Location: India- Remote
Experience: 5–10 Years
About The Client
We are hiring on behalf of our client, a pioneering organization addressing the growing shortage of healthcare professionals through AI-driven solutions. They are building next-generation AI healthcare workers to enhance care delivery, improve patient outcomes, and support providers at scale.
Job Summary
We are looking for a skilled Machine Learning Engineer to join the engineering team. This role focuses on building and optimizing multi-agent systems that power an ML-driven provider assistant. The ideal candidate will have strong experience in LLMs, RAG pipelines, and production-grade ML systems, along with a passion for solving complex problems in a fast-paced, evolving environment.
Key Responsibilities
- Design, develop, and maintain multi-agent ML systems for care pathway optimization
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines for low latency and high accuracy
- Develop scalable, reliable, and safe ML solutions aligned with goal-driven workflows
- Integrate LLMs and proprietary ML models into production environments
- Collaborate with cross-functional teams (data science, engineering, product)
- Solve challenges related to real-time ML applications, including performance and scalability
- Monitor, evaluate, and improve ML model performance in production
- Explore and adopt new tools, frameworks, and ecosystems beyond existing cloud environments
- Implement MLOps best practices (model versioning, retraining, deployment)
- Ensure compliance with data privacy and security standards
Key Requirements
- 5+ years of experience in Machine Learning Engineering or related roles
- Strong experience in building production-grade ML systems
- Hands-on experience with LLMs and RAG pipelines
- Solid understanding of multi-agent systems and distributed architectures
- Proficiency in Python and frameworks such as LangGraph, Google ADK, etc.
- Experience with cloud platforms (preferably Azure) and cloud-native ML tools
- Strong problem-solving skills in latency, accuracy, and ML system safety
- Good knowledge of data structures, algorithms, and software engineering principles
- Experience with MLOps practices (monitoring, retraining, versioning)
- Excellent communication and cross-functional collaboration skills
- Experience in US Healthcare domain
- Ability to work in ambiguous and evolving problem spaces
- Experience in high-impact, fast-paced environments
Additional Information
Minimum 1.5+ years stability in each organization
Remote for a couple of months; once the team is set up, later might have to move to Bangalore.
Notice Period: Immediate to 30 days preferred
