R&D Director

Gartner, Inc.; Hartford; On-site; GBP 112,000 - 150,000; Full time

Job summary

A global technology advisory firm in Hartford seeks an Applied AI Research & Engineering Leader to define the AI division's technical roadmap. The role requires extensive experience in Machine Learning and managing technical teams, focusing on optimizing and deploying advanced AI models. The ideal candidate will lead a high-performing team, translating cutting-edge research into scalable solutions. This position plays a crucial role in driving innovation while adhering to industry best practices.

Qualifications

• 15+ years of hands-on experience in Machine Learning, Deep Learning, or AI Research.
• 5+ years of technical leadership experience managing a team.
• Proven experience building a commercial practice focused on Generative AI.

Responsibilities

• Set the multi-year technical roadmap for the AI platform.
• Design and optimize advanced deep learning and Generative AI models.
• Recruit, mentor, and manage a high-performing AI team.

Skills

Machine Learning

Deep Learning

AI Research

Technical Leadership

MLOps

Cloud-Based ML Services

Generative AI

Large Language Models

Education

Ph.D. or Master’s in Computer Science, Machine Learning, or related field

Tools

PyTorch

TensorFlow

Python

Spark

Ray

Job description

About Our Team

We are at the forefront of AI innovation, driving the core technical engine that powers our next generation of enterprise products. Our mission is to translate complex, cutting‑edge academic research into scalable, reliable, and commercially impactful solutions. We operate with the agility of a startup but with the resources of a global leader, fostering a culture of technical rigor, publication, and groundbreaking work.

The Opportunity

We are seeking an Applied AI Research & Engineering Leader to define the technical foundation and innovation roadmap for our entire AI division. This is a hands‑on, high‑impact technical leadership role for an individual who excels at merging deep academic research with production‑grade engineering. You will be responsible for leading a team of elite researchers and engineers, defining our core ML/AI research agenda, and ensuring the robust, scalable deployment of all novel algorithms into our production environment.

Responsibilities

• Set the multi‑year technical roadmap for the AI platform, prioritizing projects that solve critical, high‑complexity technical challenges such as model efficiency, interpretability, and real‑time inference.
• Design, implement, and optimize advanced deep learning, Generative AI, and Reinforcement Learning models from scratch, pushing the state‑of‑the‑art for our domain.
• Monitor and translate bleeding‑edge academic research and industry trends into rapid prototypes suitable for mission‑critical production deployment.
• Establish and enforce industry‑leading best practices for MLOps, ensuring automation, reproducibility, version control, and CI/CD for all models.
• Review, approve, and optimize the technical architecture for all deployed AI systems, ensuring they meet strict criteria for scalability, low latency, and fault tolerance.
• Drive research into optimizing computational costs for large models, including model compression, quantization, and efficient hardware utilization.
• Recruit, mentor, and manage a high‑performing team of Applied AI Scientists, Machine Learning Engineers, and Researchers.
• Foster a technically demanding and research‑driven culture, encouraging publication, patent filing, and open‑source contributions.
• Ensure all core AI codebases adhere to the highest standards of quality, documentation, and maintainability.

Qualifications

• 15+ years of hands‑on experience in Machine Learning, Deep Learning, or AI Research, with a focus on building and deploying complex models at scale.
• 5+ years of technical leadership experience managing a team of Data Scientists and ML Engineers.
• Expert‑level proficiency in core ML frameworks (e.g., PyTorch, TensorFlow) and data science languages (Python).
• Proven experience building a commercial practice or product focused on Generative AI and Large Language Models.
• Demonstrated expertise in at least two major AI domains (e.g., Deep Learning, NLP, Computer Vision).
• Track record of translating technical output into commercial results in a client‑facing or product‑focused role.
• Deep practical knowledge of MLOps principles and extensive experience with cloud‑native ML services (e.g., Google Cloud Vertex AI, AWS SageMaker, Azure ML).
• Ph.D. or Master’s degree in Computer Science, Machine Learning, or a highly quantitative field, OR equivalent demonstrated technical leadership experience.
• Strong portfolio of research publications (ICML, NeurIPS, KDD, etc.) or patents related to applied AI (preferred).
• Extensive experience with distributed computing frameworks (e.g., Spark, Ray) for large‑scale model training and inference.