The goal of the team is to build a unified set of risk data for decision-makers at the firm level to make informed decisions about the firm's complex set of positions. The team will be coordinating with multiple different asset-class risk teams to build the firm's high-level view, including building out individual asset-class risk analytics in cases where it is deemed necessary.

This role involves research into using many different statistical and probabilistic techniques to evolve the firm's understanding of risk. Key to the role will be understanding the ways in which different market structures impact their individual asset classes, the behavior of large market participants, shared traits of popular trading strategies, and developing probabilistic methodologies to anticipate potential stress scenarios.

Responsibilities:

• Build and validate cross-asset risk measures.
• Identify market factors across asset classes and identify common risk premia trades.
• Apply feature discovery and classification-style ML to identify and interpret portfolio/trade drivers with careful validation and robustness testing.
• Partner closely with asset class risk teams to test assumptions, interpret results, and drive adoption of the analytics.
• Develop forward-looking scenario models, identifying risks in the firm shared across asset classes.

Requirements:

• 1–5 years of hands-on experience in quantitative research, modeling, or applied ML
• Strong foundation in applied mathematics / statistics / machine learning (especially probability theory, linear algebra, calculus, and statistics)
• Demonstrated ability to design, implement, and validate models from scratch (not just apply off-the-shelf packages)
• Python proficiency for research prototyping and analysis
• Experience with deep learning frameworks (For example, PyTorch/TensorFlow)
• Strong research habits: hypothesis formation, experimentation, back testing/validation, and clear communication
• Financial markets experience is helpful but not required

The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future.

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This is a highly collaborative role. You'll work closely across pre-training, post-training, and product with world-class researchers, infrastructure engineers, and designers.

As a researcher in this role, you'll be expected to:

• Own research projects on audio training, low-latency inference, and conversational responsiveness.
• Design and train large-scale models that natively support audio input and output.
• Investigate scaling behaviour such as how data, model size, and compute affect capability and efficiency.
• Build and maintain audio data pipelines, including preprocessing, filtering, segmentation, and alignment for training and evaluation.
• Collaborate with data and infrastructure teams to scale audio training efficiently across distributed systems.
• Publish and present research that moves the entire community forward.

Share code, datasets, and insights that accelerate progress across industry and academia.

This role blends fundamental research and practical engineering, as we do not distinguish between the two roles internally. You will be expected to write high-performance code and read technical reports.

It's an excellent fit for someone who enjoys both deep theoretical exploration and hands-on experimentation, and who wants to shape the foundations of how AI learns.

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Responsibilities: Use proprietary tools to label and evaluate data. Support and ensure the delivery of high-quality curated data. Work with engineers to refine tasks, tools, and workflows. Design, select, and refine tasks grounded in real-world occupational math, for example: Insurance and risk: premiums, deductibles, expected loss calculations, simple risk modeling. Logistics and operations: inventory and reorder policies, capacity/throughput, basic cost optimization. Skilled trades: surveying and land measurement, electrical load calculations, machining tolerances, material estimation, blueprint and scale calculations. Finance and banking: loan amortization schedules, time value of money, portfolio and risk metrics. Accounting and tax: financial statements, reconciliations, depreciation, multi-bracket tax calculations, payroll. Health and social data: rates, ratios, simple biostatistics, survey-based metrics and policy-relevant indicators. Provide detailed, step-by-step solutions and evaluate model responses for correctness, adherence to domain rules (e.g., tax codes, building codes, basic regulatory or business constraints), clarity, and plausibility. Interpret, analyze, and execute tasks based on given instructions.

