Senior Data Scientist

Sigmoid is a Sequoia backed data solutions company working across data science, data engineering and data ops for large enterprise clients. This role sits at the applied end: taking machine learning and AI from prototype into live production, building enterprise AI systems with LLMs, retrieval augmented generation, knowledge graphs and multi agent orchestration, and embedding models into existing products and APIs. It also covers the unglamorous half that matters, monitoring, retraining and error analysis to keep deployed models working. The stack named is Python with TensorFlow, PyTorch and scikit-learn, GenAI frameworks including LangGraph, AutoGen and the OpenAI SDK, and cloud AI services across SageMaker, Azure ML and Vertex AI. At 3 to 5 years it is one of the more reachable AI roles in this edition. Hyderabad, and the role is client facing.

Required by the posting: 3 to 5 years of relevant Machine Learning experience. Strong programming in Python with TensorFlow, PyTorch and scikit-learn, plus GenAI frameworks such as LangGraph, AutoGen and the OpenAI SDK, and prompt engineering on foundation models from OpenAI, Hugging Face and Anthropic. Knowledge of NLP, computer vision or generative AI covering LLMs, diffusion models, RAG, model fine tuning, conversational AI and knowledge graphs. Familiarity with cloud AI services including AWS SageMaker, Azure ML and GCP Vertex AI. Solid understanding of data structures, algorithms and software engineering principles. Hands on experience with model deployment through APIs, microservices and real time inference.

Nice to have: experience with MLOps tools including MLflow, Kubeflow, Airflow, Docker and Kubernetes, and experience with big data technologies such as Spark and Hadoop.

The real day to day: architecting, developing and deploying machine learning models and AI solutions into live production; partnering with data scientists to convert prototypes into scalable enterprise ready applications; designing enterprise AI systems using LLMs, RAG, knowledge graphs and multi agent orchestration; embedding AI models into existing products, APIs and enterprise systems; running experimentation, fine tuning and error analysis to improve model accuracy; monitoring, maintaining and retraining deployed models; translating business challenges into AI solutions with stakeholders; and upholding responsible AI principles.

Client facing reality: the posting states you will be engaging with clients to understand their business context, and Sigmoid's work is consulting shaped for large enterprises. Its other postings note openness to working from a client location depending on the project, so ask about that during interviews.

Location: Hyderabad. Sigmoid's Greenhouse metadata for this requisition records a minimum of 3 and a maximum of 5 years, which matches the body text, so the band here is reliable.

Honest fit guidance: the job title says Data Scientist but the responsibilities are mostly ML engineering and deployment, not research or analysis. If you enjoy getting models into production and keeping them healthy, that is a good thing. If you want to spend your time on modelling and experimentation, read the responsibilities list again before applying.