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Senior Machine Learning Engineer - NLP (Bangalore/Noida Location)

Level AI· AI /
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Hybrid (Noida), Hybrid (Bangalore)Full-timePosted 11mo ago

About the role

Senior ML Engineer focused on NLP and LLM-based solutions, responsible for building, deploying, and scaling production NLP pipelines, optimizing models, and driving AI innovations across Level AI’s products in hybrid, Bengaluru/Noida locations.

Responsibilities

  • Understand customers’ needs and innovate and use cutting-edge Machine Learning techniques to build data-driven solutions.
  • Work on NLP problems across areas such as voice agents, agentic applications, text classification, entity extraction, and summarisation, using LLMs.
  • Collaborate with cross-functional teams to integrate/upgrade AI solutions into company’s products and services
  • Optimise existing machine learning models for performance, scalability and efficiency.
  • Help implement and evaluate reasoning, planning, and memory modules for agents.
  • Build, deploy and own scalable production NLP pipelines.
  • Build post-deployment monitoring and continual learning capabilities.
  • Propose suitable evaluation metrics and establish benchmarks.
  • Keep abreast of SOTA techniques in your area and exchange knowledge with colleagues.
  • Desire to learn, implement and apply latest emerging model architectures (like LLMs), inference optimizations, distributed training, using open-source models, etc.

Qualifications

  • B.Tech/M.Tech/PhD in computer science or mathematics-related fields from tier-1 engineering institutes with 3+ years of industry experience in Machine Learning and NLP.
  • Strong coding skills in Python and Pytorch with familiarity with libraries like Transformers and LangChain/LangGraph.
  • Strong practical experience in NLP problems in areas such as text classification, entity tagging, information retrieval, question-answering, natural language generation, clustering, etc.
  • Knowledge and hands-on experience with Transformer-based Language Models like BERT, Llama, Qwen, Gemma, DeepSeek, etc.
  • In-depth familiarity with LLM training concepts, model inference optimizations, GPUs, etc.
  • Experience with ML and Deep Learning model deployments using REST API, Docker, Kubernetes, etc.
  • Good problem-solving skills involving data structures and algorithms.
  • Knowledge of cloud platforms (AWS/Azure/GCP) and their machine learning services is desirable.
  • Knowledge of multimodal models is a plus
  • Knowledge of real-time streaming tools/architectures like Kafka and Pub/Sub is a plus.

Skills

Required:PythonPyTorchTransformersLangChain / LangGraphNLPLLM conceptsREST API / Docker / Kubernetes
Nice to have:Cloud ML servicesMultimodal modelsStreaming tools (Kafka / Pub/Sub)
Last updated Aug 19, 2026. Interested? Apply on the company site.
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