Basic Qualifications: A Master's or PhD in a quantitative field such as Mathematics, Statistics, Operations Research, Economics, Finance, Actuarial Science, or a closely related discipline with strong training in applied/occupational math; or A Bachelor's degree in one of the fields above plus substantial professional experience (e.g., 2+ years) in a math-heavy occupational domain such as finance, banking, insurance, accounting, logistics/supply chain, healthcare analytics, or policy analysis Professional licensure or certification in a skilled trade (e.g., licensed surveyor, master electrician, journeyman machinist) with demonstrated expertise in trade-specific mathematical calculations. Strong proficiency in applied mathematics relevant to at least one of the above domains (e.g., probability and statistics, financial math, optimization under constraints, geometric and measurement calculations, or similar). Proficiency in reading and writing, both in informal and professional English. Strong ability to navigate various information resources and databases. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience: Professional certifications in relevant fields (e.g., CFA, FRM, SOA exams, CPA, Six Sigma, PE, licensed surveyor, or similar) or demonstrably equivalent experience. Prior professional experience in one or more domains such as asset management, retail or commercial banking, insurance pricing/reserving, accounting/audit, logistics/supply chain planning, healthcare analytics, public policy analysis, or skilled trades. Previous AI Tutoring experience and/or experience teaching or training others in applied or occupational math topics. Experience building and reviewing complex spreadsheets, financial or risk models, dashboards, technical drawings, or similar artifacts.

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You will work closely with delivery leads, application developers, and other solutions architects, as well as internal and external partners to design, implement, and deliver bleeding edge quantum solutions on state-of-the-art quantum-inspired, quantum annealing, and quantum gate platforms for real-world defense and national security challenges.

The ideal candidate will combine a strong foundation in quantum computing principles with hands-on classical and quantum software development expertise. You will leverage your skills to translate complex problems into (hybrid) quantum algorithms, applications, and services.

This includes developing robust software implementations, and integrate quantum-enhanced solutions into existing and new defense systems.

If you are passionate about applying theoretical quantum concepts to deliver tangible, high-impact results, and thrive in an environment that values innovation, collaboration, and rapid prototyping, we encourage you to apply.

Key Responsibilities: Be a key contributor to the development of next-generation quantum-enhanced Anduril offerings and lead the design, development, and deployment of novel quantum-enhanced applications and services in the defense and national security domain. Develop impactful hybrid quantum algorithms and applications that promise significant decision advantages and focus on practical scalability and real-world applicability. Contribute knowledge of classical and quantum optimization algorithms and tools, evaluating, and communicating their pros and cons, current state-of-the-art, scaling behaviors, trade-offs, and cross-over points. Participate in the full (hybrid) quantum software development lifecycle, from concept and design to testing, deployment, and ongoing maintenance.

Requirements: Bachelor's degree in Computer Science, Quantum Information Science, Physics, Mathematics, or a closely related technical field. 3+ years of hands-on, professional software development experience with C, C++, Python, or another general-purpose compiled programming language. Practical experience in quantum computing, including programming quantum applications, or quantum circuit compilation. Proficiency with one or more leading quantum programming languages, SDKs, or APIs such as Qiskit, CUDA-Q, Q#, Cirq, PennyLane, or similar. Expertise in key mathematical techniques foundational to quantum computing, including linear algebra, matrix decompositions, probability theory, group theory, symmetry, and computational complexity. Proficient with database systems and SQL, with hands-on experience working with relational databases (e.g., PostgreSQL, Oracle, MySQL). Experience with Git version control, build tools, and CI/CD pipelines. Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing. Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment. Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences. Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance. Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.

Preferred Qualifications: Master's or Ph.D. in Quantum Information Science, Physics, Computer Science, or a related quantitative field. Familiarity with leading classical optimization tools and solvers (e.g., CPLEX, Gurobi, OR-Tools) and knowledge of mathematical modeling and classical optimization solution techniques. Experience building and deploying applications to solve complex business or defense problems for customers. Proven record of successful on-time delivery of complex software projects with a high degree of predictability and quality. Experience with deployment of code in distributed environments, cloud application development (e.g., AWS, Azure, GCP), and RESTful API-driven architectures. Experience with high-performance computing (HPC) environments or parallel programming. Familiarity with quantum hardware platforms and their unique characteristics. Prior experience in defense, aerospace, or related industries applying advanced technologies. Willingness to travel up to approximately 10%.

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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'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging problems in statistics to boost performance.

