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Machine Learning Intern Remote Jobs in Walnut Creek, CA

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Canals

Machine Learning Engineer

San Francisco, CA · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

6sense

Sr. Machine Learning Engineer

San Francisco, CA · Remote

$200K - $260K/yr

The Opportunity We're hiring a Senior Machine Learning Engineer to join our AI team, reporting ... remote Notice of Collection and Use of Personal Information for California Residents: California ...

New

EvenUp

Staff Machine Learning Engineer

San Francisco, CA · Remote

$212K - $301K/yr

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how ... Open to remote candidates or 3 days a week hybrid from our Toronto or San Francisco hubs. Benefits ...

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All JobsMachine Learning Intern JobsMachine Learning Intern Remote JobsMachine Learning Intern Remote Jobs in Walnut Creek, CA

Machine Learning Intern Remote information

See Walnut Creek, CA salary details

$28.2K

$47.2K

$97.5K

How much do machine learning intern remote jobs pay per year?

As of Aug 23, 2026, the average yearly pay for machine learning intern remote in Walnut Creek, CA is $47,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,000.00 and $50,900.00 per year, depending on experience, location, and employer.

What does a machine learning intern do when working remotely?

A remote Machine Learning Intern typically assists with data collection, cleaning, and analysis, helps develop and test machine learning models, and collaborates with team members through virtual meetings and code repositories. They may also research new algorithms, document their work, and present findings to their supervisors. The role provides hands-on experience in applying machine learning concepts to real-world problems while working from a remote location.

What are the key skills and qualifications needed to thrive as a machine learning intern?

To thrive as a Machine Learning Intern (Remote), a solid understanding of programming (especially Python), statistics, and foundational machine learning concepts—often supported by coursework or a relevant degree—is essential. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and version control systems (e.g., Git) is typically required, along with experience using data analysis libraries. Strong problem-solving skills, initiative, and clear communication are valuable soft skills for collaborating virtually and adapting to remote work environments. These skills and qualities enable effective contribution to projects, smooth team communication, and successful learning in a dynamic, distributed setting.

What types of projects can I expect to work on as a machine learning intern?

As a remote Machine Learning Intern, you can typically expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of models into production environments. You may also help with tasks like feature engineering, exploratory data analysis, and preparing technical documentation. Collaboration is usually done through virtual meetings and code repositories, and you'll often work closely with data scientists, engineers, and mentors who provide guidance and feedback. This hands-on experience helps you gain exposure to industry-standard tools and workflows, preparing you for more advanced roles in the future.

What are popular job titles related to Machine Learning Intern Remote jobs in Walnut Creek, CA?

For Machine Learning Intern Remote jobs in Walnut Creek, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Intern Remote jobs in Walnut Creek, CA look for?

The top searched job categories for Machine Learning Intern Remote jobs in Walnut Creek, CA are:

What cities near Walnut Creek, CA are hiring for Machine Learning Intern Remote jobs?

Cities near Walnut Creek, CA with the most Machine Learning Intern Remote job openings:

Machine Learning Intern Remote jobs near you
Infographic showing various Machine Learning Intern Remote job openings in Walnut Creek, CA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $47,158 per year, or $22.7 per hour.

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Re-posted 25 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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