computer Science (with risk/finance focus), or closely related field or equivalent professional experience as a quantitative risk analyst, risk modeler, or risk quant
• Excellent written and verbal English communication (technical reports, regulatory documentation, explanatory breakdowns)
• Strong familiarity with financial risk data sources and platforms (Bloomberg, Refinitiv, Moody’s Analytics, S&P Capital IQ, RiskMetrics, internal bank risk systems, regulatory filings, Basel/FRB datasets, etc.)
• Exceptional analytical reasoning, attention to detail, and ability to exercise sound judgment with incomplete or ambiguous data

Preferred Skills and Experience:

• Professional experience in quantitative risk management, model development/validation, or risk analytics at a bank, hedge fund, asset manager, insurance company, regulator, or consulting firm
• Track record of publication(s) or contributions in refereed journals/conferences on risk, econometrics, statistics, or quantitative finance
• Prior teaching, mentoring, or training experience (university, industry workshops, regulatory training)
• Proficiency in Python/R for risk modeling (pandas, NumPy, SciPy, statsmodels, QuantLib, PyTorch/TensorFlow for ML risk models, etc.) and familiarity with risk systems (Murex, Calypso, Numerix, etc.)
• Experience with Monte Carlo simulation, copula models, stochastic processes, time-series analysis, extreme value theory, or machine learning for risk (anomaly detection, credit scoring, etc.)
• Knowledge of regulatory capital frameworks (Basel III/IV, FRB CCAR, SR 11-7 model risk guidance, IFRS 9/CECL, Solvency II)
• CFA, FRM, PRM, CQF, or similar risk-focused certifications
• Previous exposure to large language models, AI safety, or quantitative evaluation pipelines

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time
• We are unable to provide visa sponsorship
• For those who will be working from a personal device, your computer must meet xAI’s minimum hardware requirements

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You will collaborate closely with our technical teams to support the development and refinement of new AI capabilities, with a particular emphasis on quantitative trading domains.

Your expertise will help select and solve challenging problems in systematic and quantitative strategies , including statistical arbitrage, factor investing, market microstructure modeling, high-frequency / execution algorithms, risk premia harvesting, machine learning-based alpha generation, and portfolio optimisation under realistic constraints.

This role requires strong analytical thinking, rapid adaptation to evolving guidelines, and the ability to provide rigorous, technically sound critiques and solutions in a fast-moving environment.

As a Quantitative Trader, you will directly contribute to xAI's mission by helping train and refine our frontier AI models.

You will teach the models how quantitative traders reason, model markets, evaluate signals, manage risk, and interact with complex financial data and systems.

This involves providing high-quality data in various formats (text, voice, video), writing detailed annotations, critiquing model outputs, recording audio explanations, and occasionally participating in structured video sessions.

We are looking for individuals who are enthusiastic about these data-generation activities, as they form a core part of advancing xAI’s goals in scientific discovery and real-world reasoning.

Quantitative Traders provide labeling, annotation, evaluation, and expert reasoning services across text, voice, and video data modalities to support model training and evaluation.

The role may include recording audio responses, participating in video-based tasks, or producing step-by-step quantitative reasoning traces , all of which are essential job functions required to fulfill xAI’s mission.

All outputs are considered work-for-hire and owned by xAI.

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You will lead environmental and stress testing efforts, including temperature cycling, vibration, HALT, and HASS, conduct failure analysis and materials characterization, and analyze root cause investigations for manufacturing non-conformances and field returns. You'll participate in design reviews and FMEA activities, shape material selection and manufacturing requirements, analyze test and field data using reliability modeling tools, and help develop corrective actions and process improvements that elevate hardware reliability across the program.

