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Python Ml Developer Jobs in Glendale, CA (NOW HIRING)

Tror AI for everyone

AI/ML Architect

Los Angeles, CA · On-site

AI/ML Architect with Databricks Location : Los Angeles CA (Hybrid) Role Overview We are seeking a ... Strong programming skills in Python (pandas, numpy, scikit‑learn). * Experience working with ...

Capsule.Video Inc

AI Engineer

Los Angeles, CA · On-site

... as an AI/ML engineer in a commercial software development setting * Computer Science or related degree * Strong proficiency in Python and at least one deep learning framework (e.g. PyTorch)

CookUnity

Director, Data Science/ML

Los Angeles, CA

Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap ... Hands-on technical proficiency in Python, SQL, and modern ML frameworks (scikit-learn, PyTorch ...

Doist

Senior Applied AI/ML Engineer

Santa Monica, CA · On-site

$140 - $200/hr

As a Senior Applied AI/ML Engineer, you will design, build, and improve production AI systems that ... Strong software engineering background, particularly with Python and backend systems that support ...

New

CIM Group

Sr. Machine Learning Ops Engineer

Los Angeles, CA · On-site

$140K - $179K/yr

... ML models and GenAI applications, leveraging GitHub Actions, Azure DevOps, or similar tools. • ... Python, complemented by strong skills in Bash scripting. • Extensive experience designing and ...

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All JobsPython Ml Developer JobsPython Ml Developer Jobs in Glendale, CA

Python Ml Developer information

See Glendale, CA salary details

$14

$62

$91

How much do python ml developer jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for python ml developer in Glendale, CA is $62.09, according to ZipRecruiter salary data. Most workers in this role earn between $51.15 and $70.53 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.

What are the key skills and qualifications needed to thrive as a Python ML Developer?

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.

What cities near Glendale, CA are hiring for Python Ml Developer jobs? Cities near Glendale, CA with the most Python Ml Developer job openings:
Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in Glendale, CA as of July 2026, with employment types broken down into 1% Internship, 87% Full Time, 7% Part Time, and 5% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $129,141 per year, or $62.1 per hour.

AI/ML Architect

Tror AI for everyone

Los Angeles, CA • On-site

Contractor

Re-posted 26 days ago

Job description

Job Title: AI/ML Architect with Databricks

Location : Los Angeles CA  (Hybrid)

  

Role Overview

We are seeking a skilled AI/ML Architect with hands-on experience in Databricks to join our team. The ideal candidate has strong analytical capabilities, experience building scalable data pipelines and machine learning models, and the ability to collaborate with cross‑functional teams to drive data‑driven decision‑making.

This role involves working with large datasets, advanced analytics, and modern data engineering and ML frameworks—primarily using Databricks on Azure/AWS.

Skills & Qualifications

Required

  • Bachelor’s degree or higher in Computer Science, Data Science, Mathematics, Statistics, Engineering, or related field.
  • 3+ years of experience in data science or machine learning roles.
  • Advanced knowledge of Databricks, including:
  • PySpark / Spark SQL
  • Databricks notebooks
  • Delta Lake
  • MLflow
  • Databricks Jobs & Workflows
  • Strong programming skills in Python (pandas, numpy, scikit‑learn).
  • Experience working with large-scale data processing.

Solid understanding of machine learning algorithms and statistical techniques

Key Responsibilities

Data Science & Machine Learning

  • Develop, train, and optimize machine learning and statistical models using Databricks, Python, PySpark, and MLflow.
  • Perform exploratory data analysis (EDA) to identify trends, patterns, and insights in large datasets.
  • Deploy ML models into production using Databricks MLflow, Delta Live Tables, or other MLOps pipelines.
  • Conduct A/B testing, forecasting, segmentation, anomaly detection, or recommendation systems as required by the business.

Data Engineering & Databricks Platform

  • Build scalable, high‑performance ETL/ELT pipelines using PySpark, SQL, and Databricks workflows.
  • Work with Delta Lake to ensure high-quality, reliable, and performant data.
  • Optimize cluster usage and job performance within the Databricks environment.
  • Collaborate with data engineers to ensure high-quality data availability for modeling.

Business Collaboration

  • Translate business problems into analytical solutions and present findings to non‑technical stakeholders.
  • Partner with product, engineering, and business teams to drive data-informed decisions.
  • Communicate complex statistical concepts in a clear and concise manner.

Preferred

  • Experience deploying models in production using MLOps frameworks.
  • Knowledge of Azure Databricks or AWS Databricks environments.
  • Understanding of CICD pipelines and DevOps concepts (Azure DevOps, GitHub Actions, etc.)
  • Familiarity with deep learning frameworks (TensorFlow, PyTorch) is a plus.

Key Competencies

  • Strong analytical and problem‑solving skills
  • Ability to work in a fast-paced, collaborative environment
  • Excellent communication and presentation skills
  • Self-driven with high attention to detail