Senior Machine Learning Engineer

Salary Range: 116000 to 160000 (Currency: CAD) (Pay period: per-year-salary)

How You’ll Make an Impact:

• Explore, design and build AI prototypes capable of significantly altering our users’ experiences
• Work in close collaboration with Data Scientists to build and deployed in production ML solutions/agents, test new algorithms, provide feedback on their performance, accuracy and scalability, also suggest alternatives.
• Write optimized code that is performant, scalable, testable, maintainable and observable
• Design scalable solutions to productionize machine learning models
• Develop tools and pipelines for tracking models and experiments
• Design and implement data pipelines that ingest vast amounts of real-time data to power models and generate accurate results
• Manage ML models/Agent lifecycle, including versioning, training, retraining, deploying and monitoring
• Be responsible for maintaining and operating algorithms, codes and models in production and monitor models in production to make sure that they are functioning and report on any anomalies
• Research/Investigate tools and technologies that would enable us to build and release faster
• Layout best practices for ML engineering functional role
• Evangelize a data-driven culture and participate in a highly collaborative environment. We want you to share your expertise!

We Could Be a Match if You Have:

• B.S., M.S or PhD in computer science (or a scientific discipline coupled with substantial engineering experience)
• Minimum of 5+ years post graduation experience as a Machine Learning Engineer, Software Engineer with algorithm experience, Data Scientist or similar. 
• Minimum of 3+ years experience building and productionalizing agent based solutions within a commercial application in collaboration with product owner and deploying and operating LLM solutions to support business feature development
• Significant experience in cutting edge deep learning techniques and associated tools (such as PyTorch/Tensorflow)
• Excellent programming skills with history of deployment to production and you have a proven track record of scaling and productionizing machine learning solutions and models
• Solid understanding of mathematical modeling and statistics: inference, Bayesian methods, graphical models, network theory, likelihood estimation, Monte-Carlo methods and sampling theory
• Understanding of how to optimize machine learning models (parallelization, batching techniques, etc)
• Ability to rapidly acquire and adopt new knowledge and techniques but also thinks creatively about problems and not afraid to go “outside the box”
• Proficient with standard SQL and relational databases
• Familiarity with Python and associated data science/machine learning packages
• Comfortability working independently on large projects (demonstrated via industry or academic experience) or as part of a diverse team of different skills as necessary
• Ability to see the “big picture” and how your work relates to POF’s entire business - and the ability prioritize your research work accordingly
• Experience with GCP or other cloud providers