Senior Machine Learning Engineer - NLP
Build and deploy scalable NLP and LLM solutions for voice agents, classification, information retrieval, and agentic applications. The role requires 3+ years of machine learning and NLP experience, strong Python/PyTorch skills, and experience with production model deployment.
About the job
Responsibilities
- Understand customer needs and apply cutting-edge machine learning techniques to build data-driven solutions.
- Work on NLP problems involving voice agents, agentic applications, text classification, entity extraction, and summarization using LLMs.
- 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.
- Propose evaluation metrics and establish benchmarks.
- Stay current with state-of-the-art techniques and share knowledge with colleagues.
- Apply emerging model architectures, inference optimizations, distributed training, and open-source models.
Requirements
- B.Tech, M.Tech, or PhD in computer science or a mathematics-related field from a tier-1 engineering institute.
- 3+ years of industry experience in machine learning and NLP.
- Strong coding skills in Python and PyTorch.
- 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.
- 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.
- Strong problem-solving skills involving data structures and algorithms.
Nice to Have
- Knowledge of AWS, Azure, or Google Cloud and their machine learning services.
- Knowledge of multimodal models.
- Knowledge of real-time streaming tools and architectures such as Kafka and Pub/Sub.
Skills
Python, PyTorch, Transformers, LangChain, LangGraph, Natural Language Processing, LLMs, Bert, Llama, Qwen, Docker, Kubernetes, AWS, Kafka, GCP
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