ML Research Engineer Visa Sponsorship Jobs in California
California is the top state for ML research engineer visa sponsorship, driven by a concentration of major tech employers across the San Francisco Bay Area, Silicon Valley, and Los Angeles. Companies like Google, Meta, Apple, and dozens of AI-focused startups and research labs regularly sponsor H-1B visa and O-1 visas for qualified ML research engineers.
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Get Access To All JobsINTRODUCTION
Your work days are brighter here.
We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.
ABOUT THE TEAM
Admin Central is building the future of how administrators work across Workday, turning a fragmented patchwork of tools and disconnected AI into a single, unified experience. Within Admin Central, Workday implementations move from being driven by human effort to being powered by intelligence designed into the platform. You’ll build mission-critical distributed systems, high-availability usage pipelines, new agentic functionality, and event-driven data flows across global product regions to ensure enterprise billing integrity at scale. If you're excited to build from scratch, move fast, and transform how thousands of admins work every day, come join us!
ABOUT THE ROLE
As a Sr Software Development Engineer (ML/AI) on the Admin Central team, you will lead the technical design, development, and scaling of advanced ML pipelines, predictive analytics engines, and AI-driven recommendation features. Admin Central sits at the core of Workday's enterprise AI and automation strategy, serving over 700 customer accounts to handle ad hoc and ambient agentic requests through high-throughput analytics and agentic workflows.
In this role, you will bridge the gap between production-grade distributed software engineering and modern ML/LLM architectures. You will architect low-latency inference services, build automated feature stores and retraining pipelines over big data infrastructure (Kafka, Spark/Flink, ClickHouse, S3), and extend AI observability across agent execution loops using frameworks like LangSmith and LangChain.
KEY RESPONSIBILITIES
- ML Infrastructure & Pipeline Engineering: Architect, deploy, and maintain end-to-end Machine Learning pipelines—from distributed data ingestion and feature engineering to model training, evaluation, and production deployment.
- Agentic AI & Recommendation Engines: Design algorithms and LLM-driven recommendation features (e.g., IDD insights, next-best-action models) that optimize agentic workflows and tool usage.
- Low-Latency Inference & Scaling: Optimize real-time model inference and scoring microservices to ensure sub-second response times across high-concurrency multi-tenant environments.
- LLM & Agentic Observability: Integrate telemetry and tracing (OpenTelemetry, LangChain, LangSmith) into ML pipelines to track model performance, prompt/response drift, and execution efficiency.
- Data & Feature Store Architecture: Collaborate with core backend engineers to leverage big data platforms (ClickHouse, Apache Iceberg, Spark) for high-dimensional feature retrieval and analytics.
- Cross-Functional Leadership: Partner closely with Product Managers, Data Engineering, SRE, and Legal/Compliance to translate complex business and governance requirements into scalable ML solutions.
ABOUT YOU
BASIC QUALIFICATIONS
- 8+ years in ML research, development, and implementation of advanced models/techniques, including 4+ years building, deploying, and operating production ML systems at scale.
- 5+ years in deep learning, NLP, and GenAI/LLM orchestration using frameworks like PyTorch, TensorFlow, Scikit-learn, LangChain, and LlamaIndex, plus proficiency in Java, Go, Scala, or C++ for high-performance backend systems.
OTHER QUALIFICATIONS
- Data Processing & Pipelines: Strong ability in distributed processing (Spark, Flink, Kafka) and high-throughput columnar/vector storage (ClickHouse, Pinecone, Milvus) to design robust ML data pipelines.
- AI/ML Expertise: Solid knowledge of RAG architectures, LLM fine-tuning, intent classification, and recommendation engines — applying ML algorithms and Model-Based Design (including MCP tooling and structured agentic execution paths) to multi-agent orchestration, contextual reasoning, and workflow optimization.
- Data Analysis & Feature Engineering: Experience leading EDA on multi-tenant execution logs to validate prompt/response accuracy and optimize tool usage, paired with strong feature engineering skills for vector embeddings, feature stores, and multi-tenant data isolation.
- Model Lifecycle: Experience leading model building (foundation model adaptation, prompt engineering, fine-tuning, low-latency inference) and deep understanding of the model development lifecycle, including MLOps platforms (Kubeflow, MLflow, Airflow, SageMaker) for monitoring, latency tracking, and retraining at scale.
