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Machine Learning Engineer Python Jobs in Victorville, CA

Esri

Sr. Generative AI Software Developer

Redlands, CA

$54.75 - $72.50/hr

... Engineer to help advance the next generation of geospatial data quality capabilities across the ... Develop Python-based machine learning components that enhance how users assess, understand, and ...

Esri

Sr. Generative AI Software Developer

Redlands, CA · On-site

$123K - $202K/yr

... Engineer to help advance the next generation of geospatial data quality capabilities across the ... Develop Python-based machine learning components that enhance how users assess, understand, and ...

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Machine Learning Engineer Python information

See Victorville, CA salary details

$24.2K

$147.5K

$213.4K

How much do machine learning engineer python jobs pay per year?

As of Aug 26, 2026, the average yearly pay for machine learning engineer python in Victorville, CA is $147,526.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,500.00 and $173,400.00 per year, depending on experience, location, and employer.

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 are the key skills and qualifications needed to thrive as a machine learning engineer python?

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 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 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 are popular job titles related to Machine Learning Engineer Python jobs in Victorville, CA?

For Machine Learning Engineer Python jobs in Victorville, CA, the most frequently searched job titles are:

What cities near Victorville, CA are hiring for Machine Learning Engineer Python jobs?

Cities near Victorville, CA with the most Machine Learning Engineer Python job openings:

Machine Learning Engineer Python jobs near you

Staff Machine Learning Engineer (Mountain View)

Victorville, CA • On-site

Intuit Inc.
Computer and Electronic Product Manufacturing • 5 - 10K employees

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

108th of 246 rated software companies

People enjoy working here

Good employer

Recommended by students

Learn more about Intuit Inc.external

$197K - $266K/yr

Full-time

Posted 8 days ago

Job description

Overview

Come join Intuit as a Staff Machine Learning Engineer!

In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics.

Responsibilities
  • Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
  • Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
  • Partner with data scientists to understand, implement, refine and design machine learning and other algorithms.
  • Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
  • Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
  • Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.

Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

Qualifications
  • BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.
  • 6+ years of experience
  • Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
  • Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
  • Understand machine learning principles (training, validation, etc.)
  • Knowledge of data query and data processing tools (i.e. SQL)
  • Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
  • Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
  • Experience deploying highly scalable software supporting millions or more users
  • Experience with GPU acceleration (i.e. CUDA and cuDNN)
  • Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
  • Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs. The expected base pay range for this position is: Bay Area, CA: $197,000 - $266,500.

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