Responsibilities: ude and implement design-for-reliability best practices, conducting rigorous testing, shaping manufacturing requirements, selecting materials, and analyzing field data to enhance the robustness of VBAT hardware. Perform stress screening, environmental testing, and drive failure analysis to ensure flight hardware meets reliability and performance targets. Analyze designs and test results to identify potential failure modes and mitigations. Collaborate with design engineers to implement design for reliability best practices early in design. Act as a key stakeholder in reviewing and approving designs for release. Participate in design reviews and failure mode effects analysis (FMEA) to assess potential reliability issues. Investigate manufacturing non-conformances and field hardware failures to determine root cause. Travel as needed to perform deep dives into supplier processes. Develop and recommend corrective actions to address identified reliability issues. Utilize reliability modeling and simulation tools to predict system performance and lifespan. Stay current with industry trends, advancements, and best practices in hardware reliability engineering. Propose and implement process improvements to drive improvements in reliability across the program.

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Responsibilities:

• Design, characterize, and deliver algorithms such as channelizers, frequency agile detection, adaptive filters, MIMO, wideband detectors, and other algorithms related to signal sorting
• Write and contribute to existing Python repositories using CUDA and PyTorch
• Own requirements, ICDs, and verification from concept through delivery
• Stay current: Track and insert advances in signal processing techniques and associated technologies, adaptive beamforming, RF machine learning, and resilient PNT for GPS-denied ops.

Required Qualifications:

• Masters Degree in Electrical, Computer or Systems Engineering or related field with Graduate study emphasis in Signal Processing; OR a Bachelor’s Degree in an Engineering discipline with 3-5 years relevant working Signal Processing Experience
• Intermediate to advanced proficiency in Python
• Willingness to support critical test events that occasionally require extended hours/weekends.
• Ability to obtain and maintain a security clearance. Learn more about Security Clearances here.
• Must be a U.S. Person (see ITAR Regulations below) due to required access to U.S. export-controlled information or facilities

Bonus Points:

• PhD in Electrical Engineering, Computer Engineering, or related field
• 5+ years’ experience with EW subsystems and payloads.
• EA/ECM technique design (deception, Digital RF Memory, coherent/non-coherent techniques).
• Comms system design (LPI/LPD, Waveform-of-Interest exploitation)
• RF machine learning for emitter ID, modulation/classification, anomaly detection, PDW creation
• Tools Experience: ADS/AWR/SystemVue, MATLAB/Simulink, Python (NumPy/SciPy), GNU Radio/SDR (USRP/RFSoC), VITA-49; HDL/firmware experience also helpful (Vivado/Quartus/Libero).
• Clearance: Active Secret or ability to obtain and maintain; TS/SCI eligibility preferred. ITAR/EAR-controlled work.
• Field work: supporting periodic travel for flight tests and customer demonstrations/support
• Mindset: Builder-tester who loves first-principles RF, rapid lab iteration, and getting hardware flying fast.

What We Offer:

• Competitive salary, stock options and benefits, including health, vision and dental.
• 401K enrollment at 90 days.
• Generous PTO + most Federal Holidays observed.
• Collaborative and inclusive work environment.
• Access to the latest tools and technologies.
• High levels of responsibility and autonomy.
• Professional growth and development opportunities.
• Access to the hardest problems in electronic warfare.

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This role requires an onsite presence in our El Segundo, CA HQ; a remote work environment is not considered for this opportunity.

Key Responsibilities:

• Design, validate & deliver RF payload subsystems: Design, Integration and Testing of Antennas, RF front ends, SDRs and provide validation of operation. Support development and analysis of RF performance metrics.

• Own requirements, ICDs, and verification from concept through delivery

• Stay current: Track and insert advances in relevant technologies, SDRs, RF Systems, RF machine learning, and PNT.

Qualifications:

• BS/MS in Electrical Engineering, Computer Engineering, or related field

• Antenna and receiver design across analog/RF/mixed-signal domains: mixers, PLLs/LOs, gain/linearity/noise trades; ability to turn simulations into reality.

• Channelizers & wideband architectures: filter banks, analog/digital down conversion, sample-rate planning, clocking/synchronization.