- Technical Stack: Strong proficiency in Python and ML libraries (PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, LangChain, LangSmith, DSPy), with experience deploying scalable ML systems in cloud-native production using Docker, Kubernetes, gRPC/REST APIs, and CI/CD under strict high-availability (99.9% uptime) and low-latency SLAs.
- Team Collaboration: Strong ability to mentor team members, drive cross-functional technical alignment, draft system design specs/model cards, and communicate technical and governance decisions.
- Education: Bachelor's in Computer Science, Data Science, Machine Learning, Applied Mathematics, Statistics, or Engineering; Master's or PhD strongly preferred.
COMPENSATION
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things.
- Primary Location: USA.CA.Pleasanton
- Primary Location Base Pay Range: $192,000 USD - $288,000 USD
- Additional US Location(s) Base Pay Range: $163,000 USD - $288,000 USD
OUR APPROACH TO FLEXIBLE WORK
With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.
Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.
If you require a reasonable accommodation, you may email accommodations@workday.com, as far in advance as possible.
ARE YOU BEING REFERRED TO ONE OF OUR ROLES?
If so, ask your connection at Workday about our Employee Referral process!
At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.
Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.
In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.
INTRODUCTION
Your work days are brighter here.
We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.
ABOUT THE TEAM
Admin Central is building the future of how administrators work across Workday, turning a fragmented patchwork of tools and disconnected AI into a single, unified experience. Within Admin Central, Workday implementations move from being driven by human effort to being powered by intelligence designed into the platform. You’ll build mission-critical distributed systems, high-availability usage pipelines, new agentic functionality, and event-driven data flows across global product regions to ensure enterprise billing integrity at scale. If you're excited to build from scratch, move fast, and transform how thousands of admins work every day, come join us!
ABOUT THE ROLE
As a Sr Software Development Engineer (ML/AI) on the Admin Central team, you will lead the technical design, development, and scaling of advanced ML pipelines, predictive analytics engines, and AI-driven recommendation features. Admin Central sits at the core of Workday's enterprise AI and automation strategy, serving over 700 customer accounts to handle ad hoc and ambient agentic requests through high-throughput analytics and agentic workflows.
In this role, you will bridge the gap between production-grade distributed software engineering and modern ML/LLM architectures. You will architect low-latency inference services, build automated feature stores and retraining pipelines over big data infrastructure (Kafka, Spark/Flink, ClickHouse, S3), and extend AI observability across agent execution loops using frameworks like LangSmith and LangChain.
KEY RESPONSIBILITIES
- ML Infrastructure & Pipeline Engineering: Architect, deploy, and maintain end-to-end Machine Learning pipelines—from distributed data ingestion and feature engineering to model training, evaluation, and production deployment.
- Agentic AI & Recommendation Engines: Design algorithms and LLM-driven recommendation features (e.g., IDD insights, next-best-action models) that optimize agentic workflows and tool usage.
- Low-Latency Inference & Scaling: Optimize real-time model inference and scoring microservices to ensure sub-second response times across high-concurrency multi-tenant environments.
- LLM & Agentic Observability: Integrate telemetry and tracing (OpenTelemetry, LangChain, LangSmith) into ML pipelines to track model performance, prompt/response drift, and execution efficiency.
- Data & Feature Store Architecture: Collaborate with core backend engineers to leverage big data platforms (ClickHouse, Apache Iceberg, Spark) for high-dimensional feature retrieval and analytics.
- Cross-Functional Leadership: Partner closely with Product Managers, Data Engineering, SRE, and Legal/Compliance to translate complex business and governance requirements into scalable ML solutions.
ABOUT YOU
BASIC QUALIFICATIONS
- 8+ years in ML research, development, and implementation of advanced models/techniques, including 4+ years building, deploying, and operating production ML systems at scale.
- 5+ years in deep learning, NLP, and GenAI/LLM orchestration using frameworks like PyTorch, TensorFlow, Scikit-learn, LangChain, and LlamaIndex, plus proficiency in Java, Go, Scala, or C++ for high-performance backend systems.
OTHER QUALIFICATIONS
- Data Processing & Pipelines: Strong ability in distributed processing (Spark, Flink, Kafka) and high-throughput columnar/vector storage (ClickHouse, Pinecone, Milvus) to design robust ML data pipelines.