All of our AI Tutor roles potentially involve gathering or providing data in text, voice, and video formats, including annotations, audio recordings, or video sessions,tasks with which candidates must be comfortable.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from statistical domains that align with your expertise, focusing on areas such as probability theory, inferential statistics, regression modelling, multivariate analysis, stochastic processes, Bayesian methods, experimental design, and data-driven applications where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Statistics (or Mathematics with a specialisation in statistics or probability) or (b) a medal in an International Math Olympiad (IMO), International Statistical Olympiad, or similar competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organisational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgement even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• PhD in Statistics or a closely related quantitative field.
• Peer-reviewed publications in statistics, probability, or applied statistical modelling.
• Previous AI Tutoring experience and/or experience teaching college-level statistics courses.

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. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
• 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 be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.

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A Research Scientist at Anduril should possess an M.S. or Ph.D. in Applied or Computational Mathematics, Electrical Engineering, Computer Science, Controls and Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field. A Research Scientist should have a record of academic excellence, including demonstrated experience in most of the following areas:

• Applied Mathematics: differential equations, linear algebra, numerical analysis, and continuous or discrete optimization;
• Engineering: controls, estimation theory, digital signal processing, and machine learning;
• Scientific Computing: software design, algorithm implementation, and software analysis, testing, and optimization;
• Probability: statistics and random processes.

A Research Scientist should have effective written and verbal communication skills, with the demonstrated ability to convey salient details about advanced technology in a compelling manner to both experts and non-experts alike. Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance.

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Responsibilities: Use proprietary tools to label and evaluate data. Support and ensure the delivery of high-quality curated data. Work with engineers to refine tasks, tools, and workflows. Design, select, and refine tasks grounded in real-world occupational math, for example: Insurance and risk: premiums, deductibles, expected loss calculations, simple risk modeling. Logistics and operations: inventory and reorder policies, capacity/throughput, basic cost optimization. Skilled trades: surveying and land measurement, electrical load calculations, machining tolerances, material estimation, blueprint and scale calculations. Finance and banking: loan amortization schedules, time value of money, portfolio and risk metrics. Accounting and tax: financial statements, reconciliations, depreciation, multi-bracket tax calculations, payroll. Health and social data: rates, ratios, simple biostatistics, survey-based metrics and policy-relevant indicators. Provide detailed, step-by-step solutions and evaluate model responses for correctness, adherence to domain rules (e.g., tax codes, building codes, basic regulatory or business constraints), clarity, and plausibility. Interpret, analyze, and execute tasks based on given instructions.

Basic Qualifications: A Master's or PhD in a quantitative field such as Mathematics, Statistics, Operations Research, Economics, Finance, Actuarial Science, or a closely related discipline with strong training in applied/occupational math; or A Bachelor's degree in one of the fields above plus substantial professional experience (e.g., 2+ years) in a math-heavy occupational domain such as finance, banking, insurance, accounting, logistics/supply chain, healthcare analytics, or policy analysis Professional licensure or certification in a skilled trade (e.g., licensed surveyor, master electrician, journeyman machinist) with demonstrated expertise in trade-specific mathematical calculations. Strong proficiency in applied mathematics relevant to at least one of the above domains (e.g., probability and statistics, financial math, optimization under constraints, geometric and measurement calculations, or similar). Proficiency in reading and writing, both in informal and professional English. Strong ability to navigate various information resources and databases. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience: Professional certifications in relevant fields (e.g., CFA, FRM, SOA exams, CPA, Six Sigma, PE, licensed surveyor, or similar) or demonstrably equivalent experience. Prior professional experience in one or more domains such as asset management, retail or commercial banking, insurance pricing/reserving, accounting/audit, logistics/supply chain planning, healthcare analytics, public policy analysis, or skilled trades. Previous AI Tutoring experience and/or experience teaching or training others in applied or occupational math topics. Experience building and reviewing complex spreadsheets, financial or risk models, dashboards, technical drawings, or similar artifacts.

