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Contract Apple Machine Learning Engineer Jobs in Santa Rosa, CA

Apple

Machine Learning FEA Engineer

Bodega Bay, CA

$142K - $263K/yr

D. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline ... Apple employees also have the opportunity to become an Apple shareholder through participation in ...

Apple

Machine Learning FEA Engineer

Bodega Bay, CA

$142K - $263K/yr

D. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline ... Apple employees also have the opportunity to become an Apple shareholder through participation in ...

Ema

Software Engineer, Machine Learning

Bodega Bay, CA · On-site

$160K - $220K/yr

Who You Are We're looking for innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge ...

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All JobsContract Apple Machine Learning Engineer JobsContract Apple Machine Learning Engineer Jobs in Santa Rosa, CA

Contract Apple Machine Learning Engineer information

See Santa Rosa, CA salary details

$34.4K

$140.8K

$211.6K

How much do contract apple machine learning engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for contract apple machine learning engineer in Santa Rosa, CA is $140,787.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $169,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a contract Apple machine learning engineer?

To thrive as a Contract Apple Machine Learning Engineer, you need a strong background in computer science, mathematics, and deep learning, typically with a relevant degree and experience in building ML models. Proficiency with Python, TensorFlow or PyTorch, Apple's Core ML framework, and version control systems is commonly required. Strong problem-solving skills, collaboration, and effective communication help you navigate project requirements and work with cross-functional teams. These skills and experiences are crucial for delivering high-quality, scalable machine learning solutions that align with Apple's standards and rapidly evolving technology needs.

What are the common challenges faced by contract Apple machine learning engineers when integrating ML models into Apple’s ecosystem?

Contract Apple Machine Learning Engineers often encounter challenges such as ensuring seamless integration of machine learning models with Apple’s proprietary platforms like iOS, macOS, or Core ML. Adapting to Apple’s strict security, privacy standards, and performance requirements is essential, as is optimizing models for real-time performance on Apple devices. Collaborating effectively with cross-functional teams—such as software developers, designers, and QA engineers—is crucial to deliver scalable and user-friendly ML features within project timelines.

What is a contract Apple machine learning engineer?

Contract Apple Machine Learning Engineers are professionals hired on a temporary or project basis to develop and implement machine learning models and algorithms specifically for Apple’s products and platforms. They typically work on tasks such as optimizing machine learning workflows for iOS, macOS, or other Apple technologies, and may collaborate closely with Apple’s in-house teams. Their responsibilities can include data preprocessing, model training, evaluation, and integration into Apple’s ecosystem. These engineers are expected to have expertise in machine learning frameworks, programming languages like Python or Swift, and a strong understanding of Apple’s development tools. Contract roles often provide flexibility but may require quick adaptation to Apple’s proprietary systems and high standards.
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Contract Apple Machine Learning Engineer jobs near you

Machine Learning Engineer

Kanak Elite Services Inc

Bodega Bay, CA • Remote

Contractor

Re-posted 23 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).