Machine Learning Engineer, Distributed Data Systems Job at OpenAI (San Francisco)

Machine Learning Data Engineer - Systems & Retrieval

As a Machine Learning Data Engineer - Systems & Retrieval, you will build and op...

Location

United States , Palo Alto

Salary:

Not provided

Zyphra

Expiration Date

Until further notice

Requirements

Strong software engineering background with fluency in Python
Experience designing, building, and maintaining data pipelines in production environments
Deep understanding of data structures, storage formats, and distributed data systems
Familiarity with indexing and retrieval techniques for large-scale document corpora
Understanding of database systems (SQL and NoSQL), their internals, and performance characteristics
Strong attention to security, access controls, and compliance best practices (e.g., GDPR, SOC2)
Excellent debugging, observability, and logging practices to support reliability at scale
Strong communication skills and experience collaborating across ML, infra, and product teams

Job Responsibility

Design and implementation of distributed data ingestion and transformation pipelines
Building retrieval and indexing systems that support RAG and other LLM-based methods
Mining and organizing large unstructured datasets, both in research and production environments
Collaborating with ML engineers, systems engineers, and DevOps to scale pipelines and observability
Ensuring compliance and access control in data handling, with security and auditability in mind

What we offer

Comprehensive medical, dental, vision, and FSA plans
Competitive compensation and 401(k)
Relocation and immigration support on a case-by-case basis
On-site meals prepared by a dedicated culinary team
Thursday Happy Hours

Fulltime

Software Engineer, Distributed Data Systems

The Sora team is pioneering multimodal capabilities for OpenAI’s foundation mode...

Location

United States , San Francisco

Salary:

230000.00 - 385000.00 USD / Year

OpenAI

Expiration Date

Until further notice

Requirements

Strong experience with distributed systems and large-scale infrastructure
Detail-oriented with rigor in building and maintaining reliable systems
Excellent software engineering fundamentals and organizational skills
Comfortable with ambiguity and rapid change
Strong interest in data

Job Responsibility

Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security
Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient
Partner with researchers to deeply understand requirements and translate them into production-ready systems
Harden, optimize, and maintain critical data infrastructure systems that power multimodal training and evaluation

What we offer

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

Fulltime

Research Engineer - Machine Learning and Systems

We are hiring a principal level Research Engineer with deep strength in machine ...

Location

United States , New York City

Salary:

100000.00 - 250000.00 USD / Year

Helpcare AI

Expiration Date

Until further notice

Requirements

PhD in Computer Science, Machine Learning, Computer Graphics, Computer Vision, or related field, or equivalent research track record
Seven or more years of experience in applied ML or research engineering including significant time in fast paced or startup settings
Strong publication record in top venues such as NeurIPS, ICLR, ICML, CVPR, ECCV, ICCV, SIGGRAPH, or TOG with multiple first author papers or equivalent impactful artifacts
Proven experience training and serving large models at scale including multi GPU or multi node training, distributed data loading, mixed precision, and memory optimization
Fluency in Python and C++ and experience writing efficient CUDA or Triton kernels
Expertise with PyTorch or JAX and modern tooling for experiment tracking, evaluation, and deployment
Demonstrated ability to take ideas from paper to production with measurable impact on users or business outcomes
Strong systems skills including profiling, performance tuning, reliability engineering, and cost awareness
Excellent communication with the ability to work across research and product teams

Job Responsibility

Research, design, and implement models and systems across vision, generative modeling, simulation, rendering, and 3D perception
Build data, training, evaluation, and deployment pipelines with strong observability and reproducibility
Translate research insights into reliable production services that meet product and latency requirements
Contribute hands on across prototyping, optimization, integration, and scaling
Survey new methods and run grounded evaluations to identify what to adopt and when
Share expertise through design reviews, mentoring, and documentation

What we offer

Relocation support available

Fulltime

Manager, Data & Machine Learning Platform Engineer

This Los Angeles-based role is a hands-on opportunity for a Manager, Data & Mach...

Location

United States , Inglewood

Salary:

180000.00 - 200000.00 USD / Year

Robert Half

Expiration Date

Until further notice

Requirements

4+ years of experience in data engineering, machine learning engineering, or MLOps
Proven track record of building end-to-end data and ML systems in production environments
Strong proficiency in Python and SQL
Experience with cloud platforms (Azure, AWS, or GCP) and distributed systems
Expertise in building and maintaining data pipelines (batch and streaming)
Experience deploying ML models into production, including real-time inference systems
Hands-on experience with CI/CD pipelines for ML workflows and containerization tools (e.g., Docker, Kubernetes)
Strong background in designing scalable data models and working with large-scale datasets

Job Responsibility

Design, build, and maintain scalable data pipelines and ML platform infrastructure for analytics and AI use cases
Own the end-to-end lifecycle of data and ML systems, including ingestion, transformation, feature engineering, deployment, and monitoring
Develop and optimize data models and schemas to support both batch and real-time workflows
Build and manage feature pipelines and enable low-latency access for real-time decisioning systems
Deploy machine learning models into production via APIs and real-time inference services
Implement CI/CD pipelines for machine learning workflows, including testing, versioning, and automated deployment
Establish monitoring systems to track data quality, model performance, and system reliability
Enable experimentation frameworks such as A/B testing to support data-driven product iteration
Collaborate cross-functionally with data scientists, product teams, and business stakeholders to deliver impactful AI solutions
Drive architectural decisions and promote best practices in data engineering and MLOps

