We are looking for an experienced engineer with 8+ years of experience in ML infrastructure, including model training and model deployments. You should have hands-on experience with ML optimization, cloud-based technologies, MLOps tools, and proficiency with common programming languages and frameworks of ML. Strong focus on scalability, reliability, performance, and ease of use is essential.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.

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Design & own evaluation/optimization frameworks for frontier music models. Dive deep under the hood of our music generation systems, applying computational & human resources to understand model capabilities and identify areas for growth. Build optimization loops and apply your findings to our pretraining, post-training and inference systems as applicable.

Drive product & research roadmap. Own our data roadmap end-to-end, formulating research questions, exploring/linking/expanding data sources and conducting experiments at your discretion. Your work will span data mining, machine learning, causal inference, survey design and more, and your results will be critical for decision-making in product development, research investment and overall business direction.

Build stable infrastructure. Your work will reach far beyond the jupyter kernel, manifesting in robust integrations with our research & product tech stacks, potentially in performance-critical paths. You'll also build large-scale standalone data processing systems, allocating resources as needed to manage the data ecosystem.

Champion scientific rigor. As our first quantitative researcher, you'll cultivate a culture of scientific rigor across the company and deepen common understanding of models, users and data. You'll proactively identify opportunities, define metrics, share results, and build a rigorous foundation upon which to understand our highly subjective domain.

We're looking for someone with deep quantitative expertise, preferably a Ph.D. in statistics, mathematics, physics, or another quantitative discipline, or 5+ years' industry experience as a quantitative analyst / data scientist. Autonomy & ownership are key, as you'll thrive in greenfield research domains, undefined product categories and small, flat teams. Engineering chops are also important, as you'll need to translate your ideas into clear, production-ready code and collaborate in an active research codebase.

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Our Minesweeper squad produces Human Understandable Language Knowledge to enrich music and talk content understanding. We use AI and ML techniques, including Large Language Models, to understand music, podcasts and audiobooks, building reliable, scalable systems to distribute that knowledge to Spotify internal teams, users, and creators.

We are looking for a Machine Learning Engineer to join our team and help build the future of music, podcast and audiobook listening experiences for millions of listeners at Spotify. This is a unique opportunity to help develop and shape Spotify content enrichment, and recommendations.

As a Machine Learning Engineer, you will:

• Utilize in-house and 3rd party LLMs to solve language understanding problems
• Employ techniques such as fine-tuning and RAG to improve models
• Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
• Help drive optimization, testing, and tooling to improve quality of our content enrichment assets
• Collaborate with cross-functional teams of MLEs, data and backend engineers, and other stakeholders including tech research, data science, and product to develop new features and technologies
• Perform data analysis to establish baselines and inform product decisions
• Stay up-to-date on the latest machine learning algorithms and techniques

You will be part of a motivated and supportive team that values agile software processes, data-driven development, reliability, and disciplined experimentation.

If you have a strong background in machine learning, especially experience with Large Language Models, and are passionate about fostering collaborative teams, we encourage you to apply.

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The TurnTable team’s mission is to own and innovate on AI DJ and the interactive listening experiences. Using a mixture of LLMs and traditional ML, we strive to provide depth and connection for all listeners. We are looking for a Machine Learning Engineer to join our team to build and improve our interactive listening experiences.

Responsibilities

• Design, build, evaluate, and ship an agent-based DJ solution that brings our DJ and interactive experiences to the next level.
• Collaborate with cross-functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways.
• Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users.
• Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
• Be part of an active group of machine learning practitioners.

Requirements

• An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment.
• Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications.
• Hands-on expertise with implementing end-to-end production ML systems at scale. Experience with production LLM scale-based systems is a plus.
• Experience with incorporating human feedback to improve LLM-based systems using techniques like DPO, KTO, and reinforcement fine-tuning.
• Experience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams.
• Experience with large-scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS.

Benefits

• Health insurance
• Six-month paid parental leave
• 401(k) retirement plan
• Monthly meal allowance
• 23 paid days off
• 13 paid flexible holidays
• Paid sick leave

The United States base range for this position is $176,166 - $251,666 plus equity.

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Are you ready to contribute to the evolution of our data pipelines for our B2C division? At Future, we are transforming our data-driven decision-making processes and we are looking for a passionate and experienced Data Engineer to join us.

