Role: Senior Machine Learning Engineer (NLP/LLM).

Industry: Enterprise AI & Cloud Software building scalable NLP and Large Language Model (LLM) solutions for search, summarization, conversational AI, and intelligent automation across B2B and consumer platforms.

This is a fully remote role based in India helping accelerate production-grade LLM deployments, RAG systems, and real-time inference pipelines.

Orbion Infotech is hiring an experienced ML engineer to lead design, implementation, and operationalization of LLM-driven products that deliver measurable customer impact.

You will join a distributed engineering team focused on model quality, inference efficiency, and robust ML platform practices.

Role & Responsibilities :

- Design and implement end-to-end LLM/NLP pipelines: data collection, preprocessing, fine-tuning/adapter training, evaluation, and deployment.

- Build and maintain Retrieval-Augmented Generation (RAG) systems: embeddings, vector store integration, FAISS-based search, and relevance tuning.

- Optimize inference throughput and latency: quantization, batching, ONNX/Triton optimizations, containerized deployment (Docker) and autoscaling.

- Integrate LLM capabilities into backend services and APIs using LangChain (or equivalent) and orchestrate workflows for prompt templates, tool calling, and agentic flows.

- Implement monitoring, testing, and CI/CD for ML models: unit/eval tests, drift detection, observability dashboards, and rollout/rollback strategies.

- Partner with product, data engineering, and MLOps teams to define success metrics, mentor engineers, and drive ML best practices across the org.

Skills & Qualifications :

Must-Have (technical skills) :

- Python.

- PyTorch.

- Hugging Face Transformers.

- LangChain.

- FAISS.

- Docker.

Preferred (nice-to-have) :

- Kubernetes.

- AWS SageMaker.

- Model quantization.

Experience & Qualifications :

- 7+ years of professional experience in machine learning engineering, with demonstrable leadership on NLP/LLM projects.

- Proven track record of deploying production LLMs or large-scale NLP systems with measurable performance and reliability outcomes.

- Strong software engineering fundamentals: code quality, CI/CD, testing, and working in distributed/remote teams.

Benefits & Culture Highlights :

- Fully remote role with flexible working hours and India-based hiring.

- Opportunity to work on cutting-edge LLM products and own end-to-end delivery across cloud and edge environments.

- Learning stipend, conference support, and mentorship in a fast-paced, growth-oriented engineering culture.