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

Machine Learning Engineer

San Francisco, CA · On-site +1

$187K - $260K/yr

Collaborate with other engineers to improve the recommendation systems and models that power personalization and discovery. Train, evaluate, and deploy sophisticated machine learning models to ...

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $400K/yr

About the role We're looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable AI systems at scale. You'll play a central role in ...

The Role We're looking for a Machine Learning Engineer who loves getting close to the metal. This is a hands-on engineering role focused on making models faster, more efficient, and more reliable ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$187K - $260K/yr

Special Skill Requirements: 1.) Machine Learning; 2.) TensorFlow; 3.) Python and SQL; 4.) Feature Engineering and Selection; 5.) Ads predictive model design; 6.) Ads predictive model offline training ...

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $400K/yr

About the role We're looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable AI systems at scale. You'll play a central role in ...

About the Role As a Machine Learning Engineer on the AI Core team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG. You will collaborate with other engineers to ...

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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 Jul 5, 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.

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-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants 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 AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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 1% As Needed, 91% Full Time, 6% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $157,670 per year, or $75.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

UnifyID (acquired by Prove)

Redwood City, CA • On-site

Full-time

Posted 3 days ago


Job description

About Prove (acquired UnifyID)
Prove is the modern platform for continuous identity authentication and is used by over 1,000 enterprises and 500 financial institutions, including 9 of the top 10 U.S. banks. Prove's cloud solutions, and mobile intelligence-driven APIs can be easily orchestrated to increase Approve Rates to over 90%, enabling companies to authenticate customer identities accurately, effortlessly, and privately while mitigating fraud. Prove's solutions are available in 195 countries.
For the latest updates from Prove, follow us on LinkedIn.
About the role
We are looking for a seasoned software engineer to join our A+ technical team in designing, building and deploying machine learning solutions into production.
UnifyID is building a platform to solve one the world's biggest unsolved security problems in a completely novel way, requiring us to push the boundaries of what's possible in production machine learning and on mobile devices. Our data analytics platform can translate mobile sensor data from real-world human activity into a "digital fingerprint" with no conscious action from the user, all in real-time, and in a way that respects user privacy. This is an opportunity to be a part of something truly unique and game-changing.
We are looking for natural-born builders who are comfortable in multiple technical areas, have creative problem-solving skills, a love for coding and technology and a "get stuff done" attitude.
Your day-to-day
  • Be an early member of a high-performing team of software engineers and machine learning researchers building a new human identity platform
  • Take ownership, be creative, and think outside the box to invent and build solutions to real-world customer problems
  • Interface with our world-class machine learning research team to help turn core research into reality
  • Wrangle and perform experiments on petabyte-scale data sets
  • Wear many hats to make things happen in a dynamic startup environment
  • Bring your own unique expertise to the team and learn from others
  • Enjoy tight collaboration with your teammates

Ideal candidates will have...
  • Spent at least 5 years in the trenches of the software industry, delivering quality software that matters to people that care
  • Many "been there, done that" stories related to shipping and maintaining major software products for customers
  • Excellent coding skills in an object-oriented language (Go, Python, Rust, Java, C++, Ruby, etc...)
  • Experience working with high volumes of data, ideally with machine learning playing a critical role
  • Strong foundational knowledge of mathematics, bonus if related to machine learning or signals processing
  • A breadth of technical skills and know how to use the right tool for the job
  • High motivation and ability to learn new technologies and domains
  • A positive can-do attitude and bring a passion for excellence to the workplace
  • Excellent collaboration and communication skills
  • Professional experience with AWS, Kubernetes a bonus
  • Knowledge of cybersecurity, signals processing, or experience working with time-series data a bonus

Join us!
As we continue to scale our company, we are looking for people who know how to make an impact. We're talking self-starting professionals who thrive in a fast-paced environment, process information quickly, and make intelligent decisions. The work is challenging and requires not only smarts but natural curiosity and tenacity. Teamwork is also important to us - we work together and play together.
Prove has big plans; we're excited and optimistic about the future. If this sounds like a career for you - come check us out.
This team is located in the heart of Silicon Valley in downtown Redwood City and has unparalleled access to deep entrepreneurial expertise, high-caliber academic research institutions, and top-tier VC resources.
Finally, it is important that you be authentic and be yourself.
Prove is an equal opportunity employer committed to providing equal employment opportunity for all people regardless of race, color, religion, gender or sexual orientation, age, marital status, national origin, citizenship status, disability, veteran status, or other personal characteristics.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.