This is an exciting opportunity for someone who excels in a creative environment, enjoys solving complex data challenges, and is eager to build impactful business insights, for this role you will directly report into the Head of Data Engineering

Responsibilities

• Develop and maintain new/current features of the data platform.
• Responsible for delivery of development projects, including scoping, writing and sizing of stories involved.
• Take ownership of BAU processes, develop area specific domain mastery, and seek means to automate them or reduce their impact.
• Proposes and advocates for changes to reduce risk, cost and overhead.
• Provide appropriate documentation for pipelines developed
• Parameterise pipelines so configuration can be changed easily without having to perform deep changes to the codebase
• Apply appropriate testing principles to ensure code is fit for purpose

Experience

• Experience using Python on Google Cloud Platform for Big Data projects, BigQuery, DataFlow (Apache Beam), Cloud Run Functions, Cloud Run, Cloud Workflows, Cloud Composure
• SQL development skills
• Experience using Dataform or dbt
• Demonstrated strength in data modelling, ETL development, and data warehousing
• Knowledge of data management fundamentals and data storage principles
• Familiarity with statistical models or data mining algorithms and practical experience applying these to business problems

What's in it for you

The expected range for this role is £50,000 - £60,000

This is a Hybrid role from our Bath Office, working three days from the office, two from home … Plus more great perks, which include;

• Uncapped leave, because we trust you to manage your workload and time
• When we hit our targets, enjoy a share of our profits with a bonus
• Refer a friend and get rewarded when they join Future
• Wellbeing support with access to our Colleague Assistant Programmes
• Opportunity to purchase shares in Future, with our Share Incentive Plan

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Are you ready to contribute to the evolution of our data pipelines for our B2C division? We are transforming our data-driven decision-making processes and we are looking for a passionate and experienced Data Engineer to join us. This is an exciting opportunity for someone who grows in a creative environment, enjoys solving complex data challenges. You'll report into the Lead Data Engineer for this position and sit within the wider Data Engineer team.

The Data & Business Intelligence team guides our organisation to become more data-driven. Our to market changes gives us a competitive edge. By ensuring visibility of objective performance data, we empower our teams to make rapid, informed decisions that enhance overall performance.

Responsibilities

• Maintain new/current features of the data platform.
• Responsible for delivery of development projects.
• Utilise established software engineering practices and principles.
• Take ownership of BAU processes, develop area specific domain mastery.
• Ensure compliance matters are followed.
• Utilise CI/CD and infrastructure as code (Terraform) for rapid deployment of changes.

Experience

• Experience using Python on Google Cloud Platform for Big Data projects, BigQuery, DataFlow (Apache Beam), Cloud Run Functions, Cloud Run, Cloud Workflows, Cloud Composure.
• SQL development skills.
• Demonstrated strength in data modelling, ETL development, and data warehousing.
• Knowledge of data management fundamentals and data storage principles.
• Familiarity with statistical models or data mining algorithms and practical experience applying these to business problems.

What's in it for you

The expected range for this role is £45,000 - £50,000. This is a Hybrid role from our Bath Office, working three days from the office, two from home. Plus more great perks, which include:

• Uncapped leave, because we trust you to manage your workload and time.
• When we hit our targets, enjoy a share of our profits with a bonus.
• Refer a friend and get rewarded when they join Future.
• Wellbeing support with access to our Colleague Assistant Programmes.
• Opportunity to purchase shares in Future, with our Share Incentive Plan.

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Responsibilities

Provide Engineering Leadership

• Provide engineering leadership to multiple product lines within FCSD
• Help business partners understand our iterative development approach and focus on delivering a Minimum Viable Product (MVP) and releases
• Design and deliver industry-leading products and services to maximize value and productivity for commercial customers

Ensure Software Engineering Excellence

• Ensure software engineering excellence (e.g. best practices and quality) is achieved within the FCSD Tech product line
• Collaborate with other Product Line Anchors to reduce complexity across the portfolio, enhance interoperability between services, and build reusable API services

Provide Thought Leadership

• Provide thought leadership for the development, structure, technology, and tools used within FCSD
• Innovate and operate with an iterative, agile, and user-centric perspective

Communicate Technology Strategy

• Clearly communicate technology strategy and vision to team members and internal and external stakeholders
• Demonstrate software engineering excellence through actively coding, pairing, and performing code and architecture reviews with the software engineers within the FCSD Tech product line

Qualifications

• Bachelor's degree in Computer Science or Engineering or related
• 5+ years experience with progressive leadership responsibilities in Software Engineering, Architecture, and Agile Framework
• Experience with Lean methodology & eXtreme Programming
• Must be able to operationalize and assist teams with abstract technology concepts
• Strong communication, collaborative, and influencing skills
• Proven ability to work closely with senior leadership
• Strong personal presence and capabilities to resolve technical concerns
• Demonstrated ability to drive development of highly technical technology services and capabilities
• Demonstrated understanding and ability to drive API economy and solutions
• Demonstrated understanding and ability to drive highly available consumer-ready Internet properties and technical platforms
• Experience collaborating with engineers, designers, and product owners
• Excellent communication skills with the ability to adapt your communication style to the audience
• Ability to work collaboratively and navigate complex decision making in a rapidly changing environment
• Strong leadership and communication skills and the ability to teach others
• Experience 3+ years with building and supporting cloud-native applications leveraging Java, Spring Boot, and REACT tech stack
• Experience with cloud services and platform knowledge
• Modern databases (Relational and non-relational)
• Continuous integration/continuous delivery tools and pipelines, such as Tekton, Jenkins, Terraform, SonarQube, Maven, Gradle, Harness, Apigee X, etc.
• Experience developing and deploying to cloud platforms, such as Google Cloud Platform, Pivotal Cloud Foundry, Amazon Web Services, and Microsoft Azure
• Experience with GCP Dataflow (Apache Beam) and workflow orchestration

Benefits

• Immediate medical, dental, vision, and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care, and more
• Family building benefits, including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year's Day
• Paid time off and the option to purchase additional vacation time

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Helpshift helps B2B brands deliver this modern customer service experience through a mobile-first approach. We have changed how conversations take place, moving the conversation away from a slow, outdated email and desktop experience to an in-app chat experience that allows users to interact with brands in their own time.

