Associate Lead Data Scientist

Sigmoid; Hyderabad; On-site; INR 1,500,000 - 2,200,000; Full time

Job summary

Sigmoid is seeking an experienced AI/ML engineer to tackle a broad set of data science problems across industries. You will engage clients to understand their business context and design scalable AI solutions that transform unstructured data into actionable outcomes.

Role emphasizes building robust ML/MLOps pipelines, deploying LLM applications, and collaborating with cross-functional teams to productionize models while upholding responsible AI principles.

Qualifications

• 5–8 years of experience in AI/ML engineering, with at least 2 years in leading AI initiatives.
• Strong expertise in Python, TensorFlow, PyTorch, Hugging Face Transformers.
• Hands-on experience with LangChain or similar LLM application frameworks.
• Solid understanding of vector databases, RAG architectures, and prompt engineering.
• Proficiency in MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).
• Familiarity with cloud AI platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
• Strong background in data pipelines, APIs, and scalable system design.

Responsibilities

• Design and deploy end-to-end AI/ML solutions in production environments.
• Develop and optimize LLM applications using LangChain and similar frameworks.
• Drive RAG pipelines with vector databases like Pinecone, FAISS, Weaviate, Milvus.
• Collaborate with data scientists to transition models from research to production.
• Build and manage MLOps pipelines for training, testing, deployment, monitoring, retraining.
• Architect AI solutions via APIs and microservices in enterprise contexts.
• Stay updated on AI research and assess new frameworks for adoption.
• Mentor junior engineers and promote best practices in AI engineering.
• Translate business requirements into AI-driven outcomes.
• Ensure responsible AI practices including bias mitigation and explainability.

Skills

Python

TensorFlow

PyTorch

Hugging Face Transformers

LangChain

Vector databases

Prompt engineering

Education

Master’s Degree in Engineering/CS/Math/ML or related

Tools

MLflow

Kubeflow

Airflow

Docker

Kubernetes

Job description

About the Role

You will work on a broad range of cutting‑edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate about working on complex unstructured business problems that can be solved using data science and machine learning, we would like to talk to you.

Role: ALDS

Mandate, Skills & Competencies

• Work on the end‑to‑end design and deployment of scalable AI and machine learning solutions in production environments.
• Develop and optimize large language model (LLM) applications using frameworks such as LangChain, LlamaIndex, and Haystack.
• Drive Retrieval‑Augmented Generation (RAG) pipelines with vector databases like Pinecone, FAISS, Weaviate, and Milvus.
• Collaborate closely with other data scientists to transition models smoothly from research to production.
• Build and manage comprehensive MLOps pipelines encompassing training, testing, deployment, monitoring, and retraining.
• Architect AI solutions integrated into enterprise applications via APIs and microservices.
• Stay updated on AI and Generative AI research, continually assessing emerging frameworks for adoption.
• Mentor junior AI engineers and promote a culture of best practices in AI engineering.
• Work with business stakeholders to translate requirements into AI‑driven outcomes.
• Ensure adherence to responsible AI principles, including bias mitigation, fairness, and explainability.

Must‑Have

• 5–8 years of experience in AI/ML engineering, with at least 2 years in leading AI initiatives.
• Strong expertise in Python, TensorFlow, PyTorch, Hugging Face Transformers.
• Hands‑on experience with LangChain or similar LLM application frameworks.
• Solid understanding of vector databases, RAG architectures, and prompt engineering.
• Proficiency in MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).
• Familiarity with cloud AI platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
• Strong background in data pipelines, APIs, and scalable system design.

Nice‑to‑Have

• Experience fine‑tuning LLMs (LoRA, PEFT, parameter‑efficient training).
• Knowledge of computer vision or multimodal AI.
• Familiarity with responsible AI frameworks and explainability tools (SHAP, LIME, Captum).
• Contributions to open‑source AI projects.

Desired Experience & Education

• 4–8 years of relevant Machine Learning experience.
• Minimum Master’s Degree in Engineering, Computer Science, Mathematics, Computational Statistics, Operations Research, Machine Learning or related technical fields.