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You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging problems in statistics to boost performance.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from statistical domains that align with your expertise, focusing on areas such as probability theory, inferential statistics, regression modeling, multivariate analysis, stochastic processes, Bayesian methods, experimental design, and data-driven applications where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Statistics (or Mathematics with a specialization in statistics or probability) or (b) a medal in an International Math Olympiad (IMO), International Statistical Olympiad, or similar competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• PhD in Statistics or a closely related quantitative field.
• Peer-reviewed publications in statistics, probability, or applied statistical modeling.
• Previous AI Tutoring experience and/or experience teaching college-level statistics courses.

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You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging applied math problems to boost performance.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from applied math domains that align with your expertise, focusing on areas such as probability, statistics, numerical analysis, optimization, operations research, dynamical systems, data modeling, and related fields where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Mathematics with a specialization in a subdomain of applied mathematics (there is a separate position for pure math) or (b) a medal in an International Math Olympiad (IMO) or similar level math competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• Math PhD with a specialization in a subdomain of applied mathematics.
• Peer-reviewed applied math publications in well-regarded journals.
• Previous AI Tutoring experience and/or experience teaching college courses.

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. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
• 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 be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.

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In this role, you'll apply strong analytical judgment and product intuition to help us understand customer behaviour, evaluate trade-offs, and make smart investment decisions across the cards and lending lifecycles , from eligibility and activation to spend, retention, incentives, and credit performance. You'll help build a data-informed culture across Mercury so teams can move quickly, measure what matters, and invest intelligently.

Key responsibilities include:

• Bringing impeccable communication and complete ownership , independently identifying opportunities, developing strong points of view, and influencing executives, Cards & Credit leaders, and cross-functional partners through clear, concise, and persuasive storytelling.
• Developing a nuanced understanding of cardholder behaviour and economics, helping teams reason about trade-offs between growth, engagement, risk, and unit economics.
• Defining, owning, and analysing metrics that inform both tactical decisions and long-term strategy across the cards and credit lifecycle (e.g., eligibility, activation, spend, utilisation, rewards, retention, loss signals).
• Designing and evaluating experiments using rigorous statistical approaches, including A/B testing, cohort analysis, causal inference techniques, and trend analysis.
• Building and improving data pipelines and tools to streamline data collection, processing, and analysis workflows, ensuring the integrity, reliability, and security of data assets.
• Building and deploying predictive models to forecast key outcomes, inform product treatments, and deepen understanding of causal drivers.

Requirements include:

• 7+ years of experience working with large datasets to drive product or business impact in data science or analytics roles.
• Fluency in SQL and comfort with Python.
• Strong judgment in defining and analysing product metrics, running experiments, and translating ambiguous questions into structured analyses.
• Exceptional proactivity and independence , identifying opportunities, forming strong points of view, and making your case to stakeholders.
• Experience with ETL processes and modern data modelling (e.g., dbt, dimensional models, Airflow), with a solid understanding of how data is produced and consumed.
• Experience in analytical approaches ranging from behavioural modelling to experimentation to optimisation , and, importantly, know when simpler approaches are the right answer.
• Apply AI tools to accelerate analytical and business workflows, improving scalability, decision quality, and reducing manual or repetitive work across teams.

Nice to have:

• Experience working on cards or credit products, with familiarity in card economics and lifecycle concepts (e.g., spend behaviour, interchange, rewards and incentives, utilisation, credit limits, retention).
• Experience developing quantitative pricing models or engines (e.g., dynamic pricing, incentive optimisation, or marketplace pricing systems).
• Experience applying optimisation techniques to resource allocation or decision systems (e.g., customer operations, capacity planning, or policy optimisation).
• Experience building or supporting credit models, including probability of default modelling, cashflow modelling, or dynamic credit limit setting.

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Based in Mountain View, CA, Cyngn is a publicly-traded autonomous technology company. We deploy self-driving industrial vehicles like forklifts and tuggers to factories, warehouses, and other facilities throughout North America.

To build this emergent technology, we are looking for innovative, motivated, and experienced leaders to join us and move this field forward. If you like to build, tinker, and create with a team of trusted and passionate colleagues, then Cyngn is the place for you.

