AI Summary
Lead design, implementation, and operationalization of LLM-driven products. Design and implement end-to-end LLM/NLP pipelines, build and maintain RAG systems, and optimize inference throughput and latency.
Key Highlights
Design and implement end-to-end LLM/NLP pipelines
Build and maintain RAG systems
Optimize inference throughput and latency
Technical Skills Required
Benefits & Perks
Fully remote role
Flexible working hours
Learning stipend
Conference support
Mentorship
Job Description
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.
Must-Have (technical skills):
- Python
- PyTorch
- Hugging Face Transformers
- LangChain
- FAISS
- Docker
- Kubernetes
- AWS SageMaker
- Model quantization
- 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.
- 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.
Skills: machine learning,nlp,llm