1

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

We are seeking an experienced Data Science Engineer to join our team. The ideal candidate will have strong expertise in data science, machine learning, and AI-driven features that enhance decision ...

... machine learning operations, continuous integration/continuous delivery pipelines, and DevOps practices Experience applying AI solutions in finance, healthcare, or supply chain environments ...

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials ...

New

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

next page

Showing results 1-20

Machine Learning Engineer information

See Folsom, CA salary details

$33.7K

$137.7K

$206.9K

How much do machine learning engineer jobs pay per year?

As of Jun 27, 2026, the average yearly pay for machine learning engineer in Folsom, CA is $137,693.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $165,700.00 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 the most commonly searched types of Machine Learning Engineer jobs in Folsom, CA? The most popular types of Machine Learning Engineer jobs in Folsom, CA are:
What are popular job titles related to Machine Learning Engineer jobs in Folsom, CA? For Machine Learning Engineer jobs in Folsom, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Folsom, CA look for? The top searched job categories for Machine Learning Engineer jobs in Folsom, CA are:
What cities near Folsom, CA are hiring for Machine Learning Engineer jobs? Cities near Folsom, CA with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Folsom, CA as of June 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $137,693 per year, or $66.2 per hour.
Generative AI Engineer III - State and Local Government with Security Clearance

Generative AI Engineer III - State and Local Government with Security Clearance

Deloitte

Sacramento, CA • On-site

$61.25 - $82.25/hr

Other

Posted 14 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

55th of 139 rated financial services


Job description

Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and help make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation. Work you'll do As an AI and Data Science Engineer III on the team, you will be responsible for: * Design, build, test, and deploy machine learning and artificial intelligence solutions for business and client use cases * Develop and maintain data pipelines, model training workflows, and production-grade application components that support AI-enabled products * Analyze structured and unstructured data to identify patterns, generate insights, and support model development and validation * Collaborate with engineers, data scientists, product stakeholders, and business teams to translate requirements into technical solutions * Monitor model and application performance, troubleshoot issues, and implement enhancements to improve accuracy, reliability, and scalability A successful candidate would possess these skills: * Ability to work independently and collaborate as part of a team * Effective written and verbal communication skills * Meticulous attention to detail and quality of work product * Ability to build and sustain professional relationships * Ability to lead projects or workstreams * Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong interpersonal skills and professional demeanor * Ability to meet deadlines * Ability to provide clear guidance to others The team Deloitte's Government & Public Services (GPS) practice - our people, ideas, technology and outcomes - is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise. Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively with organizational intelligence programs and differentiated strategies to win in their chosen markets. Qualifications Required: * Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a quantitative field * 5+ years of professional experience designing, developing, deploying, or supporting machine learning, artificial intelligence, or advanced analytics solutions * 3+ years of experience programming in Python, PySpark, PyTorch, and TensorFlow
* 1+ years of technology consulting experience in the State Government or Local Government space * Active certification in Python, PySpark, PyTorch, or TensorFlow * Ability to travel 20%, on average, based on the work you do and the clients and industries/sectors you serve. * Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future. Preferred: * Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a quantitative field * Ability to obtain and maintain a US government security clearance
* 2+ years of experience deploying machine learning models into production environments * 2+ years of experience working with large language models, natural language processing, or generative artificial intelligence solutions * 2+ years of experience using containerization and orchestration tools such as Docker or Kubernetes * 1+ years of experience supporting model monitoring, model governance, or machine learning operations processes The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $ 110,700 to $218,300. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. ai&e fy27 profile

What Deloitte employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom