JSR Tech Consulting · 19 hours ago
Senior Machine Learning Engineer (Generative AI / MLOps)
JSR Tech Consulting is seeking a Senior Machine Learning Engineer with a strong Generative AI and MLOps focus to join a financial services organization on a contract-to-hire basis. This role involves deploying and operating Generative AI solutions at scale, ensuring reliability and performance in production environments.
Responsibilities
Deploy, monitor, and maintain Generative AI and machine learning models in production environments
Ensure reliability, scalability, security, and performance of GenAI solutions in real-world use cases
Apply advanced GenAI techniques including LLMs, Retrieval-Augmented Generation (RAG), hallucination monitoring, and human-in-the-loop workflows
Design and manage ML infrastructure using cloud platforms (AWS, Azure, or GCP)
Build and maintain containerized workloads using Docker and orchestration with Kubernetes
Implement infrastructure-as-code using Terraform or CloudFormation
Develop and manage CI/CD pipelines to support model development, deployment, and versioning
Build and maintain data pipelines and storage solutions that support model training and inference
Partner with data engineers to ensure efficient, reliable data access for ML workflows
Implement secure coding practices, authentication, and authorization for ML systems
Set up monitoring, alerting, and logging for infrastructure and model performance
Manage GPU/TPU resources and optimize model serving to control operational costs
Design and implement agentic and multi-agent systems using frameworks such as LangChain
Enable GenAI systems to interact with external APIs, tools, and services effectively
Qualification
Required
Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
5+ years of experience as a Machine Learning Engineer with hands-on production deployment experience
Strong proficiency in Python and modern software engineering best practices
Solid understanding of machine learning fundamentals, model lifecycle management, and production monitoring
Experience with cloud platforms, containerization, and infrastructure management
Hands-on experience with DevOps practices, CI/CD pipelines, and automation tools
Demonstrated experience working with Generative AI frameworks, prompt engineering, and model serving
Ability to work independently in a fast-paced environment
Preferred
Master's degree in Computer Science, Engineering, Data Science, or a related field
Experience managing GPU/TPU workloads and optimizing inference performance
Hands-on experience with agent frameworks and multi-agent architectures
Proven ability to optimize costs associated with GenAI deployments
Experience deploying ML solutions in regulated or enterprise environments