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Machine Learning Flexible Hours Jobs in California

$40/hr

Monday, May 17, 2027 (40/hours per week max) How You'll Be Rewarded Salary range in the US: $40.00 - $40.00 401(k) participation and match Paid sick leave A unique opportunity to further your ...

New

This flexible approach gives team members the best of both worlds: plenty of focus time along with ... MS / PhD in Computer Science. * 5+ years of industry experience as a machine learning engineer or ...

$40/hr

Monday, May 17, 2027 (40/hours per week max) How You'll Be Rewarded Salary range in the US: $40.00 - $40.00 401(k) participation and match Paid sick leave A unique opportunity to further your ...

New

$40/hr

Monday, May 17, 2027 (40/hours per week max) How You'll Be Rewarded Salary range in the US: $40.00 - $40.00 401(k) participation and match Paid sick leave A unique opportunity to further your ...

New

$40/hr

Monday, May 17, 2027 (40/hours per week max) How You'll Be Rewarded Salary range in the US: $40.00 - $40.00 401(k) participation and match Paid sick leave A unique opportunity to further your ...

New

$40/hr

Monday, May 17, 2027 (40/hours per week max) How You'll Be Rewarded Salary range in the US: $40.00 - $40.00 401(k) participation and match Paid sick leave A unique opportunity to further your ...

New

Showing results 21-40

Machine Learning Flexible Hours information

What does a machine learning job with flexible hours involve?

A machine learning job with flexible hours typically allows professionals to set their own work schedules instead of adhering to a strict 9-to-5 routine. These roles still require expertise in data analysis, algorithm development, and model training, but provide the freedom to work remotely or during non-traditional hours. Flexible arrangements are common in tech companies and startups, enabling better work-life balance while meeting project deadlines and collaborating with teams virtually.

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

To thrive as a Machine Learning Engineer with flexible hours, you need a solid background in computer science, statistics, and mathematics, often supported by a relevant degree and experience in developing machine learning models. Familiarity with technical tools such as Python, TensorFlow, PyTorch, and cloud computing platforms, as well as relevant certifications, is highly valuable. Strong problem-solving skills, self-motivation, and effective communication help you excel when working independently and collaborating remotely. These skills are crucial for delivering impactful solutions, maintaining productivity, and ensuring successful project outcomes in a flexible work environment.

How do flexible hours impact collaboration and project delivery in a machine learning role?

In a Machine Learning role with flexible hours, collaboration is typically managed through asynchronous communication tools and scheduled meetings to ensure team alignment. While this flexibility allows for better work-life balance and can boost productivity, it also requires clear communication and proactive planning to meet project deadlines. Team members often coordinate their core working hours for critical discussions or decision-making, and use shared platforms to track progress and share updates. Adapting to this structure can be a challenge at first, but it often leads to a more autonomous and motivated team environment.

What is the difference between Machine Learning Flexible Hours vs Data Scientist Flexible Hours?

AspectMachine Learning Flexible HoursData Scientist Flexible Hours
CredentialsDegree in Computer Science, Data Science, or related field; knowledge of ML frameworksDegree in Data Science, Statistics, or related field; proficiency in data analysis tools
Work EnvironmentTech companies, research labs, startups; project-basedBusiness analytics, research institutions, tech firms; collaborative teams
Industry UsageAI development, automation, predictive modelingData analysis, reporting, strategic decision-making

Both roles often offer flexible hours, but Machine Learning roles focus on developing algorithms and models, while Data Scientists analyze data to inform decisions. The choice depends on your skills and career goals within the data and AI industry.

What job categories do people searching Machine Learning Flexible Hours jobs in California look for?

The top searched job categories for Machine Learning Flexible Hours jobs in California are:

What cities in California are hiring for Machine Learning Flexible Hours jobs?

Cities in California with the most Machine Learning Flexible Hours job openings:

Infographic showing various Machine Learning Flexible Hours job openings in California as of August 2026, with employment types broken down into 1% As Needed, 64% Full Time, 24% Part Time, 1% Temporary, and 10% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution.

Summer 2027 Intern - Machine Learning Engineering

Workiva

On-site, Remote

$40/hr

Full-time, Temporary, Internship

Retirement

Posted 2 days ago

New


Workiva rating

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

1st of 247 rated software companies


Job description

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the development, deployment, and monitoring of machine learning models. Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management and Analytics organization. This is an excellent opportunity to gain hands-on experience in the machine learning lifecycle.

What You'll Do

  • Participate in discovery, requirements gathering, and prototyping of new tools and libraries
  • Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer
  • Help integrate tools such as LlamaIndex and LlamaParse into existing workflows
  • Assist in building and deploying AI Agents to automate data processing and analysis tasks
  • Participate in code reviews
  • Implement and update tests (unit, integration)
  • Track tasks and complete status updates using internal tools
  • Work in an Agile development methodology alongside your teammates

What You'll Need

Minimum Qualifications

  • Currently pursuing a bachelor’s degree or higher in Statistics, Mathematics, Computer Science, Physics, Electrical Engineering, or related field of study
  • Possess solid programming skills
  • Basic experience with source control systems such as Git

Preferred Qualifications

  • Work effectively within a geographically distributed team
  • Demonstrate strong communication and organizational skills
  • Familiarity with the data science lifecycle and basic machine learning concepts
  • Experience with containerization tools such as Docker and Kubernetes
  • Knowledge of cloud platforms such as AWS
  • Proficiency with Python and/or Go
  • Familiarity with REST APIs

Travel Requirements & Working Conditions

  • Minimal travel
  • Reliable internet access for any period of time working remotely, not in a Workiva office

Location: This internship is primarily a remote opportunity. However, if you are located near one of our office hubs, you are welcome to work in a hybrid capacity and utilize our office spaces. Check out our article on Workplace Flexibility to learn more.

When can you expect to hear back?

We are committed to attending all career fairs and recruitment events before closing our positions. That means, this position might be open without updates for a few weeks to give us time to connect with all potential candidates before wrapping up the recruitment season. Check out our tentative timeline below to see when you can expect to hear from us!

Postings close: September 27, 2026

Engineering postings close: October 2, 2026

Interviews: Early to mid October

Offers: Late October

2027 Start Dates:

This position has opportunities to start in the Spring or Summer. Please see our start dates below and let us know your availability in your application.

  • Spring 2027 Internships: Monday, January 4, 2027 (15-20 hours per week max)
  • Summer 2027 Internships: Monday, May 17, 2027 (40/hours per week max)

How You’ll Be Rewarded

Salary range in the US: $40.00 - $40.00 401(k) participation and match

Paid sick leave

A unique opportunity to further your learning experience through additional internship seasons

Why Join Workiva

Workiva is the platform designed to bring confidence, control, and a competitive edge to the world’s most complex organizations. Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation-ensuring data is trusted, traceable, and ready to act on. With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world.

At Workiva, you’ll bring technology to market that executives, boards, and regulators depend on. The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny. If you’re energized by meaningful challenges, inspired by collaborative teams, and motivated to help organizations turn uncertainty into advantage, we’d love to meet you.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email earlycareer@workiva.com .

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.


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