Why This Job is Featured on The SaaS Jobs
Machine learning roles in SaaS become most consequential when they connect research output to dependable product behaviour. This position sits in that translation layer, focusing on production systems that support experimentation while also meeting the reliability expectations of enterprise software. The emphasis on low latency inference, monitoring, and client facing ML features reflects the realities of shipping ML inside a commercial platform rather than a lab environment.
For a SaaS career, the durable value here is exposure to the full operational lifecycle of models, including deployment, observability, performance tuning, and platform adoption. Those are the skills that tend to travel well across SaaS companies because they map to recurring needs: keeping ML services stable, measurable, and cost aware as usage grows. Working closely with applied scientists also builds the cross functional judgement needed to turn prototypes into maintainable systems.
This role is best suited to someone who enjoys engineering work at the intersection of product and infrastructure, and who prefers measurable system outcomes over purely exploratory modelling. It will fit a developer who is comfortable collaborating to improve shared tooling and who wants to deepen practical MLOps habits in a cloud and Kubernetes oriented environment.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Build what brings AI to life at scale
How do you turn AI research into production-ready systems that perform reliably at scale? As a Machine Learning Developer, you will support applied scientists by building robust, scalable systems that accelerate experimentation and power real-world products.
You will work with the latest advances in machine learning to build and improve solutions for enterprise commerce, self-service, and other business-critical use cases at Coveo.
As one of our Machine Learning Developers, you will:
Contribute to the end-to-end lifecycle of machine learning models, from implementation to testing, deployment, and monitoring.
Analyze and improve the performance of machine learning models and systems, supporting large-scale training and low-latency inference.
Maintain and improve client-facing product features powered by machine learning.
Support the adoption of machine learning platforms, observability tools, and best practices to improve efficiency and reliability.
Collaborate with peers to explore new approaches and continuously improve how we build and operate systems.
Here is what will qualify you for the role:
2+ years of industry experience working with machine learning systems.
Hands-on experience deploying, monitoring, and supporting artificial intelligence (AI) models in production.
A collaborative mindset: you enjoy working closely with scientists to understand their challenges and improve their tools and workflows.
Experience working with Python, Amazon Web Services (AWS), Kubernetes, or other relevant technologies.
What will make you stand out:
Experience in machine learning operations (MLOps), machine learning engineering, or large-scale model deployment.
Experience working with data pipelines and structuring data workflows for machine learning projects.
Experience contributing to shared internal tools or libraries.
Knowledge of domains such as natural language processing (NLP), information retrieval, or recommendation systems.
Do you think you can bring this role to life? Or add your own color?You don’t need to check every single box; passion goes a long way and we appreciate that skillsets are transferable.
Send us your application, we want to hear from you!
Join the Coveolife!
We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background.
This job description was written by humans, assisted by AI. We may leverage technology in our hiring process to help us see the person behind the resume.
Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.#li-hybrid