• Willingness to support critical test events that occasionally require extended hours/weekends

• Ability to obtain and maintain a security clearance

• Must be a U.S. Person (see ITAR Regulations below) due to required access to U.S. export-controlled information or facilities

Bonus Points:

• PhD in Electrical Engineering, Computer Engineering, or related field

• 5+ years’ experience with EW subsystems and payloads

• EA/ECM technique design (deception, Digital RF Memory, coherent/non-coherent techniques)

• Digital Signal processing: Design characterize and deliver channelizers, wideband detection/classification, MIMO/digital-arrays, and algorithms in MATLAB/Python/C++

• Communication / Waveform system design

• RF machine learning for emitter ID, modulation/classification, anomaly detection, PDW creation

• Tools Experience: ADS/AWR/SystemVue, MATLAB/Simulink, Python (NumPy/SciPy), GNU Radio/SDR (USRP/RFSoC), VITA-49; HDL/firmware experience; also helpful (Vivado/Quartus/Libero).

• Clearance: Active Secret or ability to obtain and maintain; TS/SCI eligibility preferred. ITAR/EAR-controlled work. Learn more about Security Clearances here.

• Field work: supporting periodic travel for flight tests and customer demonstrations/support

• Mindset: Builder-tester who loves first-principles RF, rapid lab iteration, and getting hardware flying fast

What We Offer:

• Competitive salary, stock options and benefits, including health, vision and dental.

• 401K enrollment at 90 days.

• Generous PTO + most Federal Holidays observed.

• Collaborative and inclusive work environment.

• Access to the latest tools and technologies.

• High levels of responsibility and autonomy.

• Professional growth and development opportunities.

• Access to the hardest problems in electronic warfare.

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Software Engineer  - Silicon Validation Tools (SerDes)

Mississauga, Ontario, Canada

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Category: EngineeringHire Type: Employee

Job ID 16183Date posted 03/22/2026

We Are:

At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, from self-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and software content. Join us to transform the future through continuous technological innovation.

You Are:

You are a hands-on software engineer passionate about bridging the gap between hardware and software in high-speed silicon validation environments. You thrive in lab-heavy settings, working directly with advanced instruments and hardware abstraction layers. Your expertise in Python allows you to architect robust automation frameworks and reusable libraries, streamlining complex workflows and ensuring repeatable, high-quality results. You’re comfortable translating intricate MATLAB algorithms into efficient Python code, maintaining numerical equivalence and clear documentation for future maintainability. Your experience integrating C/C++ SDKs, DLLs, and libraries into Python empowers seamless cross-team collaboration with firmware and software teams worldwide. You are meticulous in your approach to code governance, CI/CD pipelines, and release management, ensuring that your code is reliable, maintainable, and well-documented.

You communicate clearly, translating technical requirements into actionable solutions and collaborating across validation, SDK, firmware, and software teams. You are proactive in identifying opportunities for process improvement, championing best practices, and mentoring teammates. Your curiosity drives you to stay current with industry trends, and your adaptability shines in fast-paced environments where innovation and continuous improvement are valued. You are committed to delivering intuitive GUIs and data tools that empower your team to make informed decisions, reduce operator error, and streamline bench operations. With a strong foundation in high-speed SerDes technologies and lab instrumentation, you are ready to make a lasting impact on industry-leading IP and silicon validation processes.

What You’ll Be Doing:

• Defining and maintaining Python automation architecture, folder/repo structure, and coding standards for lab environments.

• Building hardware-abstraction layers for lab instruments (J-BERT, oscilloscopes, pattern generators, power supplies) using VISA/SCPI and vendor APIs.

• Creating reusable libraries for test sequencing, calibration/adaptation flows, results logging, fault handling, and multi-bench resource scheduling.

• Translating MATLAB algorithms and calibration scripts into robust Python (NumPy/SciPy/Pandas), ensuring numerical equivalence and documenting migration notes.

• Developing and hardening drivers/wrappers for Keysight/Teledyne-LeCroy/R&S instruments, including connection management, waveform acquisition, and compliance scripts.

• Integrating SDK C/C++ code, DLLs, and shared libraries into Python via ctypes/cffi/SWIG, collaborating with firmware teams to validate features and APIs.

• Managing code repositories (Git/Perforce), branching strategies, code reviews, release tagging, and CI/CD pipelines for linting, testing, and packaging.

• Building internal GUIs for bench control, run setup, live plots, and progress tracking, as well as data processing pipelines for quick-turn analysis and report generation.

