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Python Ml Developer Jobs in Newark, CA (NOW HIRING)

Clera

Senior AI/ML Engineer

San Francisco, CA · On-site

$123K - $169K/yr

They are looking for a Senior AI/ML Engineer to own model training pipelines, evaluation systems ... Strong Python and PyTorch (or JAX) fundamentals * Experience with distributed training, GPU ...

Mach9 Robotics Inc

ML Engineer

San Francisco, CA · On-site

$180K - $300K/yr

The role At Mach9, ML Engineers build the perception models at the core of our AI-enabled CAD ... Proficient with Python and a production-quality ML library like PyTorch, JAX, or TensorFlow. Bonus ...

Albert Invent

Staff ML Ops Engineer

Oakland, CA · On-site

We are seeking a highly motivated and talented individual with deep expertise in Python backend development, Kubernetes, and distributed systems. You'll be embedded with ML engineers and researchers ...

Waymo

Software Engineer, ML Tools

Mountain View, CA · Hybrid

Developer productivity, scale, and efficiency are core tenets. In this hybrid role, you will report ... Proficiency developing large-scale jobs and backend servers in C++ or Python * Proficiency ...

Dexmate

Developer Advocate Engineer

Santa Clara, CA · On-site

Required : • You write Python fluently and have real ML engineering experience -- model training, fine-tuning, inference optimization, or ML infrastructure. You've shipped models that ran in ...

Career Renew

Senior ML Engineer

San Francisco, CA · Remote

$180K - $240K/yr

... ML team building production-grade AI voice agents used by enterprise customers like AAA and ... You're an applied AI engineer who thrives in startup environments, writes clean Python, and can ...

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All JobsPython Ml Developer JobsPython Ml Developer Jobs in Newark, CA

Python Ml Developer information

See Newark, CA salary details

$14

$65

$97

How much do python ml developer jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for python ml developer in Newark, CA is $65.93, according to ZipRecruiter salary data. Most workers in this role earn between $54.33 and $74.90 per hour, depending on experience, location, and employer.

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI and machine learning systems. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and interpreting complex models, making complete replacement unlikely in the near term. MLEs need skills in programming, data analysis, and model deployment to adapt to evolving AI technologies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. Such roles usually involve leadership, strategic planning, and extensive experience in the field.

Which 3 jobs will survive AI?

For a Python ML Developer, roles that require complex problem-solving, creativity, and human judgment are likely to persist, such as AI research scientist, data scientist, and software engineer. These jobs involve designing, interpreting, and improving AI models, which currently require advanced expertise, critical thinking, and domain knowledge that AI cannot fully replicate. Continuous learning and staying updated with new tools and techniques are essential for long-term career resilience.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

Can you do ML in Python?

Yes, Python is widely used for machine learning (ML) development due to its extensive libraries such as TensorFlow, scikit-learn, and PyTorch. Python skills are essential for a Python ML developer to build, train, and deploy ML models efficiently in various environments.
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Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in Newark, CA as of July 2026, with employment types broken down into 85% Full Time, 3% Part Time, 1% Temporary, and 11% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $137,139 per year, or $65.9 per hour.

Senior AI/ML Engineer

Clera

San Francisco, CA • On-site

$123K - $169K/yr

Full-time

Re-posted 26 days ago

Job description

About the role
Our client is a well-funded AI startup building production-grade ML infrastructure used by enterprise customers. They are looking for a Senior AI/ML Engineer to own model training pipelines, evaluation systems, and inference serving at scale. Full-time, on-site in San Francisco.

What you will do

  • Design and ship end-to-end ML systems: data pipelines, training, evaluation, deployment

  • Own model performance, latency, and cost trade-offs in production

  • Build evaluation harnesses and offline benchmarks for fast iteration

  • Work directly with product to translate ambiguous goals into measurable model improvements

  • Mentor other engineers on ML best practices and code quality

What we are looking for

  • 4+ years of applied ML engineering in production environments

  • Hands-on experience with LLMs, fine-tuning, RAG, or large-scale recommender systems

  • Strong Python and PyTorch (or JAX) fundamentals

  • Experience with distributed training, GPU optimization, or inference serving

  • Pragmatic about trade-offs between research-grade and ship-grade work

This role is presented by a recruiting partner. Company name shared after an initial conversation.