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Machine Learning Research Engineer Jobs in California

This role sits at the intersection of ambitious research and rigorous engineering: you will explore ... Collaborate with neuroscientists and machine learning engineers to build scalable, end-to-end ...

Research Engineer

San Francisco, CA · On-site

$120 - $150/hr

About the role As a Research Engineer, you will be responsible for post-training models for ... You have academic and/or industry experience with reinforcement learning or machine learning ...

Come join the team that turned cutting edge Generative AI research into compelling user experiences ... Description We are seeking a machine learning research engineer with experience building modern ...

Research Engineer

San Francisco, CA · On-site

$120K - $200K/yr

We are actively seeking a Research Engineer specializing in Machine Learning and AI to play a pivotal role in pioneering advanced solutions. In this role, you will lead end-to-end research projects ...

Research Engineer

San Francisco, CA · On-site

$120K - $200K/yr

We are actively seeking a Research Engineer specializing in Machine Learning and AI to play a pivotal role in pioneering advanced solutions. In this role, you will lead end-to-end research projects ...

Showing results 41-60

Machine Learning Research Engineer information

See California salary details

$36.5K

$104.6K

$140.6K

How much do machine learning research engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning research engineer in California is $104,624.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,600.00 and $102,600.00 per year, depending on experience, location, and employer.

What does a machine learning research engineer do?

A Machine Learning Research Engineer develops and improves machine learning models, conducts research to advance AI techniques, and implements scalable algorithms. They work at the intersection of applied research and engineering, leveraging mathematical and statistical methods to optimize performance. Their role involves experimenting with new architectures, analyzing large datasets, and collaborating with data scientists and software engineers to deploy models into production.

What are the key skills and qualifications needed to thrive as a machine learning research engineer?

A Machine Learning Research Engineer typically needs a strong background in computer science, mathematics, and statistics, often with a graduate degree in a related field. Proficiency in programming languages such as Python or C++, experience with machine learning frameworks like TensorFlow or PyTorch, and familiarity with tools for data analysis are crucial, along with relevant certifications being a plus. Strong problem-solving skills, collaboration, and effective communication help drive innovative research and facilitate teamwork. These competencies are essential for developing advanced machine learning models, staying current with evolving technologies, and effectively translating research into real-world applications.

What are some common challenges faced by machine learning research engineers in their daily work?

Machine Learning Research Engineers often encounter challenges such as sourcing and preparing large, high-quality datasets, tuning complex model architectures, and ensuring reproducibility of experimental results. They work closely with cross-functional teams, including data scientists and software engineers, to deploy models in production environments and must frequently adapt to rapidly evolving research. Keeping up with the latest scientific literature and integrating new algorithms into ongoing projects can be demanding but is also rewarding. This collaborative, fast-paced environment provides constant opportunities for learning and professional development.

What job categories do people searching Machine Learning Research Engineer jobs in California look for?

The top searched job categories for Machine Learning Research Engineer jobs in California are:

Infographic showing various Machine Learning Research Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $104,624 per year, or $50.3 per hour.

Agentic AI & Graph Machine Learning Research Engineer

HRL Laboratories

Calabasas, CA • On-site

$128 - $159.95/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

HRL Laboratories pioneers the next frontiers of physical and information science. Delivering transformative technologies in automotive, aerospace and defense, HRL advances the critical missions of its customers to help them remove limitations and create competitive advantage. HRL then transitions the work back to customers – ready for real-world application. For more than 70 years, HRL's rich portfolio of scientific discoveries and engineering innovations continues to build on each other - often in unexpected, profound and far-reaching ways. As a private company owned jointly by Boeing and GM, HRL prioritizes purpose over profit, significantly advancing the state of the art.

HRL Laboratories develops robust intelligent systems that deliver adaptable, autonomous performance improvement solutions for complex missions. Our teams advance human-machine synergy, operationalized machine learning models and complex systems analytics and agents to create scalable, secure technologies. We design novel algorithms and mission-ready solutions that strengthen decision making for autonomous and human-guided systems across national security and commercial applications.