The Impact You Will Have:

• Accelerate SerDes bring-up and characterization through standardized Python automation and instrument libraries, reducing time-to-first-measurement and increasing bench throughput.

• Enhance efficiency and reliability of Silicon Validation processes with robust frameworks, CI-verified packages, and repeatable workflows.

• Improve test quality, reproducibility, and data analysis by shipping versioned tools, enforcing parity on MATLAB to Python conversions, and delivering clear analysis artifacts.

• Contribute directly to the success of high-speed, mixed-signal SerDes IP, enabling faster SDK/FW feature validation and higher confidence in release readiness.

• Support cutting-edge IP solutions that drive industry innovation by turning validation requirements into dependable software and GUIs adopted across benches.

• Streamline communication and day-to-day operations across Validation, FW, SDK, Software via documented interfaces, shared roadmaps, and predictable release notes.

• Increase code reuse and maintainability with a clear repo structure, a reusable hardware-abstraction layer, and shared GUI components that standardize user experience.

• Deliver intuitive, maintainable GUIs for bring-up and mass-char workflows, reducing operator error and enabling telemetry-driven improvements over time.

• Foster a culture of innovation and continuous improvement through mentorship, code reviews, documentation, and knowledge sharing within the validation team.

What You’ll Need:

• 2–6 years professional software engineering experience building automation frameworks or tooling in a hardware or lab environment.

• Strong proficiency in Python (OOP, packaging, virtual environments, logging, multithreading for instrument I/O).

• Experience controlling lab instruments via SCPI/VISA and vendor SDKs/APIs; comfortable with Windows and Linux benches.

• Proven skill integrating native libraries (C/C++ DLL/.so) into Python and debugging across the boundary.

• Solid practice with Git: code reviews, branching strategies, conflict resolution, and release tagging.

• Data skills: NumPy/Pandas, CSV/Parquet, plotting, and producing analysis artifacts usable by the team.

• Clear communicator who can translate validation requirements into robust software and collaborate across SDK, FW, and SW teams.

Who You Are:

• Analytical thinker with strong problem-solving skills.

• Collaborative team player who thrives in cross-functional environments.

• Detail-oriented and organized in both code and documentation.

• Curious and eager to learn new technologies and methodologies.

• Adaptable, proactive, and comfortable with ambiguity and innovation.

• Effective communicator, able to translate complex requirements into actionable solutions.

• Mentor and knowledge sharer, fostering a culture of continuous improvement.

The Team You’ll Be A Part Of:

You’ll join the SerDes Silicon Validation team, a dynamic group of engineers dedicated to enabling high-speed IP innovation through rigorous hardware validation and software automation. The team works closely with worldwide software, firmware, and SDK teams, collaborating to deliver robust tools, frameworks, and GUIs that accelerate bring-up, characterization, and validation workflows. Together, you’ll drive advancements in silicon validation, empower efficient lab operations, and shape the future of high-performance IP solutions.

Rewards and Benefits:

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

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Our products will put artists and songwriters first, through four key principles:

• Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later.
• Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music.
• Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions.
• Artist-fan connection: AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans.

As a Research Scientist, you will conduct groundbreaking research in music generation, run large-scale experiments, create practical applications, and collaborate with a cross-functional team to craft innovative solutions to complex challenges.

You will have a direct impact on Spotify’s products, tools, and services, working on projects that influence the entire organization. You will also engage with the broader research community by publishing your findings, delivering talks, and attending top conferences.

We offer a flexible work arrangement, allowing you to work where you work best, as long as you are within the EMEA region and operate within the Central European and GMT time zone for collaboration.

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Our products will put artists and songwriters first, through four key principles:

• Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later.

• Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music.

• Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions.

• Artist-fan connection: AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans.

As a Staff Research Scientist, you will conduct groundbreaking research in music generation, run large-scale experiments, create practical applications, and collaborate with a cross-functional team to craft innovative solutions to complex challenges.

You will have a direct impact on Spotify’s products, tools, and services, working on projects that influence the entire organization. You will also engage with the broader research community by publishing your findings, delivering talks, and attending top conferences.

