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Machine Learning Engineer Jobs in Berkeley, CA (NOW HIRING)

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

Machine Learning Engineer We are looking for a Machine Learning Engineer to join the growing AI and Machine Learning team at Strava. This team is responsible for sophisticated machine learning models ...

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of key technologies and ...

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Machine Learning Engineer Fremont, California Gotion Inc. is based in Silicon Valley, CA, currently building a Manufacturing facility in Manteno, IL and has R&D centers in Ohio, China, Japan and ...

Machine Learning Engineer

San Francisco, CA · On-site

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

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Showing results 1-20

Machine Learning Engineer information

See Berkeley, CA salary details

$38.6K

$157.7K

$236.9K

How much do machine learning engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for machine learning engineer in Berkeley, CA is $157,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,300.00 and $189,800.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are popular job titles related to Machine Learning Engineer jobs in Berkeley, CA? For Machine Learning Engineer jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Berkeley, CA look for? The top searched job categories for Machine Learning Engineer jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Machine Learning Engineer jobs? Cities near Berkeley, CA with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Berkeley, CA as of June 2026, with employment types broken down into 96% Full Time, and 4% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $157,670 per year, or $75.8 per hour.

Machine Learning Engineer

Poesis

San Francisco, CA • On-site

$200K - $280K/yr

Full-time

Medical, Dental, Vision

Posted 26 days ago


Job description

About Poesis
Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal.
About the Role
At Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management. We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power investment decision-making across the platform. You'll work across the full machine learning lifecycle, from experimentation and model and agent development to deployment and iteration, with significant ownership over both research and production outcomes.
Responsibilities
  • Rapidly implement and iterate on machine learning models, signals and research ideas
  • Design and run experiments to evaluate and improve model and agent performance and investment impact
  • Build reproducible workflows for feature generation, training, validation and evaluation
  • Work with large-scale financial, fundamental and alternative datasets to identify predictive signals and improve model performance

Required Competencies
  • 5+ years experience as a Machine Learning Engineer, or related role
  • Prior experience at a frontier AI lab, agentic startup, leading hedge fund, big tech company, or similar
  • Strong Python and SQL skills, with experience working with large-scale datasets
  • Experience developing, evaluating and deploying machine learning models in production environments
  • Success building reproducible research workflows and experimentation frameworks
  • Familiarity with modern AI systems, including LLMs, evaluation frameworks, and agent workflows
  • Skill leveraging Claude Code, Codex, or other coding agents
  • BS/MS/PhD in Computer Science or a related field, or equivalent practical experience

Preferred Competencies
  • Experience developing ML and AI systems using financial, fundamental, alternative, or time-series datasets
  • Familiarity with quantitative investing, portfolio construction, or risk management
  • Experience with PyTorch or TensorFlow, and AI workflows for parsing financial documents (filings, transcripts)

Location
Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.
Benefits
We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches in our Menlo Park office, commuter benefits, and more.
Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.
Working at Poesis
As an early team member, you'll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You'll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.