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Contract Google Machine Learning Engineer Jobs in Santa Rosa, CA

Ema

Software Engineer, Machine Learning

Bodega Bay, CA · On-site

$160K - $220K/yr

Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers ... You love utilizing machine learning techniques to push the boundaries of what is possible within ...

Apple

Machine Learning FEA Engineer

Bodega Bay, CA

$142K - $263K/yr

We are committed to pushing the boundaries of innovation and engineering excellence in product designs through machine learning and FEA simulations. We truly believe in the power of predictive ...

Apple

Machine Learning FEA Engineer

Bodega Bay, CA

$142K - $263K/yr

We are committed to pushing the boundaries of innovation and engineering excellence in product designs through machine learning and FEA simulations. We truly believe in the power of predictive ...

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How much do contract google machine learning engineer jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for contract google machine learning engineer in Santa Rosa, CA is $53.50, according to ZipRecruiter salary data. Most workers in this role earn between $44.95 and $55.43 per hour, depending on experience, location, and employer.

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Contract Google Machine Learning Engineer jobs near you

Machine Learning Engineer

Bodega Bay, CA • Remote

Kanak Elite Services Inc
Software Development • 51 - 200 employees
Learn more about Kanak Elite Services Incexternal

Contractor

Re-posted 12 days ago

Job description

Hello There,

My name is Himanshu Sharma, and I serve as the Recruitment Lead at Kanak-IT INC. I am reaching out to share an excellent career opportunity for the role of Machine Learning Engineer with our esteemed client. If you are interested then please share your updated resume at Himanshu01@kanakits.com .

Job Description

Title:  Machine Learning Engineer
Location:  South San Francisco, CA  - hybrid role in Bay Arear
Position Type:  Contract 
 

Note: DO NOT SEND WITHOUT MOLECULAR EXPERIENCE, 

Work on ML workflows for molecular property prediction & generative modeling to accelerate drug discovery. 3–5 yrs esp. or PhD with publications in molecular design.

Must have Masters or PH.D. Must have experience in working environment or while getting Master’s or no to very little work exp with PH.D  in Molecular design. Need to have portfolio of their work or be published. Find me Machine Learning with Molecular experience in Bay Area or someone who will relocate as last resort. 
MindSource is looking for a Machine Learning Engineer to join our client's team in South San Francisco, CA.  They will be developing and deploying advanced computational methods for molecular design.  This is a 12-month hybrid contract.  

About the Role

  • Build pipelines for probabilistic molecular property prediction and Bayesian acquisition to power active learning–driven drug discovery.
  • Engineer workflows for molecular generative modeling and other innovative design approaches.
  • Collaborate with machine learning scientists, engineers, computational chemists, and biologists.
  • Partner with therapeutic development teams to analyze existing molecules and design new candidates.
  • Contribute to ongoing initiatives while driving new research directions.

Qualifications

  • PhD in Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics, or related quantitative field — OR MS + 3+ years of relevant industry experience.
  • Demonstrated expertise in production-ready ML workflows (e.g., PyTorch + Lightning + Weights & Biases).
  • Strong track record of achievement (e.g., high-impact first-author publication or equivalent).
  • Excellent written, visual, and verbal communication skills.

Preferred Experience

  • Knowledge of physical modeling (e.g., molecular dynamics) and cheminformatics (e.g., RDKit).
  • Background in molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, or statistical methods.
  • Hands-on experience with Python, PyTorch, Torch Geometric, PyTorch Lightning, RDKit, and BoTorch.
  • Public portfolio of computational projects (e.g., GitHub).