We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location. This team operates within the Eastern Standard time zone for collaboration.

Core working hours are CET 3pm-6pm / EST 9am-12pm.

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Your work may involve brainstorming new disruptive ideas that could become the next generation of frontier AI models, particularly within the text diffusion space. You will prototype and develop these ideas with the rest of the team, contributing directly to Gemini Diffusion research. You will solve key research challenges by designing and executing experimental research on text diffusion models, sharing analyses, and proposing next steps. You will rigorously validate the theoretical and practical impact of our work at a large scale. You will work collaboratively with other Generative AI teams to move the technologies we develop out of the lab and into production. You will advance the fundamental architecture, algorithmic design, and capabilities of large-scale diffusion models. You will bring deep scientific expertise into our projects, sharing your insights and knowledge with other researchers and engineers.

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Constructor is a search and discovery platform for ecommerce, built to optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house using transformers and generative LLMs.

Role Details

As an Analytics Engineer on the Offsite Search Optimization team, you will improve the e-commerce experience for hundreds of millions of users across the world by making it faster and more personalized. The team's mission is to bridge the gap between onsite product discovery and external discovery platforms, ensuring that Constructor-powered websites can be found, understood, and correctly represented by both Google and Generative engines.

Responsibilities

• Build measurable foundations to track visibility, traffic sources, and performance across SEO and GEO.
• Build the architecture to run technical checkups on customer websites, assess their optimisation level, and provide clear recommendations on what needs to be fixed.
• Partner with Product teams to adapt enriched content for SEO/GEO and package it toward external discoverability needs.
• Define an SEO/GEO enablement layer with tools, playbooks, and frameworks to scale best practices across teams and customers.

Challenges You Will Tackle

• Complete visibility of the product discovery from external sources.
• Accurate measurement of organic, branded, AI-driven traffic.
• Create a unified model of landing pages.
• A framework for future SEO experiments (canonical tests, template variations, structured data tests).
• Internal tools that other teams can plug into.
• Run the adoption process of best practices to other teams

Requirements

• Strong SQL and Python (requests, pandas, numpy, etc).
• Experience building data integrations between products.
• Experience with APIs & auth (OAuth2, GA4 and Google Search Analytics API).
• Understanding of ETL/ELT workflows on PySpark.
• Building logic of data extraction from non-structured data (referrers, canonical URLs, page types).

Nice to Have

• Experience with BigQuery or similar.
• JS execution basics (how SSR/CSR affects crawlers).
• Knowledge of SEO fundamentals.
• Experience with BI systems (Looker/Metabase/Superset).
• Experience with logs or event handling systems

Benefits

• Work with smart and empathetic people who will help you grow and make a meaningful impact.
• Regular team offsite events to connect and collaborate.
• Fully remote team - choose where you live.
• Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year.
• Work from home stipend! We want you to have the resources you need to set up your home office.
• Apple laptops provided for new employees.
• Training and development budget for every employee, refreshed each year.
• Maternity & Paternity leave for qualified employees.
• Base salary: $80k–$120K USD, depending on knowledge, skills, experience, and interview results.
• Stock options - offered in addition to the base salary

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We're looking for a skilled Merchant Intelligence Team Member to join our team at Constructor. As a key member of our Merchant Intelligence team, you will play a critical role in helping merchandizers achieve their ecommerce goals, increasing satisfaction with their sites and retention of customers.

Key Responsibilities

• Enhance the dashboard experience for merchandizers by building analytics that provide actionable insights to improve e-commerce KPIs.
• Perform data exploration and research user behavior.
• Implement end-to-end data pipelines to support real-time analytics for essential business metrics.
• Take part in product research and development, iterate with prototypes and customer product interviews.

