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

Machine Learning Engineer (Full time) JOB DUTIES: The Machine Learning Engineer will design, develop, deploy, and maintain advanced machine learning models and data analysis systems to support ...

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

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 ...

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 ...

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 ...

They are seeking a Machine Learning Engineer to contribute to the development of tools and infrastructure for interpretable AI systems, playing a key role in transforming research into usable product ...

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

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 ...

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 ...

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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

Alt

San Francisco, CA • On-site, Remote

$196K/yr

Other

Posted 5 days ago


Job description

REFERRALS: The below position is eligible for employee incentives provided pursuant to Alt Platform Inc.'s referrals policy, which is described in detail at https://app.notion.com/p/altxyz/Hiring-Referral-program-29d859d114314e39886ae51c9fb1bdf9?source=copy_link

EMPLOYER NAME: Alt Platform Inc.

JOB TITLE: Machine Learning Engineer (Full time)

JOB DUTIES: The Machine Learning Engineer will design, develop, deploy, and maintain advanced machine learning models and data analysis systems to support specialized domain modeling and proprietary feature engineering. The person in this role will analyze structured and unstructured datasets, perform applied experimentation, develop production-grade machine learning pipelines, optimize modeling infrastructure, and collaborate across business and engineering teams to translate business needs into scalable data-driven solutions. The Machine Learning Engineer will be primarily responsible for the following duties:

  • Conduct applied research and experimentation to design, train, evaluate, and refine machine learning models, including performing feature engineering, selecting modeling techniques, validating model performance, and documenting analytical methods.
  • Develop, test, and deploy production machine learning systems by managing the complete MLOps lifecycle, including experiment tracking, model versioning, containerization, orchestration of automated workflows, and monitoring of model performance in production environments.
  • Maintain and optimize machine learning infrastructure to support training, inference, and data processing workflows, including configuring cloud compute environments, tuning distributed computation jobs, and improving system efficiency and scalability.
  • Collaborate with business stakeholders to translate analytical requirements into quantifiable modeling objectives, define evaluation criteria, validate assumptions with data, and communicate analytical findings and modeling results.
  • Design, prepare, and review technical documentation, including model design specifications, architecture diagrams, data-flow documentation, and systems integration requirements to support maintainability and long-term scalability.
  • Develop AI-driven automation solutions using Large Language Models to streamline internal workflows, design LLM-based agentic processes, validate automated outputs, and measure accuracy and efficiency improvements.
  • Design and develop internal software tools and backend services that support data quality, enable analytical workflows, expose model insights to internal teams, and integrate with organizational data systems and APIs.

No travel is required.

Fully remote position (100%) from anywhere in U.S. reporting to HQ in  San Francisco, CA 

JOB REQUIREMENTS: Master's degree (or foreign equivalent) in data science, economics, mathematics or computer science and 1 year of experience in any occupations in which required experiences were acquired (may be pre-Master's).  Professional experiences must include:

  • 1 year of experience designing, training, and evaluating machine learning models using Python-based data science libraries, including experience performing feature engineering and developing predictive and descriptive models using tools such as scikit-learn and pandas.
  • Experience using machine-learning lifecycle tools, including MLflow (or similar platforms) for experiment tracking, reproducible training workflows, and model versioning.
  • Experience using Docker for containerization to package machine learning pipelines and ensure reproducible deployment environments.
  • 1 year of experience orchestrating data processing and machine learning workflows, including scheduling, monitoring, and managing dependencies using Apache Airflow.
  • 1 year of experience using CI/CD tools to automate model training, testing, and deployment processes.
  • 1 year of experience configuring and optimizing cloud compute environments to support training, inference, and large-scale data processing tasks.
  • 1 year of experience developing AI-driven automation workflows using language models, including integrating language-based model components into analytical or operational processes.
  • Experience developing backend services and APIs using FastAPI, REST, or GraphQL to support data access, model serving, and analytical tooling.
  • 1 year of experience working with SQL databases, including PostgreSQL, and cloud data platforms (e.g., Snowflake), including writing analytical queries and implementing data-quality validation workflows.
  • Experience using distributed data-processing tools, including Spark, for large-scale data transformation and feature-engineering operations.

SALARY OFFERED: From $196,776 per year

JOB LOCATION: San Francisco, CA

TO APPLY SEND RESUME TO: Eryn@alt.xyz (write "Machine Learning Engineer" in subject line)