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

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AI/ML Architect

Los Angeles, CA · On-site

$68.75 - $88.25/hr

Strong programming ability in Python (pandas, numpy, scikit-learn). * Demonstrated experience with large-scale, multi-terabyte data processing. * Strong understanding of ML algorithms, distributed ...

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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.

Senior AI/ML Engineer GenAI & Cloud Solutions

Alpha Silicon

Los Angeles, CA • On-site

$60 - $80.25/hr

Other

Re-posted 21 days ago

Job description

Key Responsibilities

  • Architect and Design: Lead the design of scalable, secure, and high-performance AI/ML systems leveraging Agentic Layer A2A frameworks and MCP Protocols.
  • Solution Engineering: Drive end-to-end solution development including vector embeddings, prompt engineering, and context engineering for enterprise-grade GenAI applications.
  • Cloud Deployment: Architect and oversee deployment of AI/ML workloads on Azure Cloud, ensuring compliance, scalability, and cost optimization.
  • Data Architecture: Design and optimize data pipelines and storage solutions using Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg.
  • Application Development: Build and manage Azure Functions and Azure Container Apps for microservices-based AI solutions.
  • Performance & Scalability: Define cloud-native architecture patterns, implement performance tuning, and ensure resilience across distributed systems.
  • Domain Expertise: Apply deep knowledge of healthcare domain requirements, ensuring solutions meet regulatory standards (HIPAA, GDPR, etc.) and handle sensitive data securely.
  • Technical Leadership: Mentor engineering teams, establish best practices, and conduct design/code reviews.
  • Innovation & Research: Stay ahead of emerging GenAI, LLM/NLM trends, and integrate cutting-edge approaches into enterprise solutions.

Required Skills & Expertise

  • Agentic Layer & Protocols: Hands-on expertise with Agentic Layer A2A frameworks and MCP Protocol for multi-agent orchestration.
  • AI/ML Engineering: Strong background in vector embeddings, prompt engineering, context engineering, and fine-tuning LLMs.
  • GenAI & LLM Concepts: Deep understanding of Generative AI, Natural Language Models (NLM), and Large Language Models (LLM).
  • Programming: Advanced proficiency in Python; exposure to Java/Go is a plus.
  • Cloud Proficiency: Strong experience with Azure Cloud services, including deployment, monitoring, and scaling.
  • Databases: Expertise in Azure AI Search, Redis, Cosmos DB; familiarity with Blob Storage and Iceberg is advantageous.
  • Cloud-Native Architecture: Solid grasp of microservices, containerization, serverless computing, scalability, and performance optimization.
  • Healthcare Domain: Experience working with regulated data environments and compliance frameworks.

Evaluation Criteria (Critical Components)

1. Technical Depth

  • Ability to design and implement multi-agent AI systems.
  • Experience in LLM fine-tuning, embeddings, and context engineering.
  • Expertise in coding proficiency with production-grade systems in Python.

2. Architectural Vision

  • Ability to define enterprise-level AI/ML architecture aligned with cloud-native principles.
  • Experience in scalability, resilience, and performance optimization.

3. Cloud & Data Expertise

  • Hands-on deployment of AI workloads on Azure Cloud.
  • Strong knowledge of databases, search systems, and distributed storage.

4. Domain Knowledge

  • Familiarity with healthcare regulations and ability to design compliant solutions.

5. Leadership & Collaboration

  • Experience mentoring engineers, conducting reviews, and driving technical excellence.
  • Ability to collaborate with cross-functional teams including product, compliance, and operations.

6. Innovation & Research Orientation

  • Evidence of staying current with GenAI advancements and applying them to real-world problems.

Preferred Qualifications

  • Bachelors or master's in computer science, AI/ML, or related field.
  • Certifications in Azure Solutions Architect or AI Engineering.
  • Publications, patents, or contributions to open-source AI/ML projects.

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