Senior Data scientist

Sigmund Analytics is seeking a Senior Data Scientist with expertise in Generative AI for our Bengaluru office. This role offers the opportunity to work on cutting-edge data science and machine learning problems across various industries. You will engage with clients to understand business contexts and apply your passion for solving complex, unstructured business challenges using data science and machine learning.

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 LLMs, retrieval-augmented generation (RAG), knowledge graphs, and multi-agent orchestration.
• Seamlessly embed 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 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 high sense of ownership.
• Ability to thrive in a fast-paced, deadline-driven environment.
• Passion for technology and highly skilled at data interpretation.
• Excellent problem-solving abilities.
• Proficiency in Python (TensorFlow, PyTorch, scikit-learn) and GenAI frameworks (LangGraph, AutoGen, OpenAI SDK, etc.).
• Expertise in prompt engineering on foundation models (OpenAI, HuggingFace, Anthropic, etc.).
• Knowledge of NLP, computer vision, or generative AI (LLMs, diffusion models, RAG, fine-tuning models, conversational AI, knowledge graphs).
• Familiarity with cloud AI services (AWS SageMaker, Azure ML, 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 (MLflow, Kubeflow, Airflow, Docker, Kubernetes).
• Experience with big data technologies (Spark, Hadoop, Databricks).
• Exposure to responsible AI frameworks and bias detection methods.
• Contributions to open-source AI/ML projects.

Desired Experience & Education:

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