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 8000 organizations in over 100 countries moving AI from possibility to production in real-world enterprise environments every day.

AI/ML Engineer

The Team and Your Role

Were a research-driven team pushing the boundaries of whats possible with Large Language Models. Our work sits at the intersection of applied ML research and production engineering were not just consuming off-the-shelf models were building our own. Were developing novel approaches to create specialised LLMs that deliver commercial-grade intelligence at a fraction of the cost of frontier API models.

Were looking for a AI/ML Engineer who gets excited about model internals someone who thinks in terms of tensor operations architecture design and weight spaces rather than just prompt templates. Youll join a collaborative diverse team where research ideas move quickly from paper to prototype to production and where your contributions will directly shape the architecture of next-generation AI systems used by millions.

What You Will Do

• Contribute to the design and implementation of specialised Large Language Models working with model weights attention mechanisms and efficient sparse architectures. Youll help translate research papers into working implementations under the guidance of senior team members.
• Participate in the lifecycle from research spike through to deployable artefact reading papers prototyping in notebooks building reusable Python libraries and deploying on GPU-accelerated cloud infrastructure. Youll work with tools like PyTorch HuggingFace Transformers and AWS SageMaker regularly.
• Help build and maintain evaluation frameworks to compare model variants across intelligence reasoning capability and inference cost. Youll run experiments contribute to comparison tooling and help present findings to stakeholders.
• Support and extend the cloud infrastructure (AWS CloudFormation SageMaker S3 GPU instances) that powers our experimentation and model serving. Youll contribute to optimising for both research velocity and cost efficiency.
• Engage with the open-source ML ecosystem leveraging established toolkits for model development and evaluation.
• Actively participate in design discussions contribute ideas to the teams research agenda and provide guidance to more junior team members where appropriate

Required Skills & Experience

• Degree in Computer Science Machine Learning Mathematics or a related quantitative field (or equivalent hands-on experience). 3 years in ML engineering with at least 1 year working directly with LLMs or deep learning model architectures. A relevant Masters degree would reduce the experience requirement by 12 years.
• Good understanding of transformer architectures attention mechanisms and model internals. You should be able to reason about parameter counts tensor shapes and how architectural choices affect model behaviour and be eager to deepen this knowledge further.
• Solid proficiency in Python with hands-on experience in PyTorch. Familiarity with HuggingFace Transformers tokenizers model loading/saving and awareness of the broader open-weight model ecosystem (Llama Mistral DeepSeek and similar model families).
• Familiarity with AWS services for ML workloads SageMaker (Notebooks/Studio) EC2 GPU instances and S3 for model storage. Exposure to CloudFormation or other IaC tooling is a plus.
• Clean code practices Git workflows CI/CD (Jenkins or similar) unit testing and the ability to write well-structured Python code not just notebooks

Desirable Skills & Experience

The following would strengthen your application but are not required:

• Exposure to sparse architectures expert routing conditional computation or techniques for adapting and combining pre-trained models to create new specialised variants.
• Awareness of quantization (GPTQ AWQ bitsandbytes) model compression or distributed inference strategies for running large models efficiently.
• Experience with CloudFormation Terraform or similar tools for reproducible ML infrastructure deployments.
• Familiarity with the contact centre industry conversational AI or agentic AI systems is a plus but not essential well teach you the domain.
• An awkward sense of humour and a genuine love for digging into model internals. We value curiosity intellectual honesty and people who arent afraid to say I dont know but Ill figure it out.

What We Offer

Youll work on genuinely novel research not incremental improvements to existing systems but new approaches to building LLMs that could reshape how the industry thinks about model development and cost optimisation. Your work will directly influence AI systems used by millions of people globally.

We offer clear paths toward technical leadership the freedom to explore research directions and a team culture built on mutual respect psychological safety and the belief that the best ideas come from diverse perspectives. Remote-friendly with flexible working arrangements and a genuine commitment to work-life balance.

Genesys is committed to diversity and inclusion. We welcome applications from all qualified candidates regardless of background.

#LI-MC1

Working at Genesys

• AI at enterprise scale Build support and operate AI-powered technology used by more than 8000 organizations worldwide. 150new AI features were released in the last fiscal year.
• A flexible-first culture Join a global team of nearly 7000 employees with flexible ways of working designed to help people do their best work.
• Growth in the AI era Build future-ready skills through mentorship learning programs leadership development and education support.
• Time to recharge and give back Benefits include paid volunteer time August Free Fridays well-being resources and regionally tailored programs for employees and their families.
• Recognized globally Genesys is Great Place to Work certified in 17 countries and 94% of employees are proud to tell others they work at Genesys.

Learn more about our culture AI innovation and sustainability commitments through our Careers site and Sustainability Report.

What Happens After You Apply

After you apply heres what you can typically expect:

• Our Talent Acquisition team reviews your application with the hiring team.

• A Talent Acquisition Partner will review your application and if your background is aligned schedule a Zoom interview.

• Next youll meet the hiring manager and other members of the interview team.

• We aim to keep the process focused and respectful of your time with no more than five interviews in most cases.

• After interviews are complete our team will follow up with the final steps.

Every application is reviewed by a person. Response times may vary by role and location but our team will keep you informed throughout the process.

Stay Connected

Stay connected to learn more about how were applying AI to customer and employee experience challenges and get notified when relevant opportunities become available.

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Be the one building whats next - where AI experience and impact come together.

Employee Referral

If a Genesys employee referred you please apply using the link they shared so we can connect your application to their referral.

About Genesys:

Genesys empowers more than 8000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core Genesys Cloud is the AI-Powered Experience Orchestration platform that connects people systems data and AI across the enterprise. As a result organizations can drive customer loyalty growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more visit.

Reasonable Accommodations:

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Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race color age religion sex sexual orientation gender identity or expressionmarital status domestic partner statusnational origin genetics disabilitymilitary andveteran status and other protected characteristics.

Please note that recruiters will never ask for sensitive personal or financial information during the application phase.