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Fastapi Programmer Jobs in California (NOW HIRING)

Gap, Inc.

Sr. ML Engineer - ML & Applied AI

San Francisco, CA · On-site

$123K - $168K/yr

Develop and maintain high-performance model serving systems using APIs (e.g., FastAPI) for real ... Collaborate closely with data engineers, platform teams, and product stakeholders to integrate ML ...

Workhelix

Product Engineer

San Francisco, CA · On-site

Role We're hiring a Product Engineer to join our team and help us scale reliably as we grow. As we ... You'll work across our FastAPI (Python) / Postgres / React stack, touching everything from schema ...

Lorven Technologies

Sr. UI Developer

Calabasas, CA · On-site

$63.25 - $82/hr

Hi, Our client is looking for a Sr. UI Developer in Woodland Hills, CA location below is the ... Framework: FastAPI with uvicorn * AI Orchestration: LangGraph + LangChain * External Integration:

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Excelon Solutions

Frontend UI Developer

Woodland, CA · On-site

Role: Senior UI Developer Location:Woodland Hills, CA Need Healthcare Exp Frontend * Framework ... FastAPI with uvicorn * AI Orchestration : LangGraph + LangChain * External Integration : A2A SDK ...

FlexAI

Senior Full Stack Engineer

San Jose, CA · On-site

$180K - $225K/yr

You will work on developer modules Admin modules, Marketplace, and Licensing, shaping the user ... Design and implement APIs and backend services using Python (FastAPI) and/or Node.js * Define clean ...

Tessera Labs

Software Engineer, Backend

San Jose, CA · On-site

... Python (FastAPI, SQLAlchemy). • Build reliable microservices that support data processing ... DevOps to deploy and maintain cloud-based services on AWS or GCP. • Implement secure ...

Shp

MLOps Engineer

Goleta, CA · On-site

$140K - $175K/yr

Deploy and serve models (batch + real-time) via FastAPI/Flask APIs with auto-scaling and rollback ... Translate engineering needs into clean, maintainable code * Comfortable coaching peers on ...

Staffingine LLC

AI/ML Engineer

Los Angeles, CA · On-site

AI/ML Engineer Job Location: Los Angeles - California - USA Job Type: Contract * 3-5 years of ... Experience deploying models using API frameworks such as FastAPI or Flask * Knowledge of MLOps ...

Kai

Senior Software Engineer, AI Platform

San Jose, CA · On-site

$143K - $189K/yr

They are seeking a Senior Software Engineer to join their AI team, focusing on building and scaling ... Python/FastAPI microservices) • Build out observability -- distributed tracing, latency ...

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Sr. ML Engineer - ML & Applied AI

Sr. ML Engineer - ML & Applied AI

Gap, Inc.

San Francisco, CA • On-site

$123K - $168K/yr

Full-time

Re-posted 6 days ago

Gap rating

6.8

Company rating: 6.8 out of 10

Based on 272 frontline employees who took The Breakroom Quiz

25th of 103 rated fashion retailers

Job description

About the Role
Gap Inc. is seeking a Senior Machine Learning Engineer with 10+ years of experience to design, build, and scale production-grade machine learning and AI systems that power data-driven decision making across the enterprise.
This role is focused on end-to-end ML system ownership, including data pipelines, feature engineering, model training, deployment, monitoring, and continuous optimization. You will lead the development of scalable ML platforms, drive best practices in MLOps, and enable reliable, high-performance model inference in both batch and real-time environments.
The ideal candidate combines strong software engineering expertise with deep ML knowledge and has experience building robust, scalable ML systems in production, including modern applications involving large language models (LLMs) and agent-based AI systems.What You'll Do
  • Architect and build scalable, production-grade ML systems from experimentation to deployment and lifecycle management
  • Design and implement end-to-end ML pipelines, including data ingestion, feature engineering, training, validation, and inference
  • Develop and maintain high-performance model serving systems using APIs (e.g., FastAPI) for real-time and batch inference
  • Lead the design and implementation of feature stores and reusable feature pipelines across teams
  • Build and optimize distributed data processing workflows using Spark, Databricks, or similar platforms
  • Implement and enforce MLOps best practices, including CI/CD pipelines, automated retraining, model versioning, and experiment tracking
  • Design and manage model monitoring and observability frameworks to track performance, drift, latency, and system health
  • Drive strategies for model retraining, drift detection, and continuous improvement
  • Collaborate closely with data engineers, platform teams, and product stakeholders to integrate ML solutions into production systems
  • Contribute to the adoption of modern AI capabilities, including LLMs, vector databases, retrieval-augmented generation (RAG), and agentic workflows
  • Ensure high standards of code quality, testing, documentation, and reproducibility
Who You Are
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field
  • 10+ years of experience in machine learning, software engineering, or related roles, with significant experience in production ML systems
  • Strong programming expertise in Python and solid software engineering fundamentals (data structures, system design, APIs)
  • Extensive experience with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow
  • Proven experience designing and deploying scalable ML pipelines and services in production
  • Hands-on experience with model serving frameworks and API development (e.g., FastAPI, Flask)
  • Strong experience with containerization (Docker) and orchestration platforms such as Kubernetes
  • Experience working with cloud platforms (GCP, AWS, or Azure) and building cloud-native ML solutions
  • Deep understanding of ML lifecycle management, including training, evaluation, deployment, monitoring, and retraining
  • Experience implementing CI/CD pipelines for ML workflows and managing version control systems (Git)
  • Strong experience with SQL and distributed data processing frameworks (e.g., Spark, PySpark)
  • Excellent problem-solving skills and ability to design scalable, maintainable systems

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