Primary Title: Machine Learning Engineer (NLP & LLM)
About The Opportunity
A technology services firm operating in Enterprise AI and Natural Language Understanding, building production-grade LLM and NLP solutions used in customer-facing automation, document intelligence, and search applications. We deliver scalable, secure ML systems and integrate state-of-the-art language models into cloud-native backends to drive measurable business outcomes.
Location: India (Remote)
- Role level: Mid — 4 years experience
Role & Responsibilities
- Design, train, fine-tune, and evaluate LLMs and transformer-based NLP models for tasks such as classification, named-entity recognition, summarization, and retrieval-augmented generation (RAG).
- Implement model-serving pipelines and APIs (low-latency inference) using containerized services; optimise model size, quantisation, and batching for production.
- Build data pipelines for text ingestion, annotation, and feature engineering; partner with data engineers to automate ETL and retraining workflows.
- Integrate vector search and similarity-based retrieval (FAISS/Annoy etc.) into RAG architectures and implement prompt orchestration for multi-step LLM workflows.
- Author reusable model evaluation, monitoring, and CI/CD practices for experiments, model versioning, and drift detection.
- Collaborate with product and engineering teams to translate business requirements into performant, maintainable ML solutions and production drivers.
Skills & Qualifications
Must-Have
- Python
- PyTorch
- Hugging Face Transformers
- Natural Language Processing
- Large Language Models
- TensorFlow
Preferred
Benefits & Culture Highlights
- Fully remote, India-first hiring with flexible hours and focused ownership of features.
- Opportunity to work end-to-end — research, experiment, and ship models to production in customer projects.
- Learning-focused environment with exposure to modern MLOps, transformer stacks, and cloud-native deployments.
We seek pragmatic ML engineers who combine strong engineering discipline with hands-on LLM/NLP experience to move models from notebooks into reliable services. Apply if you enjoy solving real-world language problems, optimising model inference, and building reproducible ML systems.
Skills: ml,nlp,llm
