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Machine Learning Flexible Hours Jobs in California

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About the role: We're looking for an early career Machine Learning Engineer to join our team. In ... Generous PTO and flexible hybrid work model * 401(k) with employer contribution * Professional ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

By integrating advanced metal forming, robotics, and automated production inside a flexible factory ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

By integrating advanced metal forming, robotics, and automated production inside a flexible factory ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

General Atomics

Machine Learning Engineer

Poway, CA · On-site

We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and ... Able to work extended hours as required. * Customer focused, must be able to work on a self ...

Hadrian Automation

Machine Learning Engineer

Torrance, CA · On-site

$160K - $300K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Flexible vacation policy * Equity ITAR Requirements To conform to U.S. Government space technology ...

Liquid XR

Machine Learning Engineer

Los Angeles, CA · On-site +1

The Role We are seeking a Machine Learning Engineer to develop advanced models for extracting ... Compensation, Benefits, Hours This is a full-time employee position, working remotely or in our Los ...

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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 are popular job titles related to Machine Learning Flexible Hours jobs in California?

For Machine Learning Flexible Hours jobs in California, the most frequently searched job titles are:

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:

Machine Learning Flexible Hours jobs near you
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.

Machine Learning Engineer

Tapestry

Mountain View, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 days ago

Tapestry Inc. rating

8.2

Company rating: 8.2 out of 10

Based on 36 frontline employees who took The Breakroom Quiz

1st of 104 rated fashion retailers

Job description

About Tapestry
Tapestry is a group within Google working to build the AI-powered electric grid. We are tackling one of the world's most important infrastructure challenges: helping the energy system become more visible, understandable, reliable, affordable, abundant, and clean.
Originally born at X, Alphabet's moonshot factory, Tapestry brings together experts in energy, AI, software engineering, and products to build tools that help the electricity ecosystem plan smarter, move faster, and operate more efficiently.
This is a global effort. Tapestry supports partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy future.
Joining Tapestry means doing high-impact work with a multidisciplinary team tackling a problem that matters at global scale. Learn more about our team and our mission here.
About the role:
We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex challenges that face today's electric grid. You will work closely with other Machine Learning Engineers, Data Scientists and Software Engineers across diverse ML domains spanning multimodal machine learning, information retrieval, natural language processing and agentic AI.
How you will make 10x impact:
  • Train, and deploy machine learning models in production environments.
  • Work with senior team members to develop enterprise quality ML systems, spanning multiple ML domains
  • Operationalize ML model training at serving at enterprise scale
  • Stay abreast of the latest advancements in machine learning

What you should have:
  • Master's Degree/Bachelor's Degree in Machine Learning, Computer Science, Statistics or related field
  • 3+ years of experience in machine learning model development and engineering.
  • Expertise in one or more of the following areas: multimodal machine learning NLP or agentic AI, planning, control and reinforcement learning
  • Strong programming skills in Python and experience with ML frameworks like PyTorch or TensorFlow.
  • Experience with building and deploying ML systems at scale, OR a proven ability to perform applied ML research and develop the state of the art in an academic setting

It'd be great if you also had these:
  • PhD in Machine Learning, Computer Science, Statistics, or a related field
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • A strong portfolio of projects demonstrating ML expertise.

Our values
  • Take charge: We take initiative and own outcomes that move the mission forward.
  • Transform with purpose: We build solutions that solve real problems and create meaningful impact.
  • Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
  • Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
  • Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What we offer
A culture that supports growth, ownership, and meaningful impact, along with:
  • Competitive salary and equity
  • Medical, dental, and vision coverage
  • Generous PTO and flexible hybrid work model
  • 401(k) with employer contribution
  • Professional development
  • The ability to work on important real-world problems within an Alphabet-backed environment

The US base salary range for this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.

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