Senior Data Scientist - LLM Expert

Who We Are

At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world's leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people-Kyndryls-that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive.

The Role

Are you ready to dive headfirst into the captivating world of data engineering at Kyndryl? As a Data Engineer, you'll be the visionary behind our data platforms, crafting them into powerful tools for decision-makers. Your role? Ensuring a treasure trove of pristine, harmonized data is at everyone's fingertips.

As a Data Engineer at Kyndryl, you'll be at the forefront of the data revolution, crafting and shaping data platforms that power our organization's success. This role is not just about code and databases; it's about transforming raw data into actionable insights that drive strategic decisions and innovation.

We're looking for exceptional talent to join our AI Agentic Innovation Hub at Kyndryl!

The AI Agentic Innovation Hub stands as Kyndryl's center of excellence for advanced and agentic artificial intelligence. Our mission is to lead the design and deployment of transformative AI solutions that bridge frontier research with real-world impact - scalable, secure, and driven by measurable value.
Built upon a team of exceptional talent and cutting-edge technology, the Hub embodies a spirit of bold innovation and disciplined execution - an elite unit within one of the world's leading technology companies. With national reach and global ambition, we partner with major organizations to tackle their most complex challenges, pioneering the next generation of intelligent, autonomous, and trusted systems that redefine what AI can achieve.

Job Description

As a Senior Data Scientist specialized in Large Language Models at Kyndryl's AI Innovation Hub, you'll help shape the frontier of intelligent and agentic systems - turning cutting-edge research into real-world impact for some of the world's most forward-thinking enterprises.
You'll work with state-of-the-art technologies, foundation models, and emerging agentic frameworks to design, fine-tune, and deploy powerful LLM-based solutions that understand, reason, and generate language with purpose.
In this role, you'll collaborate closely with architects, ML engineers, and product teams to transform ideas into production-ready systems that redefine how organizations interact with knowledge and automation.
You'll operate in an environment that values experimentation, precision, and creativity - where you'll be encouraged to explore the limits of generative AI, drive technical excellence, and contribute to solutions used by top global clients.
If you're passionate about transforming language models into intelligent agents that can think, act, and assist - this is where your work will make a lasting mark.

Your Mission

• Design, train, fine-tune, and evaluate large language models and their distilled or specialized variants (SLMs).

• Develop and integrate Generative AI and Agentic AI solutions that combine reasoning, retrieval, and language understanding.

• Implement and optimize RAG (Retrieval-Augmented Generation) pipelines, ensuring precision, traceability, and scalability.

• Collaborate with architects and ML engineers to bring LLM-based solutions into production environments.

• Define and apply robust evaluation frameworks and metrics for alignment, safety, hallucination control, and factual consistency.

• Contribute to the Hub's innovation roadmap by exploring new models, architectures, and methods for fine-tuning and instruction learning.

• Advise on model optimization, including quantization, distillation, and memory-efficient inference.

• Promote best practices in documentation, traceability, and Responsible AI across all LLM-based initiatives.

• 4+ years of experience in AI model development, with at least 2 years focused on LLMs or advanced NLP systems.

• Proven expertise in fine-tuning, instruction tuning, and evaluation of foundation models (GPT, Llama, Claude, Mistral, Gemma, etc.).

• Hands-on experience developing RAG pipelines and LLM-based reasoning architectures.

• Solid understanding of Python and major libraries for LLM and AI development (Transformers, LangChain, LlamaIndex, PEFT, BitsAndBytes, LoRA, Accelerate).

• Experience training or serving models on GPU/TPU environments (PyTorch, DeepSpeed, vLLM, Ollama).

• Strong background in vector databases and embedding models.

• Familiarity with multi-agent frameworks and orchestration systems (CrewAI, AutoGen, LangGraph, Google ADK).

• Knowledge of Responsible AI and evaluation principles - safety, bias mitigation, factual alignment, and model interpretability.

• Experience deploying models in MLOps environments (MLflow, Vertex AI, Azure ML, OpenShift AI).

• Bachelor's or Master's degree in Computer Engineering, Data Science, Mathematics, Computational Linguistics, or related field.

• Postgraduate studies (Master's or PhD) in Natural Language Processing (NLP), Deep Learning, or Artificial Intelligence are highly valued.

• Additional training in Generative AI, Prompt Engineering, or Responsible AI is a plus.

• Demonstrated commitment to continuous learning and staying current with the latest research in LLMs and generative AI.

• Expertise in prompt optimization, context management, and hallucination detection/mitigation.

• Understanding of LLMOps practices and observability tools for model monitoring and evaluation.

• Experience with distillation, quantization, and efficient inference strategies for scaling LLMs in production.

• Familiarity with semantic search, retrieval frameworks, and knowledge-grounded generation.

• Background in reinforcement learning from human feedback (RLHF) or preference optimization.

• Ability to analyze research papers, prototype rapidly, and transfer innovation into production-ready systems.

• Comfort working with hybrid architectures, integrating models across cloud and on-premise environments.

• Clear and articulate communicator, able to explain complex model behavior and design choices to diverse audiences.

• Analytical and experimental mindset, combining scientific rigor with creativity and problem-solving agility.

• Collaborative and cross-functional approach, working closely with architects, engineers, and designers to deliver cohesive AI solutions.

• Curiosity and innovation-driven attitude, always exploring new models, datasets, and emerging techniques in the LLM space.

• Business awareness, able to translate functional requirements into measurable AI outcomes.

• Commitment to quality and reproducibility, ensuring experiments, metrics, and models are well-documented and traceable.

• Adaptability and growth mindset, embracing continuous learning in the rapidly evolving world of generative AI.