Senior Data scientist

We are seeking a Senior Data Scientist with a specialization in Generative AI to join our team. In this role, you will address a wide array of cutting-edge data science and machine learning challenges across various industries. You will collaborate with clients to understand their business needs and develop data-driven solutions for complex, unstructured business problems. This position is for our Bengaluru office.

Responsibilities:

• Architect, develop, and deploy machine learning models and AI solutions into live production environments.
• Collaborate with data scientists to transform prototypes into scalable, enterprise-ready applications.
• Design and implement enterprise AI systems utilizing Large Language Models (LLMs), retrieval-augmented generation (RAG), knowledge graphs, and multi-agent orchestration.
• Seamlessly integrate AI models into existing products, APIs, and broader enterprise systems.
• Conduct rigorous experimentation, fine-tuning, and error analysis to enhance model accuracy and reliability.
• Continuously monitor, maintain, and retrain deployed models to ensure optimal performance.
• Stay updated with the latest advancements in AI/ML, MLOps practices, and cloud-native AI technologies.
• Partner with stakeholders to translate business challenges into effective AI-driven solutions.
• Uphold ethical standards and responsible AI principles throughout the AI lifecycle.

Desired Skills & Competencies:

• Strong learning acumen and a high sense of ownership.
• Ability to thrive in a fast-paced, deadline-driven environment.
• Passion for technology and highly skilled in data interpretation.
• Proven problem-solving abilities.
• Strong programming skills in Python, utilizing libraries such as TensorFlow, PyTorch, and scikit-learn.
• Proficiency in Generative AI frameworks (e.g., LangGraph, AutoGen, OpenAI SDK) and prompt engineering on foundation models (e.g., OpenAI, HuggingFace, Anthropic).
• Knowledge of Natural Language Processing (NLP), computer vision, or generative AI concepts, including LLMs, diffusion models, RAG, model fine-tuning, conversational AI, and knowledge graphs.
• Familiarity with cloud AI services (e.g., AWS SageMaker, Azure ML, GCP Vertex AI).
• Solid understanding of data structures, algorithms, and software engineering principles.
• Hands-on experience with model deployment, including APIs, microservices, and real-time inference.

Nice-to-Have:

• Experience with MLOps tools like MLflow, Kubeflow, Airflow, Docker, and Kubernetes.
• Experience with big data technologies such as Spark, Hadoop, or Databricks.
• Exposure to responsible AI frameworks and bias detection methods.
• Contributions to open-source AI/ML projects.

Desired Experience & Education:

• 2 to 3.5 years of relevant Machine Learning experience.
• B.Tech from a Tier-1 college or an M.S. or M.Tech degree in Computer Science, Information Technology, or a related field is preferred.