Hiring: AI / ML Engineer Company: JSR Tech Consulting Location: California, United States Job Posted Time: 2026-09-10 15:09:23 Employment Type: Remote Target Skills & Keywords : AWS, Azure, CI/CD, CloudFormation, Data Pipeline, Docker, GCP, Git, Hugging Face, Infrastructure as Code, Kubernetes, LLM, LangChain, Machine Learning, Python, RAG, Terraform About the job Required Skills: •Model Deployment & Maintenance: Focus on deploying, monitoring, and maintaining GenAI models in production, ensuring they function reliably in real-world settings. •Data Engineering: Build and maintain efficient data pipelines and storage solutions that support model operations. •Infrastructure Management: Utilize cloud platforms (AWS, Azure, GCP) for model deployment, containerization (Docker), orchestration (Kubernetes), and infrastructure as code (Terraform/CloudFormation). •DevOps & Automation: Develop CI/CD pipelines, manage version control (Git), and automate deployment processes for seamless operational efficiency. •Security & Monitoring: Implement secure coding practices, authentication, authorization, and set up robust monitoring and alerting systems for both infrastructure and model performance. •Generative AI Expertise: Deep understanding of LLMs, GenAI architectures, frameworks like Hugging Face, prompt engineering, and specialized infrastructure for GenAI workloads. •Advanced Techniques: Apply advanced GenAI techniques like Retrieval-Augmented Generation (RAG), hallucination monitoring, and human-in-the-loop systems. •Agent Development: Design and develop agent and multi-agent systems using frameworks like LangChain, enabling them to interact with external APIs and tools efficiently. Qualifications: •Bachelor's degree in computer science/Engineering, data science, or a related field. Master's degree preferred •At least five plus years' experience as a machine learning engineer, deploying models in production •Strong proficiency in Python and software engineering principles. •Solid understanding of machine learning fundamentals and model lifecycle management. •Operational familiarity with DevOps practices and automation tools. •Expertise in GenAI frameworks, prompt engineering, and model serving. •Demonstrated capacity to manage GPU/TPU resources and optimize model serving frameworks. •Proven track record in cost optimization in AI deployments. Compensation: •Flexible work environment (work from home / hybrid options) Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!