Key reasons to join Cyngn:

We are small and big. With under 100 employees, Cyngn operates with the energy of a startup. On the other hand, we’re publicly traded. This means our employees not only work in close-knit teams with mentorship from company leaders,they also get access to the liquidity of our publicly-traded equity.

We build today and deploy tomorrow. Our autonomous vehicles aren’t just test concepts,they’re deployed to real clients right now. That means your work will have a tangible, visible impact.

We aren’t robots. We just develop them. We’re a welcoming, diverse team of sharp thinkers and kind humans. Collaboration and trust drive our creative environment. At Cyngn, everyone’s perspective matters,and that’s what powers our innovation.

About this role:

As a Staff/Senior Software Engineer on our Calibration, Localization, & Mapping (CLAM) team, you will be responsible for delivering mission-critical improvements and new features to our calibration, localization, and mapping subsystems. You will work on a small, highly focused team developing production-quality software that enables efficient and accurate creation of HD maps at Cyngn deployment-sites and robust localization for Cyngn’s autonomous vehicle fleets.

Responsibilities

• Design, implement, tune, and test mapping, localization, and sensor calibration algorithms for our autonomous vehicle platforms using C++ and Python.

• Develop tooling and metrics for performance validation and continuous testing frameworks.

• Balance project tasks, code reviews, and research to meet product-driven milestones in a fast-paced startup environment.

Qualifications

• MS/Phd with focus in robotics or a similar technical field of study

• Solid foundation in probability theory, linear algebra, 3D geometry, and spatial coordinate transformations.

• In-depth understanding of matrix factorization algorithms and Lie algebra/groups.

• Solid theoretical knowledge of state-of-the-art techniques in 3D Lidar-based mapping and localization for autonomous vehicles (LOAM series, GICP, FastLIO, bundle-adjustment)

• Familiarity with state estimation frameworks such as EKF’s as well as modern nonlinear optimization libraries (GTSAM, G2O, Ceres-Solver, GNC-Solver, etc.)

• 6+ years of industry experience as an autonomous vehicle or robotics software engineering professional including hands-on implementation and tuning on production hardware.

• 6+ years industry experience writing C++ software in a production environment - architecture design, unit testing, code review, algorithm performance trade-offs, etc.

• Proficiency in Python.

• Excellent written & verbal communication skills.

Bonus Qualifications

• Proven record of top-tier publications or patents.

• Experience with GPU programming, CUDA.

• Experience in implementing automated map change detection and updating techniques.

• Experience implementing modern multi-sensor calibration and sensor mis-alignment detection algorithms.

• Experience with camera-based SLAM and 3D multi-view geometry.

• Experience working with ROS2 to design, build, and operate robotic systems.

• Exposure to modern software development version control and project management tools - Git, Jira, etc.

Benefits & Perks

• Health benefits (Medical, Dental, Vision, HSA and FSA (Health & Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge)

• Life, Short-term and long-term disability insurance (Cyngn funds 100% of premiums)

• Company 401(k)

• Commuter Benefits

• Flexible vacation policy

• Sabbatical leave opportunity after 5 years with the company

• Paid Parental Leave

• Daily lunches for in-office employees and fully-stocked kitchen with snacks and beverages

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We are seeking a highly skilled Data Scientist III to join our EADP Gameplay Services team. As a Data Scientist III, you will play a key role in analysing complex matchmaking datasets to identify patterns, trends, and opportunities that drive data-informed business decisions.

We Are EA

Our platform powers online features for EA’s games, serving millions of users each day. We live, breathe, and dream about how we can make every player’s multiplayer experience memorable. We develop services and SDKs in collaboration with EA’s game studios for matchmaking, stats and leaderboards, achievements, game replays, VOIP, and game networking.

