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Added 6 months ago
SC
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- Full-time
Lead Technically: Mentor engineers, conduct meaningful code reviews, establish best practices, and be a trusted voice in architectural decisions
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Added 1 month ago
Staff Software Engineer, ML Infra & Distributed Systems
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Toronto, ON
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Added 1 month ago
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Added 6 months ago
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Principal Pre-sales Engineer - ALM (Automotive)
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Added 2 months ago
Staff Back End Engineer (Applications)
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Staff Software Engineer, App Runtime
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Added 2 months ago
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Added 6 months ago
Software Developer - Team Lead
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Lead Software Engineer, Full-Stack Applications - Ratings Technology
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Toronto, ON
- $160,000 to $200,000 CAD / year
Fitch Ratings is seeking a Lead Software Engineer to join our global Ratings Technology team in Toronto. This is your opportunity to not just build mission-critical applications, but to…
Added 1 month ago
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Salesforce Technical Manager
Pwc Canada
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- Full-time
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Added 3 months ago
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Salesforce Technical Manager
PwC
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- Full-time
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Tubi - Canada

Staff Software Engineer, ML Infra & Distributed Systems

Toronto, ON, Canada

$164,600 - $235,100 CAD

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Job details

Pay: $164,600 - $235,100 CAD
Posting language: English
Posted: Sep 11, 2026

Original job description

About the Role:

As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi.

A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine.

You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams.

Responsibilities:

Design and build scalable, high throughput, and low latency distributed systems using Scala
Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration
Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art.
Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary
Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc.
Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi.

Your Background:

Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM based language is a plus.
Strong experience with AWS or an equivalent cloud platform
Experience building online microservices at scale with low latency serving
Experience with both SQL (e.g. Postgres) and NoSQL databases (e.g. Cassandra), message brokers (e.g. Kafka), and caches (e.g. Redis)
Experience with containerization technologies, such as Docker or Kubernetes
Led the response and resolution efforts for multiple major, large-scale incidents

Bonus:

Familiarity with the machine learning infrastructure like inference engines (e.g. torschserve, triton, vLLM), vector stores (e.g. LanceDB, FAISS), feature stores (e.g. Feast), ElastiCache, model training orchestration, etc.
Understanding of ML model training pipelines and model internals. Experience with Recommender Systems, Search, Autocomplete and Ads ML is a plus
Previous experience with Akka, Erlang, Elixir or Go
Proficient in data-driven analysis of complex A/B testing results

About Tubi:

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.

Pursuant to local pay disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience, and location is as listed annually below.

This role is also eligible for an annual discretionary bonus, long-term incentive plan, and various benefits including medical/dental/vision, insurance, vacation/paid time off and other benefits in accordance with applicable plan documents.

Toronto, Canada

$164,600 - $235,100 CAD

Tubi Media Group is a division of Fox Corporation, and the FOX Employee Benefits summarized here, covers the majority of employee benefits. The following distinctions below outline the differences between the Tubi and FOX benefits:

For all salaried employees, in lieu of the FOX Vacation policy, Tubi offers a Flexible Time Off Policy to manage all personal matters.

For all full-time, regular employees, in lieu of FOX Paid Parental Leave, Tubi offers a generous Parental Leave Program, which allows parents twelve (12) weeks of paid bonding leave (top up in Canada) within the first year of birth, adoption, surrogacy, or foster placement of a child in addition to applicable government leave program(s) and FOX’s short-term disability policy (if applicable). This time is 100% paid through a combination of any applicable government leaves and wage-replacement programs in addition to contributions made by Tubi.

For all full-time, regular employees, Tubi offers a monthly wellness reimbursement.

About Tubi:

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.

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.

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More about this job

Responsibilities

The role involves designing and building scalable, high-throughput, and low-latency distributed systems using Scala to power ML applications like personalization and search. Responsibilities include developing critical components like the inference engine and feature store, optimizing infrastructure efficiency, and leading cross-functional refactorings.

Requirements

Candidates must have 8+ years of experience building scalable, distributed systems, preferably with Scala or a JVM language, and strong experience with AWS or a similar cloud platform. Required background includes building low-latency online microservices and experience with various data technologies like SQL, NoSQL, Kafka, and Redis.

Skills

Scala
Distributed Systems
ML Inference
Low Latency
Deep Learning
LLM
Search Models
Inference Engine
Feature Store
Vector Store
Experimentation Engine
AWS
Microservices
SQL
NoSQL
Kafka

Benefits

Annual Discretionary Bonus
Long-Term Incentive Plan
Medical
Dental
Vision
Insurance
Vacation
Paid Time Off
Flexible Time Off Policy
Parental Leave Program
Wellness Reimbursement

Visa sponsorship

Not detected in the job text

Keywords

ML Infrastructure
Distributed Systems
Machine Learning
Inference Platforms
Low Latency
Deep Learning
LLM
Search
Inference Engine
Feature Store
Vector Store
Experimentation Engine
Scala
Java
Python
Go
C++
AWS
Microservices
Postgres
Cassandra
Kafka
Redis
Docker
Kubernetes
Triton
vLLM
FAISS
Feast
A/B Testing

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