Note: The job is a remote job and is open to candidates in USA. JSR Tech Consulting is seeking a Lead Machine Learning Engineer focused on Generative AI to bridge theoretical GenAI capabilities with practical production applications. The role is responsible for deploying and maintaining reliable, scalable, secure, and cost-effective GenAI solutions, including data pipelines, cloud infrastructure, automation, monitoring, advanced GenAI techniques, and agent systems.
Responsibilities
- 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
- Cost Optimization: Implement strategies to manage and reduce the operational costs associated with GenAI deployments
Skills
- Bachelor's degree in computer science/Engineering, data science, or a related field
- 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
- Experience with cloud platforms, containerization, and infrastructure management
- Familiarity with DevOps practices and automation tools
- Expertise in GenAI frameworks, prompt engineering, and model serving
- Ability to manage GPU/TPU resources and optimize model serving frameworks
- Experience in developing agentic systems and multi-agent architectures
- Proven track record in cost optimization in AI deployments
- Experience working in fast paced environment and independent worker
- Master's degree
Benefits
- Remote position
Company Overview