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.
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