Senior Machine Learning Engineer


Kinaxis logo
Apply now Apply later

Posted 3 weeks ago



At Kinaxis, who we are is grounded in our common belief that people matter. Each one of us plays an important part in accomplishing our work, building our culture and making a global impact.

Every day, we’re empowered to work together to help our customers make fast, confident planning decisions. This is how we create a better planet – for each other, for our customers and for generations to come. Our cloud-based platform RapidResponse ensures that the products we need – everything from medicine and cars, to day-to-day items like toothpaste – make it to market and into our hands when we need them with minimal ecological footprint.

We make the world better, and you can too.

Senior Machine Learning Engineer 

Job location: our office in Toronto, Canada

Who We Are Looking For

All aspects of the software development life cycle are familiar to you. You are passionate about shipping large-scale software systems in a fast-paced environment but are able to balance longer term issues such as maintainability, scalability and quality. You have a strong interest and experience in machine learning having worked with machine learning and data analysis libraries such as pandas, scikit-Learn, XGBoost, lightGBM and Tensorflow but realize building a machine learning system is much more than just calling a few APIs.

You treat data as a first class citizen whether that the data comes from a data warehouse, object storage or output of a model. You’re fluent in Python and SQL and have hands-on experience with big data technologies such as Spark and Hadoop. You love learning about new technologies whether they be in the ML or data space but are pragmatic and discerning about which technologies you adopt in your system.

You are a team player, a quick starter and an implementer who is equally comfortable talking requirements with technical product managers or getting in the zone pair programming with data scientists. Your primary focus is on shipping large-scale machine learning software systems that drive customer value by building robust and scalable computational and data-intensive workflows and web services.


  • Bachelor’s degree or equivalent in Computer Science or a related field with focus in machine learning.
  • Strong software engineering skills and understanding of the ML lifecycle with a minimum of 3 years experience in ML and 5 years in software development.
  • Proficiency in Python.
  • Fluent in processing data with pandas and PySpark (e.g. querying, transforming, joining, cleaning, etc.) including experience debugging logic and performance issues.
  • Strong understanding of machine learning algorithms with experience writing, debugging and optimizing ML data structures, pipelines and transformations.
  • Ability to work in Linux environments with containerization technologies (Docker, Kubernetes, Argo) and major cloud services (AWS, GCP, Azure).

Nice to have

  • Retail and CPG business background.
  • SaaS, multi-tenant and MLaaS development experience (microservice frameworks, queuing systems, event-based processing and web services).
  • Machine learning dev-ops experience with major cloud providers (e.g. Kubernetes, Terraform).

What we have to offer

  • Challenging Work - We love solving highly complex problems. And as the global leaders in our industry, we never stop innovating—our work is never “done. That’s because across our teams and in all roles, every employee is empowered to bring their best ideas forward and to jump in and solve the problems they’re passionate about.
  • Great People - We take our work seriously, but we don’t take ourselves too seriously! It’s in our DNA to celebrate, laugh, and have fun. We are stronger, together, when we are open, honest, and above all, real. Every person is valued here and plays an important role in our shared success.
  • Global Impact - As a global team spanning continents, boundaries, and cultures, every day we are inspired by the impact our work has on our colleagues, our customers, our communities, and the world at large.

For more information, visit the Kinaxis web site at or the company’s blog at

Kinaxis invites candidates to apply to its welcoming community. Accommodations are available upon request for applications in all aspects of the recruitment process. If you require accommodation, please contact Human Resources at


Job tags: AWS Big Data Engineering Hadoop Kubernetes LightGBM Linux Machine Learning ML Pandas PySpark Python Scikit-Learn Spark SQL TensorFlow XGBoost