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Remote Applied Scientist Machine Learning Jobs in California

Applies data science/ machine learning /artificial intelligence methods to develop defensible and ... Applied Sciences, Statistics, or equivalent field. * 6 years in data science OR no experience, if ...

The Role We are seeking a Machine Learning Engineer to develop advanced models for extracting ... BSc or MSc degree in quantitative fields (e.g., computer science, engineering, physics, applied ...

Physics AI Scientist III

Santa Clara, CA ยท On-site +1

$142K - $196K/yr

D in Mechanical Engineering, Chemical Engineering, Materials Science, Physics, Applied Mathematics, Computer Science, or a related field. Experience applying machine learning to real-world scientific ...

By combining physics and chemistry expertise with advanced machine learning, our platform improves ... Remote-first with co-working access at Industrious offices * 401(k) with employer match * Equity ...

AI Data Scientist - Remote

Palo Alto, CA ยท Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

New

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

New

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

New

Showing results 21-40

Remote Applied Scientist Machine Learning information

What does a remote applied scientist machine learning do?

A Remote Applied Scientist in Machine Learning develops and implements machine learning models to solve real-world problems, often from a location outside of a traditional office. Their work involves analyzing large datasets, designing algorithms, and collaborating with teams to deploy scalable solutions. They may also conduct experiments to improve model performance and stay up to date with the latest research in the field. Communication and documentation are important, as they often work with cross-functional teams remotely.

What are the key skills and qualifications needed to thrive as a remote applied scientist machine learning?

To thrive as a Remote Applied Scientist in Machine Learning, you need a strong background in mathematics, statistics, and computer science, often supported by an advanced degree and experience in ML algorithm development. Familiarity with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and tools for data processing and cloud computing is essential. Exceptional problem-solving ability, communication, and self-motivation are key soft skills for collaborating remotely and driving projects forward. These skills ensure you can independently design, implement, and communicate impactful machine learning solutions in a distributed work environment.

What can I expect in terms of collaboration and communication when working as a remote applied scientist machine learning?

As a Remote Applied Scientist in Machine Learning, you will frequently collaborate with cross-functional teams, including data engineers, product managers, and software developers. Communication typically takes place via video calls, chat platforms, and shared documentation, so strong written and verbal communication skills are essential. You may participate in regular virtual stand-ups, sprint planning, and code reviews to align on project goals and share progress. Remote work environments emphasize proactive communication and self-management to ensure seamless teamwork and project delivery.

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

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

Infographic showing various Remote Applied Scientist Machine Learning job openings in California as of June 2026, with employment types broken down into 72% Full Time, and 28% Part Time. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.

Machine Learning Engineer

San Francisco, CA โ€ข Remote

Swish Analytics
Spectator Sportsย โ€ขย 1 - 10 employees

$160K/yr

Full-time

Re-posted 28 days ago


Key responsibilities

  • Design, prototype, implement, evaluate, and optimize systems to generate sports datasets and predictions with high accuracy and low latency.

  • Build, test, deploy, and maintain production systems related to sports analytics and modeling.

  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization, and scaling of workloads using Kubernetes, CI/CD, automation tools, and scripting languages.


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.