Data Science/AI ML Engineer

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.

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

We're 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. You'll 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.

• Contribute to the design and implementation of specialised Large Language Models, working with model weights, attention mechanisms, and efficient sparse architectures. You'll 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. You'll 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. You'll 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. You'll 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 team's research agenda, and provide guidance to more junior team members where appropriate

• 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 Master's degree would reduce the experience requirement by 1–2 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

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 — we'll 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 aren't afraid to say "I don't know, but I'll figure it out."

You'll 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.

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About Genesys:

Genesys® empowers more than 8,000 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 www.genesys.com.

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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 expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.

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