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Machine Learning Contract Remote Jobs in California

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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All JobsMachine Learning Contract JobsMachine Learning Contract Remote JobsMachine Learning Contract Remote Jobs in California

Machine Learning Contract Remote information

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$8

$23

$60

How much do machine learning contract remote jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for machine learning contract remote in California is $23.62, according to ZipRecruiter salary data. Most workers in this role earn between $14.95 and $27.45 per hour, depending on experience, location, and employer.

What is a machine learning contract remote job?

Machine learning contract remote jobs are temporary work opportunities where professionals use machine learning techniques to solve problems for organizations, but do so remotely, often from home or another location. These roles typically involve building, training, and deploying models, analyzing data, and collaborating with teams virtually. Contracts can vary in length and scope, allowing flexibility for both the employer and the worker. These positions are ideal for individuals seeking project-based work or more flexible schedules, and require strong technical skills and the ability to communicate effectively online.

What skills and qualifications are needed to thrive as a machine learning contractor in a remote role?

To thrive as a Machine Learning Contractor working remotely, you need strong proficiency in mathematics, programming (typically Python), and a solid understanding of machine learning algorithms, usually supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and cloud platforms such as AWS or Azure is essential, as well as experience with version control systems like Git. Excellent self-motivation, time management, and communication skills help you effectively collaborate with distributed teams and manage multiple projects independently. These competencies are crucial for delivering high-quality, scalable solutions and meeting client expectations in a flexible, remote work environment.

What are common challenges faced by remote machine learning contractors, and how can they be addressed?

Remote machine learning contractors often face challenges such as managing communication across time zones, accessing necessary data securely, and staying aligned with the client's project expectations. To address these, it’s important to establish clear communication channels, use secure data transfer protocols, and schedule regular check-ins with project stakeholders. Building strong documentation habits and leveraging collaborative tools like version control or shared notebooks can also help ensure smooth workflow and project transparency.

What is the difference between Machine Learning Contract Remote vs Data Scientist Contract Remote?

AspectMachine Learning Contract RemoteData Scientist Contract Remote
Required CredentialsDegree in Computer Science, Data Science, or related field; experience with ML frameworksDegree in Statistics, Data Science, or related; proficiency in data analysis tools
Work EnvironmentRemote, project-based, often collaborative with ML engineersRemote, analytical, often cross-functional teams
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting
Common Search & ComparisonYesYes

Machine Learning Contract Remote roles focus on developing and deploying ML models, requiring specialized skills in algorithms and frameworks. Data Scientist Contract Remote positions emphasize data analysis, statistical modeling, and insights generation. While both roles often work remotely and share similar credentials, their core responsibilities differ, making this comparison useful for job seekers exploring related opportunities.

What are popular job titles related to Machine Learning Contract Remote jobs in California?

For Machine Learning Contract Remote jobs in California, the most frequently searched job titles are:

What job categories do people searching Machine Learning Contract Remote jobs in California look for?

The top searched job categories for Machine Learning Contract Remote jobs in California are:

What cities in California are hiring for Machine Learning Contract Remote jobs?

Cities in California with the most Machine Learning Contract Remote job openings:

Machine Learning Contract Remote jobs near you
Infographic showing various Machine Learning Contract Remote job openings in California as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $49,125 per year, or $23.6 per hour.

Machine Learning Engineer

San Francisco, CA • On-site, Remote

Swish Analytics
Spectator Sports • 1 - 10 employees
Learn more about Swish Analyticsexternal

$160K/yr

Full-time

Re-posted 27 days ago

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.
The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to "roll your own" and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.
This position is 100% remote
Responsibilities:
  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.
  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.
  • Build, test, deploy and maintain production systems.
  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.
  • Support maintenance and optimization of cloud-native EDW and ETL solutions.
  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Use extensive experience to build, test, debug, and deploy production-grade components.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:
  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area
  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs
  • A proven background in quantitative analytics, trading, or engineering is required for this position
  • Demonstrated experience developing data science modeling systems and infrastructure at scale
  • Experience with Python and exposure to modern machine learning frameworks
  • Proficient in SQL; experience with MySQL
  • Background and/or interest in Rust preferred
  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Engineering & Infrastructure Role Data Science Infrastructure Locations San Francisco, CA - Remote Remote status Fully Remote

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