Requirements

• You are proficient in BI tools (both data analysis and building dashboards for engineers and non-technical folks).
• You are keen to not just prepare more data, but to think critically about how that data can deliver valuable insights and drive impactful decisions for non-technical end users.
• You are an excellent communicator with the ability to translate business requests into technical language and vice versa.
• You are excited to leverage massive amounts of data to drive product innovation and deliver business value.
• You are proficient at SQL (any variant) and well-versed in exploratory data analysis with Python (pandas & numpy, data visualization libraries)
• Practical familiarity with the big data stack (Spark, Hive, Databricks).
• You are adept at fast prototyping and providing analytical support for initiatives in the e-commerce space by identifying and focusing on relevant features and metrics.
• You are willing to develop and maintain effective communication tools to report business performance and inform decision-making at a cross-functional level.
• You get excited to hear feedback from customers and figure out potential solutions.
• You're familiar with math statistics.

Benefits

• Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year
• Fully remote team - choose where you live
• Work from home stipend! We want you to have the resources you need to set up your home office
• Apple laptops provided for new employees
• Training and development budget for every employee, refreshed each year
• Maternity & Paternity leave for qualified employees
• Work with smart people who will help you grow and make a meaningful impact
• Base salary: $80k–$120k USD, depending on knowledge, skills, experience, and interview results
• Stock options - offered in addition to the base salary
• Regular team offsites to connect and collaborate

Diversity, Equity, and Inclusion at Constructor

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In this role, you’ll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse multimodal data sources critical to model development. You will lead efforts to:

• Develop novel data collection strategies
• Improve dataset quality and integrity
• Understand data-driven model behaviors
• Align datasets with ethical and societal values

This is a cross-disciplinary, high-impact role ideal for engineers who want to push the boundaries of what AI can learn from data, especially in multimodal contexts.

Microsoft Superintelligence Team

The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control.

Responsibilities

• Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
• Develop and maintain scalable data pipelines for multimodal ingestion, preprocessing, filtering, and annotation.
• Analyze real-world multimodal datasets to assess quality, diversity, relevance, and identify areas for improvement.
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning.
• Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.

Embody our culture and values.

Qualifications

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.
• 2+ years of experience in data analysis or data engineering, including work with large-scale datasets that are unstructured or semi-structured.
• Proficiency in statistics and exploratory data analysis methods.
• Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam.
• Ability to communicate technical findings clearly to research and product teams.

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In this role, you’ll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to:

• Develop novel data collection strategies
• Improve dataset quality and integrity
• Understand data-driven model behaviors
• Train models to understand the impact of data and data mixes
• Align datasets with ethical and societal values

This is a cross-disciplinary, high-impact role ideal for engineers and researchers who want to push the boundaries of what AI can learn from data.

Microsoft Superintelligence Team

The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control.

Responsibilities

• Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
• Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.
• Analyze real-world text datasets to assess quality, diversity, relevance, and identify areas for improvement.
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning.
• Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.

Embody our culture and values.

Qualifications

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.
• 2+ years of experience in data analysis or data engineering, including work with large-scale datasets that are unstructured or semi-structured.
• Proficiency in statistics and exploratory data analysis methods.
• Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam.
• Ability to communicate technical findings clearly to research and product teams.

Software Engineering IC4

• The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year.

Software Engineering IC5

• The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

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Develop novel data collection strategies

Improve dataset quality and integrity

Understand data-driven model behaviors

Align datasets with ethical and societal values

This is a cross-disciplinary, high-impact role ideal for engineers who want to push the boundaries of what AI can learn from data, especially in multimodal contexts.

XML job scraping automation by YubHub

In this role, you’ll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to:

• Develop novel data collection strategies
• Improve dataset quality and integrity
• Understand data-driven model behaviours
• Train models to understand the impact of data and data mixes
• Align datasets with ethical and societal values

This is a cross-disciplinary, high-impact role ideal for engineers and researchers who want to push the boundaries of what AI can learn from data.

Microsoft Superintelligence Team

The Microsoft Superintelligence Team is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control.

Responsibilities

• Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
• Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.
• Analyze real-world text datasets to assess quality, diversity, relevance, and identify areas for improvement.
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning.
• Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.

Qualifications

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.
• 2+ years of experience in data analysis or data engineering, including work with large-scale datasets that are unstructured or semi-structured.
• Proficiency in statistics and exploratory data analysis methods.