Position Summary
  • Lead and conduct research in agentic AI, intelligent decision support, autonomous workflows, and LLM-powered agent architectures integrating memory, planning, tool use, and retrieval
  • Design, develop, and evaluate multi-agent systems for distributed decision-making, coordination, communication, and long-horizon task execution across mission-critical domains and applications
  • Build knowledge-enhanced AI systems that integrate structured knowledge sources, including knowledge graphs, GraphRAG pipelines, ontologies, and multimodal retrieval systems to improve reasoning and context awareness
  • Develop and apply graph machine learning (GML) and graph representation learning techniques (e.g., GNNs, geometric deep learning) to support pattern discovery, anomaly detection, and predictive analytics
  • Develop trustworthy AI systems, including Explainable AI (XAI), Verification & Validation (V&V), robustness testing, uncertainty quantification, and safety assessments for agentic and graph-based AI systems
  • Collaborate with multidisciplinary teams, publish high-quality research, support proposal development, and engage with internal and external stakeholders
Required Qualifications
  • Minimum: M.S. in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Network Science, or a related technical field plus 3+ years of relevant industry or research experience in AI/ML
  • Strong background in machine learning, deep learning, natural language processing, generative AI, and multimodal foundation models
  • Experience adapting and optimizing foundation models through prompt engineering, supervised fine tuning, parameter efficient fine tuning, preference optimization, model alignment, and inference optimization techniques
  • Experience developing LLM powered and agentic AI systems using modern agent frameworks (e.g., LangGraph, AutoGen, or equivalent)
  • Familiarity with AI interoperability standards and distributed agent architectures, including Model Context Protocol (MCP), Agent2Agent (A2A), or comparable frameworks for tool integration and multi agent communication
  • Hands on experience with graph mining, graph matching, geometric deep learning, and applied GML workflows
  • Experience with knowledge graphs, ontologies, graph schemas (e.g., LPG, RDF), graph databases (e.g., Neo4j), and graph query languages (e.g., Cypher)
  • Proficiency in Python, PyTorch, and modern software engineering practices (version control, testing, collaborative development)
  • Experience with large scale data processing and distributed systems (e.g., Ray, Spark), and optionally real time streaming or online learning pipelines
  • Experience deploying scalable AI systems using modern LLMOps/AgentOps, distributed inference, GPU acceleration, model serving frameworks (e.g., vLLM, SGLang), observability, and cloud native infrastructure
Preferred Qualifications
  • Ph.D. in a relevant technical discipline with research experience in agentic AI, foundation models, graph machine learning, geometric deep learning, autonomous systems, or related areas
  • Prior research publications in top tier AI/ML venues (e.g., NeurIPS, ICML, ICLR, KDD, WWW, AAAI) are highly desirable
Special Requirements
  • U.S. Citizenship with the ability to obtain and maintain a U.S. Government Security Clearance
Compensation and Benefits
  • Pay Range:$128,000 - $159,950
  • Our salary ranges are determined by role, level, and location (California). The range displayed on each job posting reflects the target range for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range during the hiring process.
  • Benefits: HRL offers a generous and very competitive total compensation and benefits package. Our Regular/Full Time benefits include medical, dental, vision, life insurance, 401K match, gym facilities, PTO, Sick time, upward mobility, and an exciting and challenging work environment.
  • For more information about our company benefit offerings please visit: https://www.hrl.com/careers/benefits

Non-Discrimination and Equal Employment Opportunities (U.S.)

Don't meet every single requirement? Studies have shown that some people are less likely to apply to jobs unless they meet every single desired qualification. At HRL, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

We are proud to be an EEO/AA employer M/F/D/V. We maintain a drug-free workplace and perform pre-employment substance abuse testing.

If you would like more information about Equal Employment Opportunity as an applicant under the law, please go to Employees & Job Applicants | U.S. Equal Employment Opportunity Commission

For our privacy policy please visit: www.hrl.com/privacy

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