Lead Data Scientist

• Advanced Python proficiency with hands-on experience in PyTorch or TensorFlow for model development, training, and large-scale experimentation
• Strong knowledge of Generative AI and NLP, including transformer models, LLMs (GPT-4, Claude, Gemini), and fine-tuning methodologies for domain-specific applications
• Experience with agentic AI frameworks such as LangGraph or CrewAI, as well as knowledge of multi-agent system design and autonomous decision-making patterns
• Proven track record of deploying AI/ML solutions to major cloud providers (Azure, AWS, GCP) and managing the full ML lifecycle at production scale
• Demonstrated experience leading or mentoring Data Science or ML teams, with the ability to drive technical vision and embed engineering best practices
• Strong client-facing skills, with experience shaping AI strategies and communicating complex concepts to executive and non-technical stakeholders
• Master’s or Ph.D. degree in Computer Science or a related field
• Upper-intermediate or higher proficiency in English, both spoken and written

ABOUT THE ROLE

In this role, you will define technical direction and lead the delivery of advanced Generative AI and agentic solutions, from multi-agent systems to large-scale NLP pipelines, within SoftServe’s AI and Data Science Center of Excellence, a team of 170+ experts, including Data Scientists, ML Engineers, and Architects. You’ll drive innovation, shape AI strategy for world-leading clients, and ensure solutions scale from prototype to measurable production impact.

,[Define and drive technical vision for AI initiatives using the latest generative AI and agentic frameworks, ensuring alignment with business goals and accelerating innovation across cross-functional teams, Advance agentic AI capabilities by designing and implementing multi-agent systems using LangGraph, CrewAI, or similar frameworks to enable autonomy and real-world problem-solving at scale, Foster strong client relationships by identifying opportunities, shaping AI strategies, and translating complex technical concepts into impactful, production-ready solutions, Build and deploy production-ready AI/ML solutions on major cloud platforms, reducing operational risks and ensuring reliability through close collaboration with MLOps and DevOps teams, Establish and optimize end-to-end AI development processes — from data pipelines and model training to LLMOps, monitoring, and continuous improvement, Mentor and guide Data Scientists and ML Engineers, embedding best practices in Generative AI, MLOps, and engineering excellence, Contribute to thought leadership through technical publications, case studies, and participation in industry events and conferences] Requirements: Python, AI, NLP, Cloud, Data science, GenAI