over 1 year ago
Bengaluru, IndiaSenior
Responsibilities
- Develop NLP and LLM solutions for voice agents, agentic applications, classification, entity extraction, and summarization.
- Collaborate with cross-functional teams to integrate and upgrade AI solutions in company products and services.
- Optimize machine learning models for performance, scalability, and efficiency.
- Implement and evaluate reasoning, planning, and memory modules for agents.
- Build, deploy, and own scalable production NLP pipelines.
- Develop post-deployment monitoring and continual learning capabilities.
- Define evaluation metrics, establish benchmarks, and track model performance.
- Stay current with state-of-the-art techniques, model architectures, inference optimization, distributed training, and open-source models.
Requirements
- Bachelor’s, master’s, or PhD in computer science or a mathematics-related field from a tier-1 engineering institute.
- At least 3 years of industry experience in machine learning and NLP.
- Strong coding skills in Python and PyTorch, with familiarity with Transformers and LangChain/LangGraph.
- Practical experience with NLP problems including text classification, entity tagging, information retrieval, question-answering, natural language generation, and clustering.
- Hands-on experience with transformer-based language models such as BERT, Llama, Qwen, Gemma, and DeepSeek.
- In-depth knowledge of LLM training concepts, model inference optimization, and GPUs.
- Experience deploying machine learning and deep learning models using REST APIs, Docker, and Kubernetes.
- Knowledge of data structures and algorithms and cloud platforms such as AWS, Azure, and GCP.
- Knowledge of multimodal models and real-time streaming tools or architectures such as Kafka and Pub/Sub is a plus.
- Experience with open-source LLMs, vector search, RAG, prompt engineering, vector databases, retrieval pipelines, or AI side projects is beneficial.
Categories
About Level AI
Level AI builds a conversational intelligence platform for enterprise contact centers, combining speech AI, NLP, and retrieval to analyze customer interactions and drive QA, coaching, automation, and analytics. It sells its software to large customer service and sales teams, typically via subscription. Founded in 2018 and headquartered in Mountain View, the company is Series C–funded, with customers such as Wayfair, Smartsheet, Chime, Gusto, and Swiss Re.