XML job scraping automation by YubHub

In this role, you’ll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to:

• Develop novel data collection strategies
• Improve dataset quality and integrity
• Understand data-driven model behaviours
• Train models to understand the impact of data and data mixes
• Align datasets with ethical and societal values

This is a cross-disciplinary, high-impact role ideal for engineers and researchers who want to push the boundaries of what AI can learn from data.

Microsoft Superintelligence Team

The Microsoft Superintelligence Team is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control.

Responsibilities

• Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
• Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.
• Analyze real-world text datasets to assess quality, diversity, relevance, and identify areas for improvement.
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning.
• Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.

Qualifications

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.
• 2+ years of experience in data analysis or data engineering, including work with large-scale datasets that are unstructured or semi-structured.
• Proficiency in statistics and exploratory data analysis methods.

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Microsoft AI are looking for a talented Member of Technical Staff - Data Research Engineer at their Redmond office. This role sits at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse multimodal data sources critical to model development. You will lead efforts to develop novel data collection strategies, improve dataset quality and integrity, understand data-driven model behaviors, and align datasets with ethical and societal values.

About the Role

As a Data Research Engineer, you will be responsible for creating high-quality datasets for training and evaluation, running experiments on new datasets (data ablations) to assess their impact and determine the most effective data. You will also develop and maintain scalable data pipelines for multimodal ingestion, preprocessing, filtering, and annotation. Additionally, you will analyze real-world multimodal datasets to assess quality, diversity, relevance, and identify areas for improvement. You will build lightweight tools and workflows for dataset auditing, visualization, and versioning. You will collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.

Accountabilities

• Create high-quality datasets for training and evaluation
• Run experiments on new datasets (data ablations) to assess their impact and determine the most effective data
• Develop and maintain scalable data pipelines for multimodal ingestion, preprocessing, filtering, and annotation
• Analyze real-world multimodal datasets to assess quality, diversity, relevance, and identify areas for improvement
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.)

Technical skills:

• Proficiency in statistics and exploratory data analysis methods
• Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam

Personal attributes:

• Ability to communicate technical findings clearly to research and product teams

Benefits

• Competitive salary
• Comprehensive benefits package
• Opportunities for professional growth and development
• Collaborative and dynamic work environment

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Microsoft AI are looking for a talented Member of Technical Staff - Pretraining Text Data at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

We are seeking engineers and researchers to join our Pretraining Text Data team, where we are building the next generation of foundation large language models. If you are passionate about designing and curating high-quality datasets to power frontier AI models, this role is for you. In this role, you’ll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to:

• Develop novel data collection strategies
• Improve dataset quality and integrity
• Understand data-driven model behaviors
• Train models to understand the impact of data and data mixes
• Align datasets with ethical and societal values

Accountabilities

• Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
• Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.
• Analyze real-world text datasets to assess quality, diversity, relevance, and identify areas for improvement.
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning.
• Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.

Technical skills:

• Proficiency in statistics and exploratory data analysis methods.
• Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam.

Personal attributes:

• Ability to communicate technical findings clearly to research and product teams.

Benefits

• Competitive salary
• Comprehensive benefits package
• Opportunities for professional growth and development
• Collaborative and dynamic work environment
• Access to cutting-edge technology and resources

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Microsoft AI are looking for a talented Member of Technical Staff, Data Research Engineer to join their MAI Superintelligence Team in Zürich, Switzerland. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Data Research Engineer, you will be responsible for creating high-quality datasets for training and evaluation, running experiments on new datasets to assess their impact, and developing and maintaining scalable data pipelines for multimodal ingestion, pre-processing, filtering, and annotation. You will also analyze real-world multimodal datasets to assess quality, diversity, relevance, and identify areas for improvement. Additionally, you will build lightweight tools and workflows for dataset auditing, visualization, and versioning, and collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.

Accountabilities

• Create high-quality datasets for training and evaluation
• Run experiments on new datasets to assess their impact and determine the most effective data
• Develop and maintain scalable data pipelines for multimodal ingestion, pre-processing, filtering, and annotation
• Analyze real-world multimodal datasets to assess quality, diversity, relevance, and identify areas for improvement
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning

The Candidate we're looking for

Experience:

• Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or a related technical field
• Technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.)

