Experience: 4+ years
Location: Remote – India
About the Role
We are looking for an experienced Data Scientist II with strong expertise in Machine Learning, NLP, LLMs, and Generative AI to build and deploy production-grade AI solutions. The ideal candidate should combine strong data science fundamentals with hands-on software engineering and experience taking ML/AI systems from experimentation to production.
Key Responsibilities
- Design, develop, and deploy scalable ML, NLP, LLM, and Generative AI solutions.
- Build AI applications using LLM APIs, agentic frameworks, RAG, embeddings, semantic search, and information extraction.
- Develop and optimize ML models for classification, prediction, clustering, and other business use cases.
- Work with LangChain, LangGraph, CrewAI, or similar agentic/LLM orchestration frameworks.
- Implement advanced LLM capabilities including tool calling, function calling, multi-turn conversations, and structured outputs.
- Design and work with vector databases and embedding systems such as Pinecone, Weaviate, FAISS, or similar.
- Build scalable backend services using Python, REST APIs, and asynchronous programming.
- Conduct experiments, formulate hypotheses, evaluate models, and perform rigorous analysis.
- Deploy and maintain AI/ML solutions using cloud platforms such as AWS, GCP, or Azure.
- Containerize applications using Docker and follow modern software development practices.
- Collaborate with engineering, product, and cross-functional teams to take solutions from research to production.
- Stay current with emerging developments in AI, LLMs, NLP, and ML research.
Required Skills
- 4+ years of experience in Data Science, Machine Learning, AI, or a related field.
- Bachelor's/Master's degree in Computer Science, Machine Learning, Statistics, Engineering, or a related technical discipline.
- Strong proficiency in Python and software engineering fundamentals including OOP, design patterns, testing, and Git.
- Strong hands-on experience with NLP, LLMs, Generative AI, and AI application development.
- Experience with LLM APIs such as OpenAI, Anthropic, or similar.
- Strong experience with at least one deep learning framework: PyTorch or TensorFlow.
- Hands-on experience with LangChain, LangGraph, CrewAI, or similar frameworks.
- Strong understanding of NLP concepts including Embeddings, Semantic search,Information extraction, Classification, Transformers
- Experience with multiple ML approaches such as Neural Networks, Transformers, SVM, Random Forest, Clustering, and Bayesian models.
- Experience building production ML/AI systems, from experimentation through deployment.
- Experience with REST APIs, asynchronous programming, and scalable backend services.
- Familiarity with vector databases and embedding technologies.
- Experience with cloud platforms and Docker.
- Strong analytical, experimental design, and problem-solving skills.
Good to Have
- Experience with voice/speech models and real-time audio processing, such as OpenAI Realtime API or similar.
- Knowledge of Model Context Protocol (MCP) and emerging LLM standards.
- Experience with MLOps, including model monitoring, versioning, A/B testing, and deployment pipelines.
- Contributions to open-source AI/ML projects or published research.
- Experience with streaming and event-driven systems such as Kafka or RabbitMQ.
- Experience with RAG architecture and production-grade AI agents.
What We’re Looking For
- Strong ownership and ability to take AI solutions from research → experimentation → production.
- Strong problem-solving ability and intellectual curiosity.
- Ability to work effectively in a remote, collaborative, and multidisciplinary environment.
- Passion for keeping up with rapidly evolving AI/LLM technologies.