Be the one building AI-powered experiences where they matter most.
At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.
Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.
Manager - AI/ML
The Team and Your Role
We're seeking a Manager to lead a team of AI Engineers and Data Scientists building, deploying, and operating machine learning and generative AI solutions that drive business outcomes. The team is primarily focused on AI Engineering and Data Science, with some software engineers supporting productionization and integration. You'll combine deep applied AI expertise with proven management skill to lead strategic initiatives, grow your people, and ensure AI solutions are delivered responsibly and effectively.
What You Will Do
Lead a small to mid-sized team of AI Engineers, Data Scientists, and software engineers; plan resourcing against timelines; and own hiring, performance reviews, coaching, and career development across both engineering and data science paths
Guide research teams that build, train, and deploy their own models, and teams that deliver solutions featuring LLMs and LAMs, from problem framing and experimentation through evaluation and production operation
Work on extremely complex problems requiring strong technical and quantitative skill, exercising independent judgment in developing methods and evaluation criteria across diverse data sets
Present results to upper management, explain difficult AI and data science concepts and tradeoffs to technical and non-technical audiences, and partner with stakeholders on matters affecting own and related teams
Required Skills & Experience
Bachelor's or Master's in Computer Science, Machine Learning, Data Science, Engineering, or related field (or equivalent), with 8-10 years of relevant experience including proven leadership of AI/ML or data science teams and the ability to direct and review the work of experienced professionals
Proven experience overseeing research teams that have built, trained, and deployed their own models into production, covering the full lifecycle from problem definition and dataset preparation through experimentation, evaluation, and operation
Direct experience overseeing teams that have built and deployed solutions featuring LLMs and/or LAMs through fine-tuning, distillation, and combining or adapting open-weight models, with supporting work in prompt and context engineering, retrieval-augmented generation, agentic workflows, and evaluation of generative systems
Strong grounding in machine learning and statistical methods, model development and evaluation, and the tradeoffs of deploying models at scale, with hands-on MLOps experience (experiment tracking, CI/CD for models, monitoring for drift and performance) and proficiency in Python and relevant frameworks (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face)
Ability to architect scalable, robust AI and data platforms on AWS (microservices, RESTful APIs, serverless, Kafka, GPU/compute infrastructure); manage technical projects through delegation and review; collaborate with cross-functional partners (PM, UX); and apply responsible AI practices for secure, reliable, fair AI behaviour
Desirable Skills & Experience
The following would be great additions but are not required:
Deep understanding of modern deep learning and generative AI architectures, large-scale training or fine-tuning, and model evaluation, safety, and alignment techniques
Publications, patents, open-source contributions, or a demonstrated history of taking novel research from idea to deployed product
Experience with data pipelines, feature…