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Machine Learning Engineer Python Jobs in Glendale, CA

Magnopus

Machine Learning Engineer II

Los Angeles, CA · On-site

$100K - $150K/yr

Magnopus is looking for a Machine Learning Engineer who thrives at the intersection of product innovation, real-time systems, and creative collaboration. In this role, you won't just build models ...

Magnopus

Machine Learning Engineer II

Los Angeles, CA · On-site

$100K - $150K/yr

Magnopus is looking for a Machine Learning Engineer who thrives at the intersection of product innovation, real-time systems, and creative collaboration. In this role, you won't just build models ...

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Machine Learning Engineer Python information

See Glendale, CA salary details

$24.4K

$148.2K

$214.5K

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

As of Jun 5, 2026, the average yearly pay for machine learning engineer python in Glendale, CA is $148,246.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,000.00 and $174,200.00 per year, depending on experience, location, and employer.

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 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 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 popular job titles related to Machine Learning Engineer Python jobs in Glendale, CA? For Machine Learning Engineer Python jobs in Glendale, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Glendale, CA look for? The top searched job categories for Machine Learning Engineer Python jobs in Glendale, CA are:
What cities near Glendale, CA are hiring for Machine Learning Engineer Python jobs? Cities near Glendale, CA with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you
Infographic showing various Machine Learning Engineer Python job openings in Glendale, CA as of May 2026, with employment types broken down into 42% Full Time, 56% Part Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $148,246 per year, or $71.3 per hour.
Senior Machine Learning Engineer, Reinforcement Learning - Egofold

Senior Machine Learning Engineer, Reinforcement Learning - Egofold

Snail Games USA

Beverly Hills, CA • On-site, Remote

$150K - $185K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Job description

Senior Machine Learning Engineer, Reinforcement Learning - Egofold
About Snail Games USASnail Games strives to create the new high bar for gameplay experience in online gaming. We have been a global developer and publisher of digital entertainment since 2009 and are committed to pushing the boundaries of the industry.
About EgofoldEgofold is an AI initiative within Snail Games focused on intelligent agents, simulation, and AI-driven workflows for interactive products. It operates with startup-style speed and broad ownership, backed by an established game company, and is currently building practical prototypes while shaping its longer-term direction.
About the RoleWe are looking for a Senior Machine Learning Engineer with strong depth in machine learning and practical experience applying reinforcement learning and related methods to agent behavior and decision systems. This role is focused on the ML core of Egofold: designing experiments, training and improving models, shaping evaluation loops, and helping successful approaches become usable parts of the broader project.
This is not a siloed research role. The best candidates stay engaged through evaluation, iteration, and practical integration, and bring enough adjacent breadth to be effective in a small, collaborative team. We value curiosity, ownership, sound judgment, and respectful, low-ego collaboration.
Job Type: Full-TimeLocation: Hybrid - Los Angeles Area (1-2 in-office meetings per month)
Responsibilities
  • Design, train, and iterate on machine learning models for intelligent agents and decision-making systems, with an emphasis on reinforcement learning and related approaches.
  • Define and refine state representations, action spaces, reward structures, and evaluation criteria to improve agent behavior.
  • Build and improve practical experimentation and training workflows, including data generation, experiment tracking, and reproducibility.
  • Analyze results, debug model behavior, and make pragmatic tradeoffs between model performance, iteration speed, and system complexity.
  • Work closely with engineers and other partners to help integrate successful ML work into usable product systems.
  • Contribute thoughtful technical input on next-step experiments, tooling, and ML direction as Egofold continues to evolve.

Minimum Requirements
  • Strong foundation in machine learning, with hands-on experience building, training, and iterating on applied ML systems.
  • Professional or substantial project experience with reinforcement learning, agent-based systems, sequential decision-making, or closely related areas.
  • Strong Python skills and experience with modern ML frameworks such as PyTorch.
  • Experience designing experiments, evaluating model behavior, and improving results through systematic iteration.
  • T-shaped capability: deep machine learning expertise plus practical range across one or more adjacent areas such as simulation, evaluation, model integration, systems collaboration, or robotics-adjacent machine learning.
  • Strong problem-solving ability, sound judgment, and comfort working in ambiguous, fast-changing environments.
  • Respectful, low-ego collaborative style and willingness to work beyond a narrow specialty when the work requires it.

Nice to Have Any of the following are valuable, but we do not expect depth in every area:
  • Experience with reinforcement learning methods such as PPO, SAC, DQN, actor-critic, or related approaches.
  • Familiarity with simulation environments, multi-agent systems, game AI, or interactive agent behaviors.
  • Familiarity with C++, inference runtimes, or collaborating with engineers who deploy machine learning models into production systems.
  • Exposure to robotics, embodied AI, or embedded / on-device machine learning constraints.

Salary Range: $150,000 - $185,000 Annually
Why Join the Snail Games USA Team?
  • True focus on work/life balance
  • Paid company holidays, vacation, and separate sick leave
  • Medical, dental, vision, and Life/LTD
  • 401k with company match

Work Authorization Requirements
Applicants must be legally authorized to work in the United States at the time of application. This position does not offer visa sponsorship now or in the future (including H-1B).
Additional Information
As part of the Company's activities in video game development, publishing, and short-form video content creation, certain projects, discussions, or creative materials may include themes, visuals, language, or subject matter that some individuals could find mature, violent, sexual, graphic, or otherwise sensitive in nature (collectively referred to as "Mature Content"). Examples may include, but are not limited to, depictions or descriptions of combat, violence, adult themes or relationships, suggestive or satirical humor, or strong language. Employees are expected to engage with such material in a professional and creative context as part of their job duties.

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