1

Machine Learning Engineer Python Jobs in California

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or ... Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas) * Broad familiarity with ...

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or ... Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas) * Broad familiarity with ...

Strong programming skills in Python and Scala required. Experience in other programming languages (eg. Java, R, Haskell) a plus. * Solid knowledge of machine learning tools (eg. scikit-learn ...

Strong programming skills in Python and Scala required. Experience in other programming languages (eg. Java, R, Haskell) a plus. * Solid knowledge of machine learning tools (eg. scikit-learn ...

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... in Python, OpenCV, SQL, and one or more deep learning frameworks (PyTorch, Tensorflow, etc ...

Minimum Qualifications Software engineering skills and proficiency in Python Experience with ... machine learning, computer science, computer engineering or related fields.

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only ... Minimum Requirements In-depth knowledge of Python for high-performance, data-intensive applications.

Software engineering skills and proficiency in Python. Experience with PyTorch. BA/BS degree in computer vision, computer graphics, machine learning or related field. Preferred Qualifications MS or ...

Proficiency in one or more object-oriented programming languages such as Python, Java, or C++, with hands-on experience building distributed systems. Experience building large-scale machine learning ...

As a Senior Machine Learning Engineer, you will design, build, and scale advanced software systems ... • Proficiency in Python, OpenCV, SQL, and one or more deep learning frameworks (PyTorch ...

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ... Write clean, well-documented, and production-quality Python code. * Communicate findings, results ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ... Write clean, well-documented, and production-quality Python code. * Communicate findings, results ...

next page

Showing results 1-20

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 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

Happy Elements

San Francisco, CA

Full-time

Re-posted 7 days ago


Job description

Machine Learning Engineer
Full-time
Responsibilities
  • Build, maintain, and improve efficient and reliable data mining and machine learning models.
  • Design, implement and tune machine learning models, and provide performance feedback.
  • Work closely with data engineers to adapt and improve data pipelines for production models.
  • Work closely with software engineers in putting models into production (interface, SLA, scalability).Qualifications
  • Strong academic background required. MS in Computer Science or Machine Learning with 2+ years of industry experience or PhD in related field with 1+ years of industry experience required.
  • Expert in Python, and computation graph toolkits (e.g., Scikit-learn, Tensorflow). Solid experience with Python packages such as Numpy, Panda, and Scikit-learn.
  • Expert/Master in common families of machine learning models, feature engineering, feature selection techniques, and tuning of machine learning models.
  • Master with SQL or other relational database.
  • Master in building and productionizing end-to-end machine learning systems.
  • Knowledge and experience in cloud computing is a plus.
  • Extensive data modeling and data architecture skills.
  • Advanced math skills (linear algebra, Bayesian statistics, group theory).
  • Ability to consistently exercise independent discretion and judgment on significant matters.
  • Strong analytical, problem-solving and communication skills.
  • Ability to work in a team environment