Job Description
We are seeking a visionary Senior Engineer to lead the architectural evolution of our AI infrastructure. As we move towards the 2026 era of autonomous agents and generative intelligence, we need a technical leader who can bridge the gap between theoretical AI research and scalable production deployment. You will be instrumental in defining our roadmap for next-generation Large Language Models (LLMs) and Agentic Workflows.
Why Join Us?
• Work on cutting-edge projects that define the future of human-computer interaction.
• Competitive equity package and top-tier healthcare benefits.
• Collaborative environment with industry pioneers.
Responsibilities
- Architect and optimize production-grade Retrieval-Augmented Generation (RAG) pipelines to ensure high-fidelity data retrieval.
- Lead the fine-tuning and evaluation of Large Language Models (LLMs) on proprietary datasets to enhance domain-specific accuracy.
- Design scalable MLOps infrastructure to support model deployment, monitoring, and retraining loops.
- Collaborate with product teams to translate complex requirements into functional Agentic AI workflows.
- Ensure model ethical guidelines, safety protocols, and bias mitigation strategies are implemented.
- Conduct research on emerging AI paradigms to keep our technology stack ahead of the curve.
Qualifications
- 5+ years of experience in Machine Learning Engineering, NLP, or AI research.
- Deep expertise in Python, PyTorch, and TensorFlow.
- Strong experience with vector databases (Pinecone, Weaviate, Milvus) and LLM frameworks (LangChain, LlamaIndex).
- Experience deploying AI models to cloud environments (AWS, GCP, or Azure).
- Proven track record of improving model performance metrics (Latency, Token Speed, Accuracy).
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.