Job Title

We seek an experienced Principal Data Scientist to lead our data science team and drive innovation in machine learning, advanced analytics, and Generative AI. This role blends strategic leadership with deep technical expertise across ML engineering, LLMs, deep learning, and multi-agent systems. You will be at the forefront of deploying AI-driven solutions, including agentic frameworks and LLM orchestration, to tackle complex, real-world problems at scale.Primary Stack: Languages: Python, SQL Cloud Platforms: AWS or GCP preferred ML & Deep Learning: PyTorch, TensorFlow, Scikit-learn GenAI & LLM Toolkits: Hugging Face, LangChain, OpenAI APIs, Cohere, Anthropic Agentic & Orchestration Frameworks: LangGraph, CrewAI, Agno, Autogen, AutoGPT Vector Stores & Retrieval: FAISS, Pinecone, Weaviate MLOps & Deployment: MLflow, SageMaker, Vertex AI, Kubeflow, Docker, Kubernetes, Fast APIKey Responsibilities: Lead and mentor a team of 10+ data scientists and ML engineers, promoting a culture of innovation, ownership, and cross-functional collaboration. Drive the development, deployment, and scaling of advanced machine learning, deep learning, and GenAI applications across the business. Build and implement agentic architectures and multi-agent systems using tools like LangGraph, CrewAI, and Agno to solve dynamic workflows and enhance LLM reasoning capabilities. Architect intelligent agents capable of autonomous planning, decision-making, tool use, and collaboration. Leverage LLMs and transformer-based models to power solutions in NLP, conversational AI, information retrieval, and decision support. Develop and scale ML pipelines on cloud platforms, ensuring performance, reliability, and reproducibility. Establish and maintain MLOps processes (CI/CD for ML, monitoring, governance) and ensure best practices in responsible AI. Collaborate with product, engineering, and business teams to align AI initiatives with strategic goals. Stay ahead of the curve on AI/ML trends, particularly in the multi-agent and agentic systems landscape, and advocate for their responsible adoption. Present results, insights, and roadmaps to senior leadership and non-technical stakeholders in a clear, concise manner.Qualifications: 9+ years of experience in data science, business analytics, or ML engineering, with 3+ years in a leadership or principal role. Demonstrated experience in architecting and deploying LLM-based solutions in production environments. Deep understanding of deep learning, transformers, and modern NLP. Proven hands-on experience building multi-agent systems using LangGraph, CrewAI, Agno, or related tools. Strong grasp of agent design principles, including memory management, planning, tool selection, and self-reflection loops. Expertise in cloud-based ML platforms (e.g., AWS SageMaker, GCP Vertex AI) and MLOps best practices. Familiarity with retrieval-augmented generation (RAG) and vector databases (e.g., FAISS, Pinecone). Excellent communication, stakeholder engagement, and cross-functional leadership skills.