Senior Manager, Applied AI Research

The role

You will provide hands-on technical leadership for applied AI initiatives including Small Language Models, reinforcement learning, and computer vision. You will manage a team of 3-5 Research Engineers to deliver AI models from problem framing to production deployment.

What you will do

• Provide hands-on technical leadership across multiple applied AI workstreams.
• Drive architecture, modeling choices and productionization decisions.
• Manage, mentor and grow a small team of 3-5 Research Engineers.
• Prototype novel approaches and review model designs.
• Guide training-run debugging on GPU clusters.
• Own the full applied-AI lifecycle from data strategy to deployment.
• Partner with Platform, MLOps and Product Engineering teams.
• Translate business and security priorities into an applied-AI roadmap.
• Communicate trade-offs to senior leadership.
• Establish team practices for experiment tracking, evaluation and responsible AI.

Required qualifications

• M.Sc. or Ph.D. in Computer Science, Machine Learning, Mathematics or a related quantitative field, or equivalent practical experience with demonstrable deep-learning expertise.
• 5+ years of hands-on experience building and deploying machine-learning and deep-learning systems in production.
• 2-3+ years of experience leading or managing a small team of ML / Research Engineers.
• Deep hands-on expertise across several applied-AI areas, such as modern transformer-based Small Language Models, reinforcement learning, agentic / tool-using LLM systems, computer vision or classical
• Expert proficiency in Python and PyTorch.
• Experience training and fine-tuning models on multi-GPU clusters using frameworks such as DeepSpeed, FSDP or Hugging Face Accelerate.
• Strong mathematical foundation in linear algebra, optimization, probability and statistics.
• Proven track record of taking AI models to production including data pipelines, evaluation, quantization, deployment using containers, Kubernetes and cloud, and monitoring.
• Experience with MLOps and experiment-management tooling such as Weights & Biases, MLflow or similar.
• Experience with modern software-engineering practices including CI/CD, code review and observability.
• Fluent English.

Nice to have

• Publications at top-tier ML venues such as NeurIPS, ICML, ICLR, ACL or CVPR.
• Applied-AI experience in cybersecurity, privacy or identity.
• Experience with JAX or TensorFlow.

Benefits

• Flexible working options
• Time off
• Competitive pay
• Benefits
• Well-being programs

Before you apply

• An interview with the Hiring Manager.
• A technical interview with senior members of the AI Research Lab.
• A cross-functional discussion with Product and stakeholder partners.
• A final conversation with Leadership.

About the company

Gen is a global company dedicated to powering Digital Freedom through brands including Norton, Avast, LifeLock, and MoneyLion. They deliver cybersecurity, online privacy, identity protection and financial wellness solutions to nearly 500 million users.