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

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 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 ...

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 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 ...

Camera Machine Learning Engineer - Camera Hardware Are you a passionate Machine Learning Engineer with a deep love for photography? Join Apple's Camera Hardware Engineering team and help us redefine ...

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 ...

Tesla is seeking a passionate and skilled Machine Learning Engineer to join their Noise, Vibration, and Harshness (NVH) team. This role involves designing, developing, and deploying machine learning ...

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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 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

Machine Learning Engineer

Velo3D

Fremont, CA

$150K - $220K/yr

Full-time

Posted 11 days ago


Job description

Position Overview: 

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 engineers, software engineers, and fellow ML engineers, you will develop and deploy models using image, time-series, and machine log data from advanced manufacturing systems.

Prior experience in additive manufacturing or 3D printing is not required. We are particularly interested in candidates with scientific, engineering, or technical backgrounds who have applied machine learning to complex real-world problems involving sensor data, physical systems, or experimental datasets, and who enjoy working closely with domain experts to deliver practical, high-impact solutions.

Responsibilities
  • Develop ML models using in-process sensor data to identify anomalies and quality issues during printing. 

  • Build and iterate on training and evaluation workflows; document experiments and results for reproducibility. 

  • Own ML experimentation end to end: Design datasets, preprocessing pipelines, and training workflows; iterate on model architectures and metrics; document experiments and results for reproducibility. 

  • Help define data collection and management: Partner with process and software teams to improve how build data is ingested, cataloged, versioned, and made available for training and evaluation. 

  • Deploy models into production: Work with print software and embedded teams to integrate validated models into production code running on printer hardware, including performance and reliability considerations. 

  • Collaborate with supporting software engineers: Hand off validated Python prototypes for production hardening, provide clear specifications and acceptance criteria, and support integration and regression testing. 

Requirements
  • Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field; advanced degree preferred. 

  • 3+ years of experience building and evaluating machine learning models in a professional setting. 

  •  Hands-on experience with computer vision or image-based ML (e.g., segmentation, classification, or anomaly detection). 

  • Strong Python skills and experience with modern ML frameworks (e.g., PyTorch). 

  • Experience designing ML pipelines: data loading, preprocessing, training, evaluation, and experiment tracking. 

  • Comfort working in a production software environment: version control, code review, testing, and cross-functional collaboration. 

  • Ability to communicate technical tradeoffs clearly to engineers and non-engineers. 

  • Strong programming skills in Python or C++. 

  • Experience organizing and working with structured and unstructured datasets. 

  • Background in a STEM or scientific discipline, with demonstrated use of ML to address substantive technical or engineering problems. 

Bonus  

  • Experience with powder bed fusion or other additive manufacturing processes. 

  • Knowledge of manufacturing data workflows, IoT sensor data, or industrial automation systems. 

  • Experience with image-based or time-series machine learning. 

  • Familiarity with model deployment in production or embedded environments. 

  • Familiarity with cloud storage and data pipelines (e.g., AWS S3, batch retrieval workflows). 

  • Experience in domains such as robotics, aerospace, materials, instrumentation, scientific computing, or other fields where ML is applied to physical or experimental data. 

About the Company:
 
Velo, Velo3D, Sapphire and Intelligent Fusion are registered trademarks of Velo3D, Inc. Without Compromise, Flow, Flow Developer, and Assure are trademarks of Velo3D, Inc.
 
With the only SupportFree laser powder bed fusion capability, we enable on-demand manufacturing of production quality Titanium, Inconel, and Aluminum parts with an unprecedented degree of design freedom and quality control. The VELO3D award-winning solution includes an integrated offering of hardware and software: Sapphire® metal AM production printer, Flow™ print preparation software, Assure™ quality assurance and control system, and an integrated manufacturing process that runs throughout the printing operation.
 
Our team enjoys excellent benefits including healthcare coverage and 401(K) employer contributions. We believe in transparency and recognizing exceptional efforts through our monthly all-hands meetings and team member appreciation awards.
 
Our job titles may span more than one career level. The starting base salary for this full-time position is between $150,000 and $220,000. This salary range reflects the minimum and maximum target for this position in the U.S. The actual base pay is dependent upon many factors, such as work experience, job-related skills, related education, work location, and market demands. The base pay range is subject to change and may be modified in the future. In addition to a competitive base salary and a comprehensive benefits package, this position may be eligible for other forms of compensation such as participation in a bonus and equity program, as applicable.
 
Velo3D provides equal employment opportunities to all employees and applicants for employment without regard to, and prohibits discrimination and harassment based on, race, color, religion, age, sex, national origin, disability, medical condition, genetic information, military or veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
 
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.