About ARCHLE Labs
ARCHLE Labs – Advanced Research Centre for Health And Life Science Engineering is a health-tech R&D startup based in Bangalore. Our team comprises experienced healthcare professionals and entrepreneurs passionate about making a difference in the world.
“Our mission is to drive innovations to solve complex medical challenges and enhance human well-being.”
Our commitment lies in harnessing the power of science and engineering to create tangible solutions that empower the health of individuals and communities worldwide.
Role Description
We are looking for a highly motivated AI/ML Engineer to join our Research & Development team. In this role, you will work on cutting-edge Generative AI, NLP, and machine learning applications focused on solving real-world healthcare and life science challenges.
You will be responsible for designing, developing, and deploying intelligent AI systems using modern LLM frameworks, RAG pipelines, and deep learning technologies. This is a high-impact opportunity to work closely with the CEO and leadership team in a fast-paced startup environment where innovation and ownership are highly valued.
If you are passionate about artificial intelligence, large language models, and building meaningful AI-driven healthcare solutions, we’d love to meet you.
Key Responsibilities
- Develop and deploy AI/ML applications using Python
- Build and optimize NLP and Generative AI workflows
- Design and implement RAG (Retrieval-Augmented Generation) pipelines
- Work with vector databases and embedding models
- Develop AI agents and workflows using LangChain and LangGraph
- Build scalable APIs and backend services using FastAPI
- Perform prompt engineering and optimize LLM performance
- Work with Hugging Face models, transformers, and open-source AI frameworks
- Research, test, and evaluate new AI/ML technologies and advancements
- Assist in fine-tuning and optimizing deep learning/LLM models
- Collaborate with cross-functional teams to integrate AI solutions into products
- Participate in end-to-end model deployment and monitoring
- Maintain technical documentation and development workflows
- Work closely with leadership on AI product strategy and innovation
Requirements
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or related field
- 0-1 years of experience
- Strong proficiency in Python and AI/ML application development
- Hands-on experience with NLP and LLM workflows
- Practical experience with LangChain, LangGraph, and FastAPI
- Good understanding of RAG pipelines and vector embeddings
- Knowledge of prompt engineering techniques
- Familiarity with Hugging Face ecosystem and transformer architectures
- Understanding of machine learning algorithms and deep learning fundamentals
- Basic experience with fine-tuning deep learning or LLM models
- Strong problem-solving and analytical skills
- Ability to work effectively in a fast-paced startup environment
- Strong communication and collaboration skills
- Passion for learning, research, and staying updated with advancements in AI and machine learning
Nice to Have (Optional)
- Experience with AWS EC2 and SageMaker
- Exposure to Microsoft Azure
- Knowledge of GraphRAG architectures
- Experience working with PostgreSQL
- End-to-end AI model deployment experience
- Experience building scalable production AI systems
- Exposure to healthcare AI applications or health-tech products
- Experience working in startup or R&D environments
What We Offer Here
- Competitive salary and benefits package
- Potential ESOP grants based on performance and tenure
- Opportunity to work closely with founders, CEO, and leadership team
- High ownership role with significant growth potential
- Collaborative and innovative work environment
- Professional development and research opportunities
- Opportunity to work on cutting-edge AI and healthcare technologies
- The chance to make a significant impact on healthcare innovation
Application Question(s):
- We are looking for immediate recruitment, will you be able to join us immediately ?
Work Location: In person
