Senior Machine Learning Developer

Summary

Join Coveo as a Senior Machine Learning Developer in R&D and play a key role in supporting applied scientists by building reliable, scalable, and maintainable ML systems. You will help streamline the ML model development lifecycle, analyze and improve model and system performance, maintain client-facing features, and facilitate the adoption of ML platform resources. This role involves collaborating with scientists, improving operational efficiency, and evolving our modern tech stack. The ideal candidate has 5+ years of ML industry experience, operationalized AI models at scale, and is fluent in data and software engineering practices. The position offers the opportunity to work on innovative solutions in e-commerce and other business verticals using cutting-edge technologies.

Requirements

• You have 5+ years of Machine Learning industry experience
• You have operationalized, instrumented and supported AI models in production at a non-trivial scale before
• You are fluent in good data and software engineering practices, and you are able to develop the tools and culture which enable your team to deliver reliable production code in an efficient manner
• You enjoy collaborating with scientists on a daily basis to understand their pain points and figure out how to improve their tools and increase their efficiency. You also have experience working in cross-functional teams

Responsibilities

• Help streamline the development life cycle of ML models: conception, implementation, automated testing, deployment, monitoring, etc
• Analyze and improve the performance of our models and systems – including meeting critical SLOs for training models at scale and low-latency inference
• Maintain and improve several of our most important client-facing product features
• Facilitate the adoption and utilization of ML platform and observability resources and guidelines to improve operational efficiency and service reliability
• Engage with your community of peers to challenge the status quo, improve our shared ways of working, and influence overall architecture decisions
• Learn and evolve our modern tech stack which includes Python, AWS, Kubernetes, Pytorch, Terraform, Snowflake, Honeycomb and others

Preferred Qualifications

• You master best practices in ML-Ops, ML engineering, and large-scale deployment of ML models
• You are familiar with Data Lifecycle in ML and helped structure the data logic in ML projects before
• You have experience maintaining and evangelizing internal resources and libraries
• You are savvy in specific ML domains such as Natural Language Processing, Information Retrieval, Recommendation Systems, and the technical implications of building pipelines for such use cases
• You are recognized for your communication skills and presenting complex technical subjects to audiences with different levels of technical proficiency