Description :

About The Opportunity.

- Industry: Enterprise AI / Natural Language Processing (NLP).

- Sector: Large Language Model (LLM) products and NLP-driven automation for B2B applications including conversational AI, semantic search, and knowledge ingestion.

- Remote role based in India delivering production-grade ML systems and inference services.

- Primary Job Title: Senior Machine Learning Engineer NLP & LLM.

Role & Responsibilities :

- Design, fine-tune and evaluate large language models for downstream NLP use-cases (chatbots, semantic search, summarization, QA) and deliver production readiness.

- Implement robust data pipelines for text preprocessing, annotation ingestion, and training dataset creation to support supervised and instruction-tuning workflows.

- Develop scalable model training and inference pipelines using Hugging Face / PyTorch / TensorFlow, including distributed training and mixed-precision optimization.

- Productionize models: containerize, deploy and monitor LLM services with MLOps best practices (CI/CD, model versioning, canary rollout, observability).

- Optimize inference throughput and cost: quantization, model distillation, batching, GPU/CPU resource management and vector-search integration (FAISS).

- Collaborate with product managers, ML researchers and engineers to define evaluation metrics, A/B tests and continuous improvement loops for model quality and safety.

Skills & Qualifications:

Must-Have:

- 4+ years of hands-on ML engineering experience with strong emphasis on NLP and LLM workflows.

- Proven experience fine-tuning and deploying transformer-based models (Hugging Face Transformers).

- Strong Python engineering skills and deep familiarity with PyTorch or TensorFlow.

- Experience building production ML pipelines, containerization (Docker) and cloud deployment (AWS / GCP) with monitoring and CI/CD.

Preferred :

- Experience with LangChain or similar orchestration for model agents and tool-calling.

- Hands-on knowledge of vector search systems (FAISS) and inference optimization techniques (quantization, distillation).

Benefits & Culture Highlights :

- Fully remote, India-based role with flexible hours and a strong focus on asynchronous collaboration.

- Opportunity to own end-to-end LLM product features and influence architecture decisions in a fast-paced AI team.

- Learning-first culture with support for conferences, courses and hands-on experimentation with cutting-edge ML tooling.

- If you are passionate about shipping reliable, scalable LLM-powered products and have a strong track record in NLP engineering, this role offers a high-impact, remote opportunity to advance enterprise AI solutions.