Senior Machine Learning Engineer

Summary

Join ecobee, a rapidly growing global tech company, as a Senior Machine Learning Engineer. You will be part of the Data Science Chapter, building intelligent and personalized features for ecobee products. This role involves the full ML development lifecycle, from problem framing to productionization, working with large-scale datasets and collaborating with cross-functional teams. You will leverage your expertise to mentor other engineers and drive best practices. The ideal candidate possesses a graduate degree or equivalent experience in a quantitative field, along with extensive experience in machine learning and software engineering. ecobee offers a dynamic work environment, competitive benefits, and opportunities for professional growth.

Requirements

• Graduate degree (Masters/PhD) or equivalent experience in Statistics, Mathematics, Computer Science or another quantitative field
• 3+ years’ experience applying machine learning to real world problems with expertise in manipulating data sets, building statistical models, and productizing machine learning solutions
• Proven software engineering skills across multiple languages such as Python, C/C++ and ML packages
• Experience with deep learning architectures and frameworks (e.g. Pytorch, Tensorflow)
• Experience working with data at scale (1TB+), leveraging big data processing frameworks like Spark and Google Cloud Dataflow
• 3+ years experience with software engineering and DevOps practices, MLOps deployment and infrastructure
• Strong understanding of Scrum/Agile development technologies
• Skilled communicator with a proven record of leading work across disciplines

Responsibilities

• Build ML features on structured and unstructured content (telemetry, audio, video, user behaviour and preferences)
• Manage the full ML development life cycle – from problem framing, data wrangling, and model development, to productionization, experimentation, and maintenance
• Design and deploy large-scale machine learning products and solutions with correctness, usability, interpretability, experimentation, and maintainability in mind
• Determine the feasibility of initiatives through quick prototyping with respect to performance, quality, time, and cost
• Collaborate with cross functional teams of software and data engineers to build new product features
• Leverage your experience to drive best practices in ML Engineering and mentor other engineers on the team
• Defining Scope and requirements, success metrics for ML projects

Preferred Qualifications

• Experience optimizing for resource constrained edge devices is a plus
• Interest in climate change mitigation and sustainability is a plus

Benefits

• Competitive salaries
• Health benefits
• Progressive Parental Top-Up Program (75% top-up or five bonus days off)
• Flexible hours
• Office-based, fully remote, or hybrid work environment
• In-house learning enablement team
• Generous professional learning budget