Senior Machine Learning Engineer - NLP (Bengaluru/Noida)

We'll love to explore more about you if you have

Big picture: 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.

Your role at Level AI includes but is not limited to

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.

Bonus Points

Experience with open-source LLMs (LLaMA, Mistral, etc.)

Basic understanding of vector search, RAG, and prompt engineering concepts

Contributions to AI side projects or GitHub repos

Exposure to vector databases or retrieval pipelines (e.g., FAISS, Pinecone)

To learn more visit : https://thelevel.ai/

Funding : https://www.crunchbase.com/organization/level-ai

LinkedIn : https://www.linkedin.com/company/level-ai/