About this role
The candidate will develop and apply Generative AI and machine learning solutions, including NLP pipelines and RAG applications, as part of SoftServe's AI and Data Science Center of Excellence. Responsibilities include implementing agentic workflows using frameworks like LangGraph or CrewAI and building/maintaining ML pipelines for production. The role involves working with deep learning frameworks like PyTorch or TensorFlow and cloud platforms such as AWS, GCP, or Azure. The person will collaborate with a Data Scientists, Engineers,0 and Architects within a team of 170+ experts to deliver data-driven projects for diverse clients.
Skills & technologies
Must have
- Python
- PyTorch
- TensorFlow
- Generative AI
- NLP
- LLM
- RAG
- LangGraph
- CrewAI
- Transformer models
- AWS
- Azure
- GCP
- Big Data
Read full description
About The Role
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
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
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