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Python Ml Developer Jobs in San Marcos, CA (NOW HIRING)

TEEMA

Computer Vision Engineer

San Diego, CA · On-site

$125K - $130K/yr

Strong Python skills with OpenCV or similar libraries * Solid understanding of camera geometry ... Azure ML DevOps pipelines for automated training and deployment

Qualcomm

Customer Engineer - AI / ML

San Diego, CA · On-site

Engineering Group, Engineering Group > Software Applications Engineering General Summary: Qualcomm ... C/C++ and Python proficiency. * Experience developing, training, or deploying models using an ML ...

Apple

DevOps/Backend Software Engineer

San Diego, CA

$142K - $263K/yr

We are the Product Integrity AI/ML team, and we build and deliver software supporting the ... Demonstrated ability to write applications in a high-level programming language like Python, Ruby ...

Apple

DevOps/Backend Software Engineer

San Diego, CA · On-site

$56 - $76.75/hr

We are the Product Integrity AI/ML team, and we build and deliver software supporting the ... Demonstrated ability to write applications in a high-level programming language like Python, Ruby ...

PlayStation Global

AI Engineer

San Diego, CA

Role overview Within D2C Data Science, the D2C ML Engineering team is seeking an AI Software ... Develop scalable APIs, microservices, and event-driven workflows in Python or Java, with attention ...

Qualcomm

Senior Engineer - Machine Learning

San Diego, CA · On-site

$110K - $152K/yr

We are seeking a highly skilled Core ML Engineer to design, develop, and optimize machine learning ... Preferred Qualifications Strong programming skills in Python and at least one systems language (C ...

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All JobsPython Ml Developer JobsPython Ml Developer Jobs in San Marcos, CA

Python Ml Developer information

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How much do python ml developer jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for python ml developer in San Marcos, CA is $59.73, according to ZipRecruiter salary data. Most workers in this role earn between $49.23 and $67.84 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
Technical Lead Manager, Prediction, ML Evaluation

Technical Lead Manager, Prediction, ML Evaluation

Waymo

San Diego, CA

Other

Posted 18 days ago

Job description

The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver's behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks. These models enable the autonomous vehicle to navigate complex environments safely and efficiently. 

We have an exciting opportunity for a Staff Technical Lead Manager to lead our ML Evaluation team. In this role, you will define the strategic vision for our evaluation platforms, scaling the critical infrastructure and metrics required, and partner closely with the modeling teams to rigorously validate our next-generation deep neural networks and accelerate ML developer velocity across PrePlan.

You will:

  • Influence the strategic direction of foundational infrastructure and evaluation platforms to robustly support next-generation ML model evaluation use cases
  • Collaborate cross-functionally with ML engineers, data scientists, and infrastructure teams to identify, define, and surface critical signals on model, component, and system-level performance
  • Leverage and scale evaluation and infrastructure platforms to significantly enhance the ML developer experience, enabling faster iteration through earlier, more reliable, and trusted model evaluation
  • Manage and mentor a focused team of engineers, aligning their career growth and aspirations with critical organizational needs
  • Drive best practices and leverage deep technical awareness of the Alphabet ML stack (e.g., TensorFlow, JAX, Flax, Apache Beam) to optimize evaluation workflows
  • Stay at the forefront of emerging technologies, industry trends, and research in ML evaluation methodologies and advanced metrics design

You have: 

  • M.S. in Computer Science, Mathematics, or equivalent industry experience in Robotics or large-scale ML systems with critical evaluation needs
  • 5+ years of experience building and maintaining large-scale distributed infrastructure, ML inference systems, or evaluation platforms, including 3+ years of engineering management experience
  • Strong coding and testing proficiency, specifically in Python and C++
  • Strong foundational knowledge of model evaluation and core data science principles (e.g., confidence intervals, outlier identification, curve fitting, and causality analysis)
  • Familiarity with large-scale ML deployment and orchestration tools (e.g., TF Serving, TorchServe, Kubeflow, SageMaker Pipelines, or Vertex AI Pipelines)
  • Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow

We prefer:

  • Experience developing and maintaining evaluation pipelines for ML models
  • Experience deploying and supporting machine learning models for computer vision, natural language processing, robotics/motion planning, or recommendation systems
  • Experience supporting a small team of MLEs developing high-capacity, production-grade models and components
  • Strong understanding of metrics computation and regression detection at scale

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