Senior Data scientist

Sigmoid Analytics is seeking a Senior Data Scientist specializing in Generative AI for its Bengaluru office. This role involves working on cutting-edge data science and machine learning problems across various industries, requiring client engagement to understand business contexts. If you are passionate about solving complex, unstructured business problems using advanced data science and machine learning techniques, we encourage you to apply.

Responsibilities:

• Architect, develop, and deploy machine learning models and AI solutions into 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 for optimal performance.
• Stay updated on 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 GenAI frameworks like LangGraph, AutoGen, and OpenAI SDK, including prompt engineering on foundation models from OpenAI, HuggingFace, and Anthropic.
• Knowledge of Natural Language Processing (NLP), computer vision, or generative AI concepts (LLMs, diffusion models, RAG, fine-tuning models, conversational AI, 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 (APIs, microservices, real-time inference).

Nice-to-Have:

• Experience with MLOps tools such as MLflow, Kubeflow, Airflow, Docker, and Kubernetes.
• Experience with big data technologies including Spark, Hadoop, and 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.
• Bachelor's degree (B.Tech) from a Tier-1 college, or a Master's degree (M.S. or M.Tech) in Computer Science, Information Technology, or a related field is preferred.