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Machine Learning Engineer Python Jobs in California

Skild AI

Machine Learning Engineer

San Mateo, CA

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing ... Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch ...

Velo3D

Machine Learning Engineer

Fremont, CA

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Hand off validated Python prototypes for production hardening, provide clear specifications and ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Hand off validated Python prototypes for production hardening, provide clear specifications and ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Hand off validated Python prototypes for production hardening, provide clear specifications and ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to contribute to the development of tools and ... Python, PyTorch or Jax, and distributed systems. • Experience deploying and maintaining ML ...

Apple

Machine Learning Engineer (Search)

Cupertino, CA · On-site

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution ... Java, C++, Python Knowledge and experience with one of Tensorflow/Pytorch/Jax frameworks. Excellent ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this ... Strong Python and SQL skills, with experience working with large-scale datasets * Experience ...

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Use programming languages like Python, Go, Scala, or Java Basic Qualifications: * Bachelor's Degree

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Use programming languages like Python, Go, Scala, or Java Basic Qualifications: * Bachelor's Degree

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Use programming languages like Python, Go, Scala, or Java Basic Qualifications: * Bachelor's Degree

Apple

Machine Learning Engineer

San Diego, CA · On-site

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next ... Python for algorithm development and optimization Demonstrated ability to rapidly prototype ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI ... Proficient in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, with hands-on ...

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Machine Learning Engineer Python information

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is the salary of machine learning engineer in Python?

The average salary for a machine learning engineer proficient in Python typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those requiring specialized skills in deep learning or data engineering may offer higher compensation.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Python, and why are they important?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What is the difference between Machine Learning Engineer Python vs Data Scientist?

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What engineer makes $500,000 a year?

A senior or lead machine learning engineer with extensive experience, advanced skills in Python, deep learning, and data modeling can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Such roles often require advanced degrees, certifications, and a strong track record of successful projects.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI director, often involving advanced skills in Python, deep learning, and data science. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in competitive industries like tech or finance.

Is Python enough for ML engineers?

Python is a fundamental programming language for machine learning engineers due to its extensive libraries like TensorFlow, PyTorch, and scikit-learn. However, proficiency in data manipulation, algorithms, and understanding of machine learning concepts, along with knowledge of tools like SQL and cloud platforms, are also important for success in the role.
What are popular job titles related to Machine Learning Engineer Python jobs in California? For Machine Learning Engineer Python jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in California look for? The top searched job categories for Machine Learning Engineer Python jobs in California are:
What cities in California are hiring for Machine Learning Engineer Python jobs? Cities in California with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you

Machine Learning Engineer

Skild AI

San Mateo, CA

Other

Re-posted 7 days ago

Job description

Position Overview

We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.

Responsibilities
  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  • Design and conduct experiments to train RL models and conduct real-world tests.
  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  • Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  • Strong background in algorithms, data structures, and software engineering principles.
  • Experience with physics simulation engines and tools for training RL.
  • Deep understanding of state-of-the-art machine learning techniques and models.
  • Extensive industry experience with reinforcement learning and robotic systems.

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