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Flexible Remote Machine Learning Engineer Jobs in California

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Employee divides their time between in-office and remote work. Access to an office location is ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ... Flexible Spending Account (FSA) - set aside pre-tax dollars for eligible healthcare expenses. Watch ...

Absurd Ventures

Machine Learning Engineer

Santa Monica, CA · On-site +1

$165K - $200K/yr

We are seeking a Senior Machine Learning Engineer to help shape the future of content systems and real-time gameplay using cutting-edge machine learning techniques. As Senior Machine Learning ...

Reddit

Machine Learning Engineer

San Francisco, CA · On-site +1

$187K - $260K/yr

Train, evaluate, and deploy sophisticated machine learning models to improve experiences for ... Flexible Vacation & Paid Volunteer Time Off * Generous Paid Parental Leave Submit a resume with ...

Capital One

Sr. Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Match Group

Machine Learning Engineer II

Palo Alto, CA · On-site +1

$114K - $156K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Match Group

Machine Learning Engineer II

Palo Alto, CA · On-site +1

$114K - $156K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Omnissa

Staff Machine Learning Engineer

Mountain View, CA · On-site +1

$162K - $342K/yr

Omnissa is the first AI-driven digital work platform, built to support flexible, secure, work-fro ... As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems ...

Elicit

Machine Learning Engineer

Oakland, CA · On-site +1

... role As a Machine Learning Engineer at Elicit, you'll build products and workflows that help ... Flexible work environment - work from our office in Oakland or remotely as long as you can travel ...

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All JobsFlexible Remote Machine Learning Engineer JobsFlexible Remote Machine Learning Engineer Jobs in California

Flexible Remote Machine Learning Engineer information

How does a flexible remote work arrangement impact collaboration and project delivery for Machine Learning Engineers?

In a flexible remote setting, Machine Learning Engineers often rely on digital collaboration tools to communicate with team members and manage projects. This setup allows for asynchronous work, enabling engineers to focus deeply on model development and data analysis without constant interruptions. However, it also means proactively scheduling check-ins and maintaining clear documentation are crucial to ensure alignment across distributed teams. While remote work offers autonomy and work-life balance, successful engineers build strong communication habits to keep projects on track and foster effective collaboration with data scientists, product managers, and software engineers.

What is a Flexible Remote Machine Learning Engineer?

A Flexible Remote Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models while working remotely, often with flexible hours. They use programming, data analysis, and statistical skills to create algorithms that solve real-world problems, collaborating with teams through digital communication tools. This role allows for a better work-life balance and can be performed from anywhere with a reliable internet connection. Flexible remote positions are especially popular in the tech industry, where project-based work and results matter more than strict office hours.

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

AspectFlexible Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis-focused
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, research
Common Search IntentRoles involving ML model development and deploymentRoles focused on data analysis and insights

The main difference is that a Flexible Remote Machine Learning Engineer primarily develops and deploys machine learning models, while a Data Scientist focuses on analyzing data to generate insights. Both roles often require similar educational backgrounds and can be remote, but their core responsibilities differ in application and focus.

What are the key skills and qualifications needed to thrive as a Flexible Remote Machine Learning Engineer, and why are they important?

To thrive as a Flexible Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data pipelines are essential, and certifications in machine learning or cloud technologies can be advantageous. Excellent communication, self-motivation, and time management skills help you collaborate effectively and stay productive in a remote, flexible work environment. These skills ensure you can independently deliver high-quality ML solutions, maintain clear team communication, and adapt to evolving project requirements.
What are the most commonly searched types of Remote Machine Learning Engineer jobs in California? The most popular types of Remote Machine Learning Engineer jobs in California are:
What are popular job titles related to Flexible Remote Machine Learning Engineer jobs in California? For Flexible Remote Machine Learning Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Flexible Remote Machine Learning Engineer jobs in California look for? The top searched job categories for Flexible Remote Machine Learning Engineer jobs in California are:
What cities in California are hiring for Flexible Remote Machine Learning Engineer jobs? Cities in California with the most Flexible Remote Machine Learning Engineer job openings:
Flexible Remote Machine Learning Engineer jobs near you
Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Posted 27 days ago

Job description

Our client is a leader in healthcare innovation, seamlessly integrating pharmaceutical development, diagnostic solutions, and advanced technology and data capabilities.
Title: Machine Learning Engineer (Contract)
Pay rate: $55-73/hr+ (Depends on experience)
Location: Remote in the US or Canada, or onsite in SSF. Must be available during PST hours.
Duration: Through Dec. 2026 (Likely to get extended)
Overview:
Seeking a Machine Learning Bioinformatics Engineer to develop and deploy advanced ML solutions supporting pharmaceutical R&D. This role focuses on analyzing large-scale, multimodal clinicogenomic datasets (genomic, transcriptomic, clinical, and real-world data) to drive insights into disease biology, patient stratification, and treatment response. Ideal candidates are strong in both machine learning and bioinformatics, with a passion for translating complex data into impactful discoveries.
Key Responsibilities:
  • Build and deploy scalable, production-ready machine learning models
  • Process and analyze genomic and transcriptomic data using bioinformatics pipelines
  • Prepare high-quality, normalized biological datasets for downstream analysis
  • Train large-scale models using frameworks like PyTorch Lightning and Hugging Face
  • Develop cloud-based ML solutions (AWS/GCP) with a focus on scalability and reproducibility
  • Collaborate with cross-functional teams to uncover biomarkers and therapeutic targets
  • Provide technical input and guidance on ML system design and implementation

Qualifications:
  • PhD with 0-2 years of relevant work experience, or MS with 3-5 years of relevant work experience, or BS with 4-7 years of relevant work experience.
  • Proficient programming skills: Strong Python programming skills with extensive experience in ML and data libraries (e.g., NumPy, pandas, PyTorch).
  • Deep ML expertise: Excellent knowledge of modern machine learning methods and development best practices, including training strategies, model validation, performance visualization, and experimental design.
  • Deep bioinformatic expertise: Proficient knowledge of bioinformatic processing pipelines for genomic and transcriptomic variables.
  • Strong knowledge of computational oncology, cancer genomics and analysis of clinicogenomics datasets.
  • Must be authorized to work in the United States

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