Through our market-leading AI-powered chatbots and automation, we help brands deliver instant and rapid resolutions. Because agents play a key role in delivering help, our platform gives agents superpowers with automation and AI that simply works.

About the Team

Consumers care first and foremost about having their time valued by brands. Brands need insights into their customer service operation to serve their consumers effectively. Such insights and analytics are delivered through various data products like in-app analytics dashboards and data-sharing integrations.

The data platform team is responsible for designing, building, and maintaining the data infrastructure that enables such data and analytics products at scale. We build and manage data pipelines, databases, and other data structures to ensure that the data is reliable, accurate, and easily accessible.

We also enable internal stakeholders with business intelligence and machine learning teams with data ops. This team manages the platform that handles 2 Million events per minute and processes 1+ terabytes of data daily.

About the Role

• Building maintainable data pipelines both for data ingestion and operational analytics for data collected from 2 billion devices and 900M Monthly active users
• Building customer-facing analytics products that deliver actionable insights and data, easily detect anomalies
• Collaborating with data stakeholders to see what their data needs are and being a part of the analysis process
• Write design specifications, test, deployment, and scaling plans for the data pipelines
• Mentor people in the team & organization

Requirements

• 3+ years of experience in building and running data pipelines that scale for TBs of data
• Proficiency in high-level object-oriented programming language (Python or Java) is must
• Experience in Cloud data platforms like Snowflake and AWS, EMR/Athena is a must
• Experience in building modern data lakehouse architectures using Snowflake and columnar formats like Apache Iceberg/Hudi, Parquet, etc
• Proficiency in Data modeling, SQL query profiling, and data warehousing skills is a must
• Experience in distributed data processing engines like Apache Spark, Apache Flink, Datalfow/Apache Beam, etc
• Knowledge of workflow orchestrators like Airflow, Dasgter, etc is a plus
• Data visualization skills are a plus (PowerBI, Metabase, Tableau, Hex, Sigma, etc)
• Excellent verbal and written communication skills
• Bachelor’s Degree in Computer Science (or equivalent)

Benefits

• Hybrid setup
• Worker's insurance
• Paid Time Offs
• Other employee benefits to be discussed by our Talent Acquisition team in India.

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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.

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Researcher, Pretraining Safety

Location

San Francisco

Employment Type

Full time

Department

Safety Systems

Compensation

• $295K – $445K • 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 Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.

The Pretraining Safety team’s goal is to build safer, more capable base models and enable earlier, more reliable safety evaluation during training. We aim to:

1. Develop upstream safety evaluations that to monitor how and when unsafe behaviors and goals emerge;

1. Create safer priors through targeted pretraining and mid-training interventions that make downstream alignment more effective and efficient

1. Design safe-by-design architectures that allow for more controllability of model capabilities

In addition, we will conduct the foundational research necessary for understanding how behaviors emerge, generalize, and can be reliably measured throughout training.

About the Role

The Pretraining Safety team is pioneering how safety is built into models before they reach post-training and deployment. In this role, you will work throughout the full stack of model development with a focus on pre-training:

• Identify safety-relevant behaviors as they first emerge in base models

• Evaluate and reduce risk without waiting for full-scale training runs

• Design architectures and training setups that make safer behavior the default

• Strengthen models by incorporating richer, earlier safety signals

We collaborate across OpenAI’s safety ecosystem—from Safety Systems to Training—to ensure that safety foundations are robust, scalable, and grounded in real-world risks.

In this role, you will:

• Develop new techniques to predict, measure, and evaluate unsafe behavior in early-stage models

• Design data curation strategies that improve pretraining priors and reduce downstream risk

• Explore safe-by-design architectures and training configurations that improve controllability

• Introduce novel safety-oriented loss functions, metrics, and evals into the pretraining stack

• Work closely with cross-functional safety teams to unify pre- and post-training risk reduction

You might thrive in this role if you:

• Have experience developing or scaling pretraining architectures (LLMs, diffusion models, multimodal models, etc.)

• Are comfortable working with training infrastructure, data pipelines, and evaluation frameworks (e.g., Python, PyTorch/JAX, Apache Beam)

• Enjoy hands-on research — designing, implementing, and iterating on experiments

• Enjoy collaborating with diverse technical and cross-functional partners (e.g., policy, legal, training)

• Are data-driven with strong statistical reasoning and rigor in experimental design

• Value building clean, scalable research workflows and streamlining processes for yourself and others

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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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

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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

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