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Artificial Intelligence Machine Learning Engineer Jobs in Novato, CA

Human Archive

Machine Learning Engineer

San Francisco, CA · On-site

$100K - $150K/yr

Research into human physical intelligence - including the human hand, proprioception, and vision ... The Opportunity As a Machine Learning Engineer, you'll work on multimodal perception, VLA training ...

Adobe

Senior Machine Learning Engineer

San Francisco, CA · On-site

$172K - $306K/yr

... artificial intelligence to new heights. What You'll Do As a Senior Machine Learning Engineer on the ... Content Intelligence team, you will lead the development of ML models and systems, to assist with ...

S27a

Machine Learning Engineer

San Francisco, CA · On-site

$140 - $210/hr

Stay familiar with and evaluate state of the art research in process mining, workflow intelligence ... machine learning systems to ensure continuous improvement. * Collaborate with software engineers ...

Qubeaxis

Machine Learning Engineer

San Francisco, CA · On-site

$130 - $180/hr

Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML Platform team builds intelligent systems that power recommendations, forecasting, ranking ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

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All JobsArtificial Intelligence Machine Learning Engineer JobsArtificial Intelligence Machine Learning Engineer Jobs in Novato, CA

Artificial Intelligence Machine Learning Engineer information

See Novato, CA salary details

$37K

$151.2K

$227.2K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for artificial intelligence machine learning engineer in Novato, CA is $151,183.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,200.00 and $182,000.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Novato, CA look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Novato, CA are:

What cities near Novato, CA are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Novato, CA with the most Artificial Intelligence Machine Learning Engineer job openings:

Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Novato, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $151,183 per year, or $72.7 per hour.

Machine Learning Engineer

Human Archive

San Francisco, CA • On-site

$100K - $150K/yr

Full-time

Re-posted 29 days ago

Job description

About Human Archive
Human Archive is a research lab focused on modeling human embodied intelligence.
Humans are the most sophisticated biological systems we have ever observed, yet we still do not fully understand ourselves. Research into human physical intelligence - including the human hand, proprioception, and vision - remains largely unsolved. Our mission is to recover human embodied intelligence as a learned model. To achieve this, we build custom hardware products, deploy them globally at scale, and publish research. Today, our data is used for robotics and world modeling, but the broader opportunity is advancing scientific research into intelligence itself.
Founded by Stanford and UC Berkeley researchers, we are lean, deeply technical, and operate at extreme speed, taking on unglamorous and conventionally impossible problems that directly unlock step-function gains in model capability.
The deployment of capable humanoids at scale will permanently redefine human labor. Undesirable physical work will disappear, and human effort will shift toward a new era of abundant creativity.
We are building the infrastructure to accelerate that transition by assembling the Human Archive mafia. You will own meaningful systems from day one and see your work directly impact model capabilities. This is a once-in-a-generation inflection point. If you want to help reshape physical labor and work on problems that matter at civilizational scale, join us.
The Opportunity
As a Machine Learning Engineer, you'll work on multimodal perception, VLA training, robotics post-training, and downstream policy evaluation. This is a hands-on role at the intersection of applied machine learning, data infrastructure, and robotics, where your work directly shapes how data is collected, validated, annotated, and evaluated.
You'll help close the loop between research and data collection by fine-tuning VLAs on downstream policy performance and building post-training and reinforcement learning systems around real-world robotics tasks. You'll be expected to make architectural decisions, own projects end-to-end, and operate in highly ambiguous research environments given the novelty and scale of our multimodal datasets.
Your work will help shape how frontier labs and leading robotics companies train their models, transforming physical labor markets and economies while contributing to broader research into human embodied intelligence.
What You'll Do
  • Build systems for multimodal perception, annotation, dataset QA, and robotics evaluation
  • Publish research on multimodal data by fine-tuning and evaluating VLA models on downstream robotics tasks and policy performance
  • Build post-training and reinforcement learning systems around robotics failure modes and corrective demonstrations
  • Work across video understanding, tracking, pose estimation, temporal modeling, and multimodal alignment
  • Develop tooling for benchmarking, observability, and temporal efficiency
  • Prototype quickly, ship rapidly, and iterate from real-world robotics deployments and research feedback
What We're Looking For
  • Passionate, mission-driven individuals who have demonstrated exceptional ownership in previous work
  • Engineers who want their work to directly impact the next frontier of physical AGI
  • Strong ML engineering fundamentals across robotics, computer vision, and perception systems
  • Experience with video understanding, tracking, pose estimation, robotics, or real-world sensor systems
  • Strong technical intuition and ability to move quickly in ambiguous research environments
  • Published research or production experience in robotics, embodied AI, reinforcement learning, motion capture, or vision systems is a strong plus

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