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Freelance Machine Learning Engineer Jobs in Davis, CA

AI Engineer Job Location: Woodland - California Job Type: Contract ... Design develop and deploy machine learning models and algorithms using Python Lead data science ...

Lead AI and Data Science Engineer II

Sacramento, CA ยท On-site

$109K - $144K/yr

Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns ... Lead AI and Data Science Engineer II Drive the design and delivery of advanced analytics ...

Lead AI / ML Engineer

Sacramento, CA ยท On-site

$109K - $144K/yr

Developing and deploying machine learning models and AI solutions. At least 2 from the following ... Proficiency in programming languages like Python, R, or Java. Familiarity with AI and machine ...

Senior Data Scientist

Sacramento, CA ยท On-site

$116K - $241K/yr

Fluency in the Python programming language and competency using Python's standard machine learning libraries, and a willingness to learn (if necessary) other programming languages such as R and SQL.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Within our Data and Analytics Engineering practice, you will apply data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale. As a Director, you will ...

Showing results 21-40

Freelance Machine Learning Engineer information

See Davis, CA salary details

$16

$51

$142

How much do freelance machine learning engineer jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for freelance machine learning engineer in Davis, CA is $51.57, according to ZipRecruiter salary data. Most workers in this role earn between $26.25 and $66.78 per hour, depending on experience, location, and employer.

What does a freelance machine learning engineer do?

A Freelance Machine Learning Engineer designs, develops, and implements machine learning models and algorithms for clients on a project basis. They work independently to analyze data, build predictive models, and help businesses solve complex problems using AI and machine learning techniques. Their responsibilities may also include data preprocessing, model evaluation, and deploying solutions into production environments. Freelance Machine Learning Engineers often collaborate remotely with teams and must manage their own schedules and client relationships.

What are the key skills and qualifications needed to thrive as a freelance machine learning engineer?

To thrive as a Freelance Machine Learning Engineer, you need expertise in programming (especially Python), a solid grasp of machine learning algorithms, and a relevant academic background such as a degree in computer science, mathematics, or engineering. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, GCP, Azure), and experience with version control systems are typically required. Strong problem-solving, self-management, and client communication skills help set successful freelancers apart. These competencies are crucial for delivering effective solutions, managing projects independently, and building client trust in a competitive market.

How do freelance machine learning engineers typically manage client expectations and project scopes?

Freelance machine learning engineers often work with clients who may not have a deep technical understanding of AI or data science. A common challenge is clearly defining the project scope and deliverables at the outset, ensuring both parties understand what is feasible given the data, time, and budget constraints. Successful freelancers use regular progress updates, milestone-based deliverables, and transparent communication to manage expectations and avoid scope creep. Building trust through clear documentation and setting realistic timelines also helps foster long-term client relationships.

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

AspectFreelance Machine Learning EngineerData Scientist
CredentialsTypically requires a degree in computer science, data science, or related fields; certifications in machine learning or AI are a plusUsually holds a degree in statistics, data science, or related areas; certifications in data analysis or visualization are common
Work EnvironmentIndependent, project-based work often remotely for various clientsOften employed full-time in organizations or consulting roles, sometimes freelance
Industry UsageUsed across tech, finance, healthcare, and startups for deploying ML modelsApplied in research, analytics, and strategic decision-making across industries

Freelance Machine Learning Engineers focus on developing and deploying ML models independently for diverse clients, while Data Scientists analyze data to extract insights, often working within organizations. Both roles require strong technical skills, but their work scope and environment differ significantly.

What are the most commonly searched types of Machine Learning Engineer jobs in Davis, CA? The most popular types of Machine Learning Engineer jobs in Davis, CA are:
What cities near Davis, CA are hiring for Freelance Machine Learning Engineer jobs? Cities near Davis, CA with the most Freelance Machine Learning Engineer job openings:
Infographic showing various Freelance Machine Learning Engineer job openings in Davis, CA as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 28% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $107,256 per year, or $51.6 per hour.

AI Engineer

Staffingine LLC

Woodland, CA โ€ข On-site

Contractor

Re-posted 20 days ago


Job description

Job Title: AI Engineer
Job Location: Woodland - California
Job Type: Contract

Job Description:

  • Design develop and deploy machine learning models and algorithms using Python Lead data science projects from concept to implementation ensuring timely delivery and quality outcomes
  • Perform exploratory data analysis to identify patterns trends and opportunities for business improvement
  • Collaborate with stakeholders to define key performance indicators and success metrics Optimize existing data science workflows and models for better performance and accuracy
  • Document methodologies code and findings to ensure reproducibility and knowledge sharing
  • Support the integration of data science solutions into production environments
  • Drive continuous improvement initiatives by evaluating new tools and technologies relevant to Python and data science

Skills

Mandatory Skills : Python - Data Scienc