Opportunity Ahead

Our primary mission is to enrich the player’s gaming experience by meticulously optimising the matchmaking process. We believe that effective matchmaking is the cornerstone of any successful multiplayer gaming experience, and we are committed to perfecting this aspect of our service. We continuously reflect and probe various elements to ensure the player’s gaming encounters are both fun and challenging

Key Responsibilities

• Analyse complex matchmaking datasets to identify patterns, trends, and opportunities that drive data-informed business decisions.
• Perform data exploration, mining, and feature engineering to create high-quality datasets for model development.
• Ensure data integrity and governance through robust validation, preprocessing, and quality assurance processes.
• Own model lifecycle including retraining, validation, performance monitoring, and scalability improvement.
• Define experimentation strategy (A/B testing, causal inference) and measure impact on core gameplay KPIs
• Partner with product, business, and engineering to identify new data acquisition opportunities.
• Create reusable analytical tools, libraries, and metrics that enable data-driven decisions.
• Collaborate with data engineers and software engineer across teams to serve their data needs.
• Evangelise data as a first-class citizen through documentation, standards, and reviews.

Must Have Skills

• Bachelor’s or master’s degree in computer science, Data Science, AI/ML, Statistics, or a related field (or equivalent professional experience)
• 5+ years of experience in data science, analytics, or ML engineering with a strong record of deploying scalable ML solutions.
• Solid understanding of statistical modelling, including probability distributions, regression analysis, and hypothesis testing.
• Strong understanding of experimentation design and A/B testing frameworks
• Expert proficiency in Python frameworks (PyTorch, Scikit-learn).
• Experience with model monitoring and drift detection
• Experience in handling large-scale and high-dimensional datasets using distributed data processing tools (Spark, Snowflake, Databricks).
• Strong communication skills with the ability to translate complex models into business impact.

Desirable Skills

• Experience in gaming analytics or player behaviour modelling
• Experience building recommendation or ranking systems
• Experience with cloud platforms (AWS/GCP/Azure)

What’s in it for you? Glad you asked!

We love to brag about our great perks like Global fitness program, Sodexo (Food Coupons), Parental Insurance & Medical, Accident & life insurance and since we realise it takes world-class people to make world-class games, we offer competitive compensation packages and a culture that thrives off creativity and individuality. At EA, we live the “work hard/play hard” credo every day.

_About Electronic Arts_

We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.

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San Francisco; New York City; Remote - US

Employment Type

Full time

Location Type

Hybrid

Department

Intelligence & Investigations

Compensation

• $198K – $220K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe achieving this goal requires real-world deployment and continuous iteration based on how our products are used—and misused—in practice.

The Intelligence and Investigations team supports this mission by detecting, investigating, and disrupting the misuse of our products, particularly critical or novel harms. Our work enables partner teams to develop data-backed model policies and build scalable safety mitigations. By precisely understanding abuse, we help ensure OpenAI’s products can be used safely to build meaningful, rewarding applications.

About the Role

As a Technical Abuse Investigator on the Intelligence and Investigations team, you will be responsible for detecting, investigating, and disrupting malicious use of OpenAI’s platform. You will further scale parts of the investigative process to help our team disrupt harm at scale. This role combines traditional investigative judgment with strong technical fluency: much of the work involves navigating complex datasets to surface actionable abuse signals, not just reviewing individual reports.

In addition to conducting investigations directly, this role is explicitly designed to act as a force multiplier for the broader investigations team. You will be scaling or automating highly manual, important and nuanced processes. You will design and implement lightweight technical solutions—such as notebook templates, data pipelines or internal utilities—that enable specialized investigators to identify, track, and action abuse at a greater scale than a single investigator can currently achieve. Success in this role is measured not only by investigations completed, but by how effectively your work enables you and your team members to operate more efficiently and consistently.

You will work closely with engineering, legal, investigations, security, and policy partners to respond to time-sensitive escalations, investigate activity that falls outside existing safeguards, and translate investigative insights into scalable detection and enforcement strategies.

This role includes participation in an on-call rotation to handle urgent escalations outside of normal work hours. Some investigations may involve sensitive content, including sexual, violent, or otherwise disturbing material. This role will work PST and is open to remote work within the United States, though we heavily prefer candidates based in San Francisco or New York.

In this role, you will:

• Detect, investigate and disrupt abuse and harm with policy, legal, global affairs, security, and engineering teams via complex datasets.

• Develop and iterate on abuse signals and investigative methods, scaling one-off insights to reduce manual effort and expand coverage.

• Build and maintain lightweight technical solutions (e.g., SQL/ Python data pipelines, investigation templates, dashboards, or internal utilities) for investigators focused on specific harm domains.

• Develop a deep understanding of OpenAI’s products, data systems, and enforcement mechanisms, and collaborate with engineering and data teams to improve investigative tooling, data quality, and workflows.

• Communicate investigation findings effectively to internal stakeholders through written briefs, data-backed recommendations, and escalation summaries

• Rotate (in-frequently) into an incident response role that requires rapid threat triaging, investigation, mitigation, sound judgement and concise briefing to senior leadership.

• Be someone people enjoy working with.

• Proven ability to quickly learn new processes, systems and team dynamics while thriving in ambiguous, rapidly changing, and high-pressure environments.

You might thrive in this role if you:

• Have a strong background in computer science, software engineering, or a related field.
• Have experience with data analysis, machine learning, or other technical skills relevant to the role.
• Are able to work effectively in a fast-paced, dynamic environment.
• Are able to communicate complex technical information to non-technical stakeholders.
• Are able to work independently and as part of a team.
• Are able to adapt to changing priorities and deadlines.
• Are able to maintain confidentiality and handle sensitive information.
• Are able to work in a remote environment.

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Product Manager, Codex

Location

San Francisco

Employment Type

Full time

Location Type

On-site

Department

Product Management

Compensation

• $255K – $325K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

With Codex we’re building an AI software engineer. One that you can pair with, delegate to, or even ask to take on future tasks proactively. Our team is a fast-moving group within OpenAI, bringing together research, engineering, design, and product. We iteratively build the Codex agent harness and product to get the most out of the model, and we iteratively train the model to be great in the Codex.

About the Role

As the product manager on Codex, you will lead the development of a highly technical product designed for a technical audience. Much of the work is 0–1, requiring you to shape product direction amid ambiguity and shape what the future of agents will look like. You’ll partner closely with world-class engineers and researchers to bring cutting-edge capabilities into the hands of developers, and you’ll shape how our AI tools support software development workflows.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Shape product strategy for Codex, from early concepts through launch and iteration.

• Collaborate with engineering and research to translate breakthroughs into usable, high-value developer experiences.

• Deeply understand developer workflows and identify opportunities where AI can make them faster, more intuitive, and more powerful.

• Navigate ambiguity and make thoughtful trade-offs in 0–1 product environments.

• Partner with cross-functional teams to deliver quickly while maintaining a high bar for technical quality and user experience.

You might thrive in this role if you:

• Bring a strong technical background and have recently shipped code to production

• Have a deep intuition for developer workflows and a passion for building tools that make coding more productive and enjoyable.

• Can define product direction in ambiguous, 0–1 environments and rally teams around it.

• Demonstrate strong product intuition, making thoughtful prioritization and sequencing decisions.

• Have experience driving execution across engineering, design, and research.

• Bring an entrepreneurial mindset and adaptability, whether from startup or high-growth company environments.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $250K – $380K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life.

About the Role

We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume.

In this role, you will:

• Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory.

• Build proactive testing and scale validation pipelines for dataset loading at GPU scale.

• Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience.

• Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt.

• Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized.

• Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training).

• Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets.

You might thrive in this role if you:

• Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.

• Have experience building APIs, modular code, and scalable abstractions, while recognizing that abstractions ultimately serve the users and UX is an important part of the abstractions design.

• Are comfortable debugging bottlenecks across large fleets of machines.

• Take pride in building infrastructure that “just works,” and find joy in being the guardian of reliability and scale.

• Are collaborative, humble, and excited to own a foundational (if not glamorous) part of the ML stack.

Bonus points if you:

• Have background knowledge in data math, probability, or distributed data theory.

• Have worked with GPU-scale distributed systems or dataset scaling for real-time data

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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