Senior LLM Engineer
Required Skills
Job Description
Job Title: Senior LLM Engineer
Job type: Hybrid
Location: Bangalore, Pune, Delhi
About Us:
At micro1, we’re all about connecting skilled remote professionals with some of the best companies in Silicon Valley. Our mission is to offer a stable, competitive income, along with access to top industry opportunities—all in a flexible work setting with a range of great benefits. We’re here to help you grow in your career. We're proud to work with trusted partners such as Deel, Immutable, O’Gara, and LegalSoft.
What We Offer:
- Healthcare reimbursement
- Wi-Fi Reimbursement
- Unlimited Learning: Access to Udemy courses, books, and everything you need to keep growing
- And So Much More: We’re not just about work—we’re about creating an environment where you’ll love to be!
About the Role:
We are seeking a Senior Large Language Model (LLM) Engineer with solid experience in production deployments. The ideal candidate will have a proven track record in developing, deploying, and optimizing large language models in a production environment. We are looking for individuals who have hands-on experience and are capable of managing end-to-end solutions rather than just building prototypes or proofs of concept.
Key Responsibilities:
- Design, develop, and deploy large language models for diverse, production-level applications.
- Scale GenAI applications to handle high user loads and large datasets with optimized response times.
- Develop and refine prompt strategies, including zero-shot and context-based techniques, for effective LLM utilization.
- Set up and manage end-to-end pipelines involving vector databases, caching layers, and embedding systems.
- Work in containerized environments, such as Kubernetes, to build and maintain pipelines and create API endpoints.
Required Qualifications:
- 4-8 years of Experience in software engineering, with at least 2 years in hands-on LLM projects.
- 3-4 years of experience in Python Development, with proficiency in FastAPI or Flask.
- Strong understanding of APIs , WebSockets, and production deployments.
- Experience with EC2, SageMaker, and AWS databases in AWS Services.
- Hands-on experience with frameworks such as Langchain, LlamaIndex, DSPy, and tools like OpenAI, vector databases, and recent prompt engineering and RAG implementations in LLM/GenAI Expertise.
- Proficiency in setting up pipelines, containerizing applications, and creating handoff-ready API endpoints for DevOps in Kubernetes.
- Practical experience with fine-tuning open-source models for production environments.
Nice to Have:
- Familiarity with Azure services
- Practical and deployed experience rather than hobbyist projects Experience in Fine-Tuning Open Source Models.