Middle Data Scientist (Generative AI)

In this role, you will develop and apply Generative AI and machine learning solutions — from NLP pipelines and RAG applications to agentic workflows — as part of SoftServe's AI and Data Science Center of Excellence, a team of 170+ experts, including Data Scientists, ML Engineers, and Architects. Working alongside experienced researchers and engineers, you'll contribute to data-driven projects that deliver measurable impact for clients.

Responsibilities

• Implement and contribute to Generative AI and agentic solutions — including RAG pipelines, intelligent assistants, and NLP applications — working alongside senior team members
• Build and maintain ML pipelines covering data analysis, experiment design, model training, and deployment, supporting reliability and reproducibility in production
• Collaborate with Data Scientists, Engineers, and stakeholders to understand requirements and contribute to production-ready ML solutions across diverse client projects
• Contribute to agentic workflows using frameworks such as LangGraph or CrewAI, supporting the development of multi-agent systems and autonomous AI applications
• Apply deep learning techniques in Python with PyTorch or TensorFlow to experiment, prototype, and iterate on solutions across NLP and generative AI domains
• Work with Big Data tools and cloud platforms (AWS, GCP, or Azure) to support data-driven experimentation, feature engineering, and analysis tasks
• Document and communicate experimental findings, translating data-driven insights into clear, actionable conclusions for both technical and non-technical audiences

• At least 3 years of experience in data science or machine learning, with hands-on exposure to building and experimenting with ML models
• Master's degree in Computer Science or a related field
• Solid Python proficiency with experience in PyTorch or TensorFlow for model development and experimentation
• Foundational knowledge of Generative AI and NLP techniques, including transformer models and LLMs such as GPT or Claude
• Familiarity with agentic AI concepts and frameworks, such as LangGraph or CrewAI, for building multi-agent applications
• Exposure to cloud-based AI/ML services on AWS, Azure, or GCP, and understanding of the ML development lifecycle
• Familiarity with Big Data tools and data processing in cloud environments
• Strong analytical and communication skills
• Upper-intermediate or higher proficiency in English, both spoken and written