What we offer

Comprehensive benefits package including medical, dental, and vision coverage
401(k) with company contribution
Annual wellbeing allowance
Flexible paid time off and parental leave
Company-paid life and disability insurance
Mental health and wellness support programs
Flexible spending accounts and family planning assistance

Fulltime

Senior Machine Learning Engineer (Research Scientist) - Data Foundation & AI

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , New York

Salary:

228960.00 - 315360.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

Strong applied ML research skills with production delivery experience
Depth in Transformers/LLMs, representation learning, or large-scale model training
Demonstrated ability to ship models to production (not just prototype)
Distributed training experience and strong Python + software engineering fundamentals
Fintech / financial data domain experience is a plus
External publications or open-source contributions is a plus

Job Responsibility

Building a foundation model on one of the world’s richest financial datasets that no one else has
Doing research that ships: moving from experimentation and prototypes to production systems serving real customers
Working across the full ML stack, from pretraining objectives and architectures to serving infrastructure and monitoring
Collaborating with a high-caliber team and seeing your work amplify the capabilities of multiple product teams
Helping hundreds of millions of consumers achieve greater financial freedom through data-driven products

Fulltime

Software Dev Engineer Machine Learning

Do you want to solve real customer problems through innovative technology? Do yo...

Location

Spain , Madrid

Salary:

Not provided

Amazon

Expiration Date

Until further notice

Requirements

Experience with video and image processing and compression algorithms and standards, computer vision and/or machine learning
Experience working with or having knowledge of cloud computing and existing cloud technologies
Experience with programming languages such as Python, Java, C++
Education Requirements (must meet one): - Currently enrolled in Bachelor's degree or above in Computer Science, Computer Engineering, Data Science, Information Systems, or related STEM fields - Completed Bachelor's or Graduate degree in specified fields
Expected graduation between October 2025 - September 2026, OR graduated within the last 24 months
Demonstrated experience one or more of the following: Data structures implementation, Basic algorithm development, Object-oriented design principles

Job Responsibility

Collaborate and communicate effectively with experienced cross-disciplinary Amazonians to design, build, and operate innovative products and services that delight our customers, while participating in technical discussions to drive solutions forward
Design and develop scalable solutions using cloud-native architectures and microservices in a large distributed computing environment
Participate in code reviews and contribute to technical documentation
Build and maintain resilient distributed systems that are scalable, fault-tolerant, and cost-effective
Leverage and contribute to the development of GenAI and AI-powered tools to enhance development productivity while staying current with emerging technologies
Write clean, maintainable code following best practices and design patterns
Work in an agile environment practicing CI/CD principles while participating in operational responsibilities including on-call duties
Demonstrate operational excellence through monitoring, troubleshooting, and resolving production issues

Senior Machine Learning Engineer, AI Platform

Location

United States; Canada

Salary:

128000.00 - 171000.00 CAD / Year

Mozilla

Expiration Date

Until further notice

Requirements

Bachelor’s degree with 4–6 years of relevant industry experience, or Master’s degree with significant hands-on experience building and operating production ML systems, or work experience equivalent
Strong experience developing in Python for machine learning systems, backend services, or distributed data processing
Proven experience deploying and operating ML workloads in cloud environments, including production-grade infrastructure
Solid understanding of model serving architectures, inference pipelines, and performance tradeoffs (latency, throughput, cost, scaling strategies)
Hands-on experience working with GPU-based workloads and accelerated computing in production settings
Experience designing CI/CD pipelines and development workflows that support reliable ML system deployment
Ability to independently scope and drive technical initiatives while balancing product and operational priorities
Strong problem-solving skills and the ability to debug performance and reliability issues in distributed systems
Clear and effective communication skills, with experience collaborating across engineering, product, and infrastructure teams

Job Responsibility

Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments
Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence
Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads
Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization
Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation
Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines
Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features
Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing
Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews

What we offer

Generous performance-based bonus plans to all eligible employees
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting (regardless of whether you contribute)
Quarterly all-company wellness days where everyone takes a pause together
Country specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program

Fulltime

Sr. Lead Machine Learning Engineer

As a Capital OneMachine Learning Engineer (MLE), you'll be part of an Agile team...

Location

United States , New York, New York; San Francisco, California; San Jose, California; Cambridge, Massachusetts; McLean, Virginia

Salary:

229900.00 - 286200.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor's Degree
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 3 years of experience building, scaling, and optimizing ML systems
At least 2 years of experience leading teams developing ML solutions

Job Responsibility

Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications
Retrain, maintain, and monitor models in production
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI
Use programming languages like Python, Scala, or Java

What we offer

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
health, financial and other benefits

Fulltime

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Machine Learning Engineer, Distributed Data Systems

Job Description

Job Responsibility

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