Principal, ML Infrastructure Engineer

Tubi Tv; Toronto; Hybrid; CAD 120,000 - 150,000; Full time

Job summary

A leading streaming service in Toronto seeks a Principal Engineer to drive innovation in its ML infrastructure. This role is essential for shaping scalable ML systems and mentoring senior engineers. Candidates should have over 10 years of experience in software engineering, with a strong background in distributed systems and technologies like Scala and AWS. The position offers a hybrid schedule requiring at least two days per week onsite.

Benefits

Hybrid work model

Qualifications

• 10+ years of experience in software engineering focused on large-scale distributed systems.
• Proven experience as a technical leader in ML infrastructure.
• Experience with databases, caching technologies, and message brokers.

Responsibilities

• Define and champion the long-term vision for ML infrastructure.
• Lead the architecture and design of complex ML systems.
• Resolve critical technical challenges related to ML infrastructure.

Skills

Technical Leadership

Distributed Systems Expertise

Problem Solving

Collaboration

Knowledge Sharing

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Scala

Java

Python

AWS

Job description

Boldly built for every fandom, Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.

About the Role

As a Principal Engineer on the ML Infrastructure team, you will be a technical leader and visionary, driving the evolution of our machine learning platform. You will tackle the most complex and impactful technical challenges, shaping the architecture and technology choices that enable our ML capabilities to scale and deliver exceptional user experiences. You will be a key influencer, bridging the gap between engineering and product, and a mentor to senior engineers, fostering a culture of technical excellence and continuous improvement. Your work will be used by millions of users.

This is a hybrid role in our Toronto office.

What You\'ll Do

Technical Leadership & Strategy:

• Vision & Influence: Define and champion the long-term vision for ML infrastructure, aligning it with company goals and industry best practices. Influence technical direction and technology selection across the ML platform
• Strategic Roadmap: Develop and maintain a roadmap (6-12 months) for the ML Infra team, anticipating future needs and proactively addressing emerging trends
• Innovation & Optimization: Identify opportunities to improve ML infrastructure efficiency, scalability, and performance. Research and advocate for new technologies and approaches to optimize the ML development lifecycle

Architecture, Design & Engineering:

• System Design: Lead the architecture and design of complex ML systems, ensuring scalability, reliability, security, and maintainability
• Distributed Systems Expertise: Design and build scalable, high-throughput, and/or low-latency distributed systems using Scala and related technologies. This includes expertise in areas like distributed databases, message queues, and stream processing
• Quality & Standards: Champion and enforce engineering best practices, including code quality, testing, and documentation. Contribute to the development and implementation of ML infrastructure standards

Problem Solving & Delivery:

• Technical Problem Solving: Resolve critical and complex technical challenges related to ML infrastructure, demonstrating expertise in debugging, performance optimization, and system troubleshooting
• Project Execution: Lead and deliver complex ML infrastructure projects, effectively managing scope, timelines, and dependencies. Mentor engineers on project management best practices
• Collaboration & Mentorship: Foster a collaborative environment and provide technical mentorship to other engineers, enabling their growth and development
• Cross-functional Partnership: Collaborate effectively with data scientists, ML engineers, and product managers to understand their needs and translate them into infrastructure solutions
• Stakeholder Management: Communicate effectively with stakeholders at all levels, including senior leadership. Clearly articulate technical concepts, progress updates, and roadblocks
• Knowledge Sharing: Promote knowledge sharing and best practices across the organization through documentation, presentations, and mentorship

Your Background:

• 10+ years of experience in software engineering, with a significant focus on building and scaling large-scale distributed systems
• Bachelor\'s or Master\'s degree in Computer Science or a related field
• Proven experience as a technical leader, architecting and designing complex systems, preferably in the ML infrastructure domain
• 5+ years of experience with databases, caching technologies, and message brokers
• Expertise in Scala, Java, Python programming languages
• Extensive experience with cloud platforms (preferably AWS)

Bonus:

• Experience in the media or streaming industry
• Contributions to open-source projects related to ML infrastructure

VOLUNTARY DISCLOSURES

The following is an equal opportunity employer information section. We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the voluntary self-identification survey. Completion of the form is optional and will not affect hiring decisions. Information provided is confidential.

This position is based in Toronto, Canada, with a hybrid schedule requiring at least two days per week onsite. Are you able to meet this requirement?

Public burden and disclosure notices may apply as required by law.