- AI/ML Expertise: Solid knowledge of RAG architectures, LLM fine-tuning, intent classification, and recommendation engines — applying ML algorithms and Model-Based Design (including MCP tooling and structured agentic execution paths) to multi-agent orchestration, contextual reasoning, and workflow optimization.
- Data Analysis & Feature Engineering: Experience leading EDA on multi-tenant execution logs to validate prompt/response accuracy and optimize tool usage, paired with strong feature engineering skills for vector embeddings, feature stores, and multi-tenant data isolation.
- Model Lifecycle: Experience leading model building (foundation model adaptation, prompt engineering, fine-tuning, low-latency inference) and deep understanding of the model development lifecycle, including MLOps platforms (Kubeflow, MLflow, Airflow, SageMaker) for monitoring, latency tracking, and retraining at scale.
- Technical Stack: Strong proficiency in Python and ML libraries (PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, LangChain, LangSmith, DSPy), with experience deploying scalable ML systems in cloud-native production using Docker, Kubernetes, gRPC/REST APIs, and CI/CD under strict high-availability (99.9% uptime) and low-latency SLAs.
- Team Collaboration: Strong ability to mentor team members, drive cross-functional technical alignment, draft system design specs/model cards, and communicate technical and governance decisions.
- Education: Bachelor's in Computer Science, Data Science, Machine Learning, Applied Mathematics, Statistics, or Engineering; Master's or PhD strongly preferred.
COMPENSATION
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things.
- Primary Location: USA.CA.Pleasanton
- Primary Location Base Pay Range: $192,000 USD - $288,000 USD
- Additional US Location(s) Base Pay Range: $163,000 USD - $288,000 USD
OUR APPROACH TO FLEXIBLE WORK
With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.
Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.
If you require a reasonable accommodation, you may email accommodations@workday.com, as far in advance as possible.
ARE YOU BEING REFERRED TO ONE OF OUR ROLES?
If so, ask your connection at Workday about our Employee Referral process!
At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.
Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.
In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.
ML Research Engineer Job Roles in California
See all 3,919+ ML Research Engineer Jobs in California
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Search ML Research Engineer Jobs in CaliforniaML Research Engineer Jobs in California: Frequently Asked Questions
Which companies sponsor visas for ML research engineers in California?
California's largest ML research engineer sponsors include Google DeepMind, Meta AI, Apple, Microsoft, Amazon, and NVIDIA, all with significant California research presence. Beyond big tech, AI-focused companies like Anthropic, OpenAI, and Waymo also file H-1B petitions for ML research roles. DOL H-1B disclosure data consistently shows California employers among the highest-volume sponsors for machine learning and AI research positions nationally.
Which visa types are most common for ML research engineer roles in California?
The H-1B is the most common visa for ML research engineers in California, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, machine learning, or a related field. The O-1A is another pathway for researchers with published work, conference recognition, or industry awards. International students completing master's or PhD programs in California may also work under OPT or STEM OPT before transitioning to employer-sponsored status.
Which cities in California have the most ML research engineer sponsorship jobs?
The San Francisco Bay Area, including San Jose, Mountain View, Menlo Park, and San Francisco itself, accounts for the largest share of ML research engineer sponsorship activity in California. Los Angeles has grown significantly, driven by research labs, entertainment technology companies, and university-affiliated AI programs. San Diego also has a meaningful cluster, particularly in biotech-adjacent machine learning and defense research.
How to find ml research engineer visa sponsorship jobs in California?
Migrate Mate is built specifically for international job seekers and filters ML research engineer roles in California by visa sponsorship availability, saving you from manually vetting employer histories. Because ML research positions often require deep specialization, filtering by specific subfields like NLP, computer vision, or reinforcement learning helps narrow results. Migrate Mate surfaces employers with active sponsorship records, which is particularly useful in California where both large tech firms and early-stage AI startups are actively hiring.
Are there any California-specific considerations for ML research engineers seeking visa sponsorship?
California's prevailing wage requirements under DOL rules apply to H-1B petitions filed for positions in the state, and wages for ML research engineers in major California metros are among the highest Level I and Level II benchmarks in the country. Many candidates entering this field have come through PhD programs at UC Berkeley, Stanford, UCLA, or UC San Diego, which have established pipelines into sponsored research roles. California also has a dense network of university-affiliated research labs where sponsored postdoctoral or staff researcher roles are common entry points.
What is the prevailing wage for sponsored ml research engineer jobs in California?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.