Associate lead Data Scientist

Astar Data; Bengaluru; Hybrid; INR 2,500,000 - 4,200,000; Full time

Job summary

Sigmoid Analytics in Bengaluru seeks an experienced ALDS to tackle a broad range of data science and ML problems across industries. You will engage with clients to understand business context and translate it into AI-driven outcomes.

You will work on end-to-end design and deployment of scalable AI/ML solutions, mentor junior AI engineers, and collaborate with teams to push the boundaries of what-is-possible.

Qualifications

• 5-8 years of experience in AI/ML engineering with leadership exposure.
• Strong programming background in Python and ML frameworks.

Responsibilities

• End-to-end design and deployment of scalable AI/ML solutions in production.
• Develop and optimize LLM applications using LangChain, LlamaIndex, Haystack.
• Drive Retrieval-Augmented Generation pipelines with vector databases.
• Collaborate with data scientists to transition research models to production.
• Build MLOps pipelines for training, testing, deployment, monitoring, and retraining.
• Architect AI solutions integrated into enterprise apps via APIs and microservices.
• Stay updated on AI research and evaluate new frameworks for adoption.
• Mentor junior AI engineers and promote best practices in AI engineering.
• Translate business requirements into AI-driven outcomes.
• Ensure responsible AI practices, bias mitigation, fairness, and explainability.

Job description

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We are best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You will work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.

Offices

New York | Dallas | San Francisco | Lima | Bengaluru

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 to work 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

• 3.5- 5 years of relevant Machine Learning experience.