ML Ops Engineer

Role

The ML Ops Engineer is responsible for developing, implementing, and maintaining the infrastructure and processes necessary to deploy and operate machine learning models in production. The ideal candidate will have a strong understanding of machine learning, software engineering, and DevOps principles.

This is a unique opportunity to set the foundation for the development of strong and scalable infrastructure for Switch data and prediction tasks. You will be instrumental in creating the products that drive Switch forward and lie at the core of our operations.

We seek an excellent communicator with prior experience in software engineering, data science, and ML model development/training. Your application should demonstrate your dedication to technology, attention to detail, and eagerness to learn and embrace diverse responsibilities.

Responsibilities

• Design and implement ML pipelines for training, testing, and deploying machine learning models
• Develop and maintain infrastructure for deploying and operating machine learning models in production
• Monitor and maintain ML models in production
• Work with data scientists and engineers to ensure that ML models are deployed and operated in a reliable and efficient manner
• Collaborate with DevOps engineers to ensure that ML models are integrated with the organization's software development lifecycle
• Keep up-to-date on the latest ML Ops trends and technologies

Requirements

• Bachelor's degree in computer science, data science, or a related field
• 3+ years of experience in software engineering
• 2+ years of experience with machine learning
• Strong understanding of DevOps principles and practices
• Experience with cloud computing platforms (AWS, Azure, GCP)
• Excellent communication and teamwork skills
• Lives somewhere in the UTC-3 to UTC-8 time zones

Nice to haves

• Experience growing and scaling a web platform 10-100x.
• Experience in a fast growing startup and comfort with that pace.
• Experience writing technical design documents describing planned feature development
• Familiarity with ETL pipelines and theory.
• Experience with cloud architecture, especially on GCP.

Location

• Switch is located in Toronto, Canada, but operates fully remotely.
• Remote candidates are welcome to apply.
• Preference will be shown to candidates that can be regularly available in-person in Toronto to collaborate with the leadership team.

Interview process

• Initial interview: A 30-45 minute chat with our CTO. We'll share more about the role, our expectations, your history and experience, and go over any questions you may have.
• Skills interview: We aren't big believers in the traditional whiteboard/algorithmic interview structure. You got here by knowing your craft, and we don't need to test that. Instead we will pair-program on a small project as a way to spark discussion, get to know how you approach new problems, and what things you consider. We try to keep the technical portion of our interview process focused on challenges you might face while at Switch.
• Interview with CEO/CFO: This is the candidate's chance to meet the rest of the leadership team at Switch and learn about the company from a business perspective.
• Optional: Meet with one of our industry advisors to learn more about our industry and trajectory.
• Offer: We'll make you an offer and you can decide if you want to join us.

Compensation range

• Market competitive compensation based on experience
• Meaningful equity in a fast-growing startup

To Apply

Send a description of yourself, your work experience, and why you want to work with us at Switch to [email protected].

If you think you have the experience and desire to work in a fast-paced startup environment, but lack some of the requirements please consider applying anyway.

We are looking for great people and would love to chat with you.