Technical skills:

• Proficiency in statistics and exploratory data analysis methods
• Experience in data analysis or data engineering

Personal attributes:

• Ability to communicate technical findings effectively to research and product teams

Benefits

• Competitive salary and benefits package
• Opportunity to work with a leading technology company in the AI industry
• Collaborative and dynamic work environment
• Professional development opportunities

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Microsoft AI are looking for a talented Data Research Engineer to join their MAI Superintelligence Team in London. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Data Research Engineer, you will be responsible for creating high-quality datasets for training and evaluation, running experiments on new datasets to assess their impact, and developing and maintaining scalable data pipelines for multimodal ingestion, pre-processing, filtering, and annotation. You will also analyse real-world multimodal datasets to assess quality, diversity, relevance, and identify areas for improvement.

Accountabilities

• Create high-quality datasets for training and evaluation
• Run experiments on new datasets to assess their impact and determine the most effective data
• Develop and maintain scalable data pipelines for multimodal ingestion, pre-processing, filtering, and annotation

The Candidate we're looking for

Experience:

• Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or a related technical field
• Technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.)

Technical skills:

• Proficiency in statistics and exploratory data analysis methods
• Familiarity with data processing frameworks such as Spark, Ray, Apache Beam

Personal attributes:

• Ability to communicate technical findings effectively to research and product teams

Benefits

• Competitive salary and benefits package
• Opportunities for professional growth and development
• Collaborative and dynamic work environment

XML job scraping automation by YubHub

Microsoft AI are looking for a talented Member of Technical Staff - Pretraining Text Data at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

In this role, you'll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to:

• Develop novel data collection strategies
• Improve dataset quality and integrity
• Understand data-driven model behaviors
• Train models to understand the impact of data and data mixes
• Align datasets with ethical and societal values

Accountabilities

• Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
• Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.

Technical skills:

• Proficiency in statistics and exploratory data analysis methods.
• Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam.

Personal attributes:

• Ability to communicate technical findings clearly to research and product teams.

Benefits

• Competitive salary
• Comprehensive benefits package
• Opportunities for professional growth and development
• Collaborative and dynamic work environment

XML job scraping automation by YubHub

Microsoft are looking for a talented Member of Technical Staff - Pretraining Text Data at their London office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

In this role, you'll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to: Develop novel data collection strategies Improve dataset quality and integrity Understand data-driven model behaviors Train models to understand the impact of data and data mixes Align datasets with ethical and societal values

Accountabilities

• Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
• Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.

Technical skills:

• Proficiency in statistics and exploratory data analysis methods.

Personal attributes:

• Embody our culture and values.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.

XML job scraping automation by YubHub

Microsoft are looking for a talented Member of Technical Staff - Pretraining Text Data at their London office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

In this role, you'll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to:

• Develop novel data collection strategies
• Improve dataset quality and integrity
• Understand data-driven model behaviors
• Train models to understand the impact of data and data mixes
• Align datasets with ethical and societal values

Accountabilities

• Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
• Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.
• Analyze real-world text datasets to assess quality, diversity, relevance, and identify areas for improvement.
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning.
• Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.

Technical skills:

• Proficiency in statistics and exploratory data analysis methods.
• Experience with large-scale datasets that are unstructured or semi-structured.

Personal attributes:

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.
• Access to cutting-edge technology and tools.

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What you'll do

• Create and deliver production-ready, scalable, and high-quality machine learning models and associated algorithms
• Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap

What you need

• PhD in Computer Science, Mathematics, or related field, or 3+ years of relevant industry experience
• Expert, hands-on knowledge of deep learning, foundational models, and vision and/or language, incl. local deployment of open models, continued training and fine-tuning cloud and local models
• Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch)

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What you'll do

Participating in the planning, architecture, and research phases for next-generation software products and systems.

• Leading complex development activities, including software design, solver research, and user experience enhancements.

What you need

Bachelor’s degree in Engineering, Computer Science, or related field with 5+ years of experience; Master’s with 3+ years; PhD with 1+ year.

• Expertise in software design and development methodologies, with commercial experience.

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