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Machine Learning Research Scientist Jobs in California

LLNL

Machine Learning Research Engineer

Livermore, CA · On-site

$146K - $222K/yr

This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate. Essential Duties * Research, develop, implement, and evaluate new machine learning ...

LLNL

Machine Learning Research Engineer

Livermore, CA · On-site

$9.8K/wk

This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate. Essential Duties * Research, develop, implement, and evaluate new machine learning ...

LLNL

Machine Learning Research Engineer

Livermore, CA · On-site

$146K - $222K/yr

This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate. Essential Duties * Research, develop, implement, and evaluate new machine learning ...

Horizon Robotics

Research Scientist

Cupertino, CA · On-site

$150K - $300K/yr

We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL) , etc. As a Research Scientist in the team ...

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All JobsMachine Learning Research Scientist JobsMachine Learning Research Scientist Jobs in California

Machine Learning Research Scientist information

See California salary details

$49.8K

$128.4K

$171.7K

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

As of Jul 16, 2026, the average yearly pay for machine learning research scientist in California is $128,413.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $170,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Research Scientist position, and why are they important?

To thrive as a Machine Learning Research Scientist, you need a strong background in mathematics, statistics, programming (typically Python or similar), and experience with machine learning frameworks, usually supported by an advanced degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Scikit-learn, and proficiency in data handling and cloud platforms is highly valued, alongside certifications like Google Cloud ML Engineer as a plus. Innovative thinking, strong communication, and effective problem-solving skills help set exceptional researchers apart. Mastery of both technical and soft skills is essential for developing impactful models, collaborating across multidisciplinary teams, and staying ahead in this fast-evolving field.

What are the typical projects and daily responsibilities for a Machine Learning Research Scientist?

As a Machine Learning Research Scientist, your typical projects may include developing novel algorithms, conducting experiments on large datasets, implementing and tuning models, and publishing research findings. Your daily responsibilities often involve coding, data analysis, reading the latest literature, collaborating with engineers and product teams, and participating in internal discussions about research direction. You may also mentor junior researchers, contribute to open-source projects, and present results at conferences or internal meetings. This role offers a dynamic work environment where continuous learning and innovative problem-solving are highly encouraged.

What is a Machine Learning Research Scientist job?

A Machine Learning Research Scientist develops new algorithms and models to advance the field of artificial intelligence. They conduct experiments, analyze data, and publish research to push the boundaries of machine learning theory and applications. Their work often involves designing novel architectures, optimizing existing models, and collaborating with engineers to bring research into production. This role typically requires a deep understanding of mathematics, statistics, and programming, along with experience in areas like deep learning, reinforcement learning, or probabilistic modeling.

What are the most commonly searched types of Machine Learning Research Scientist jobs in California? The most popular types of Machine Learning Research Scientist jobs in California are:
What are popular job titles related to Machine Learning Research Scientist jobs in California? For Machine Learning Research Scientist jobs in California, the most frequently searched job titles are:
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Machine Learning Research Scientist jobs near you

Machine Learning Research Scientist

Autoscience

Menlo Park, CA • On-site

Full-time

PTO

Posted 4 days ago

Job description

Company Description

At Autoscience Institute, we create AI systems that autonomously conduct AI research. Recently, we announced the first AI agent to autonomously create peer-reviewed literature (ICLR 2025 Workshops). We are passionate about pushing the boundaries of artificial intelligence and contributing to groundbreaking advancements in the field.

Role Description

This is a full-time on-site role for a Machine Learning Research Scientist located in the San Francisco Bay Area.

  • Work directly with the founder to develop autonomous research systems that ideate, experiment, and improve customer models.

  • Collaborate with the engineering team to build and deploy production-ready research systems.

  • RL post-train and fine-tune reasoning models to automate components of the machine learning research process.

  • Stay current with the latest developments in AI research and automation.

Qualifications:

  • Education: PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Exceptional candidates with strong research contributions are encouraged to apply regardless of formal degree.

  • Research: Publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, etc) or equivalent industry experience at corporate AI research labs (Microsoft, Google, Nvidia, TRI etc).

  • Technical: Expertise in training machine learning models, including deep learning, reinforcement learning or genetic algorithms. This does not include building multi-agent systems using LLM APIs or building RAG-based agents.

  • Curiosity: Passion for accelerating scientific discovery through AI and willingness to explore uncharted directions with minimal supervision.

Recommended Qualifications

  • Systems: Experience building scalable and production-ready machine learning pipelines or large-scale model training (distributed model training over >64 GPUs).

  • Science: Any background or proven interested in Automated Scientific Research is a plus.

Benefits & Perks

  • Our comp is competitive against major LLM frontier lab packages

  • Unlimited PTO and flexible working arrangements

  • Conference attendance and publication support

Our Culture

We're a team of passionate researchers and engineers working to automate scientific discovery. We believe in the power of AI to accelerate scientific discovery and are committed to responsible AI development
We are an e-verify employer.