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Meta Machine Learning Jobs in Toronto, ON (NOW HIRING)

Deep, hands-on experience designing, deploying, and scaling AI/Machine Learning systems or LLM ... Our technical leadership comes from Meta, Microsoft, X, and Goldman Sachs, bringing world-class ...

Clients include Google, Lufthansa, Meta, eBay, and OpenAI. We have been certified B Corp and ... Utilize predictive analytics and machine learning capabilities to enhance personalization and ...

New

Operations Manager (3 month FTC)

Toronto, ON · Hybrid

CA$85K - CA$100K/yr

Clients include Google, Lufthansa, Meta, eBay, and OpenAI. We have been certified B Corp and ... Train teams, document system, and create a self-sustaining machine via an operations playbook ...

Meta Machine Learning information

Does Meta have a machine learning engineer?

Yes, Meta employs machine learning engineers who develop and implement AI models to improve products like Facebook, Instagram, and WhatsApp. These roles typically require expertise in programming, data analysis, and machine learning frameworks such as PyTorch or TensorFlow. Candidates often need a strong background in computer science or related fields and experience with large-scale data processing.

What engineer makes $500,000 a year?

Senior machine learning engineers, especially those working at large tech companies or in specialized roles, can earn $500,000 or more annually. High compensation often includes base salary, bonuses, and stock options, and typically requires advanced skills in deep learning, data modeling, and experience with tools like TensorFlow or PyTorch.

What is a Meta Machine Learning job?

A Meta Machine Learning job typically involves developing and optimizing machine learning models at scale, often within Meta (formerly Facebook). These roles focus on improving AI algorithms, researching new techniques, and deploying models across products like Facebook, Instagram, and WhatsApp. Engineers and researchers in this field work with large datasets, deep learning frameworks, and distributed computing. The role requires expertise in machine learning, software engineering, and data science to enhance Meta's AI-driven capabilities.

How much does Meta machine learning pay?

Meta machine learning roles typically offer salaries ranging from $120,000 to $200,000 annually, depending on experience, location, and level. Compensation may also include bonuses, stock options, and benefits, with higher salaries generally for senior or specialized positions requiring advanced skills in AI and data analysis.

What are the key skills and qualifications needed to thrive in the Meta Machine Learning position, and why are they important?

To thrive in Meta Machine Learning, you need a deep understanding of advanced machine learning algorithms, meta-learning techniques, data science, and a degree in computer science or a related field. Experience with tools like Python, TensorFlow, PyTorch, as well as familiarity with cloud computing platforms and relevant certifications (such as AWS Certified Machine Learning Specialty) are highly valuable. Strong analytical thinking, creative problem-solving, and collaborative communication are essential soft skills for excelling in this area. These competencies enable practitioners to develop and optimize meta-learning models, drive innovation, and efficiently work in cross-functional tech teams.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or executive positions, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These roles usually involve leadership, strategic planning, and significant industry expertise, and they are among the highest-paying positions in the tech field.

What are some of the main challenges faced in a Meta Machine Learning role?

Professionals in Meta Machine Learning often encounter challenges such as working with limited labeled data, creating models that generalize well across diverse tasks, and optimizing algorithms to learn efficiently from smaller datasets. The fast-paced nature of research and the need to stay updated with cutting-edge advancements in the field can also require continual learning and adaptation. Collaboration with other data scientists, engineers, and domain experts is common, making teamwork and clear communication critical for successful project delivery. Overcoming these challenges not only sharpens technical skills but also offers rewarding opportunities for innovation and career growth in this evolving field.

What are the most commonly searched types of Meta Machine Learning jobs in Toronto, ON? The most popular types of Meta Machine Learning jobs in Toronto, ON are:
What job categories do people searching Meta Machine Learning jobs in Toronto, ON look for? The top searched job categories for Meta Machine Learning jobs in Toronto, ON are:
Infographic showing various Meta Machine Learning job openings in Toronto, ON as of June 2026, with employment types broken down into 27% Internship, and 73% Full Time. Highlights an 100% In-person job distribution.
Senior Machine Learning Engineer, Growth

Senior Machine Learning Engineer, Growth

HelloFresh

Toronto, ON • Hybrid

Other

Medical, Dental, PTO

Posted 27 days ago


HelloFresh rating

6.6

Company rating: 6.6 out of 10

Based on 52 frontline employees who took The Breakroom Quiz

10th of 22 rated food delivery companies


Job description

We are seeking a Senior Machine Learning Engineer to join the Growth Tech Alliance. In this role, you will architect and deploy the robust infrastructure behind our intelligent marketing systems. You will be responsible for maturing algorithmic prototypes into high-performance production systems, ensuring our AI-driven marketing optimization is served reliably and autonomously at a global scale.

S'more about the team

We are hiring a Senior Machine Learning Engineer to take our AI tooling to the next level by architecting and deploying the robust infrastructure behind our intelligent marketing optimization systems. You will provide critical engineering execution for our AI initiatives. You will develop scalable microservices for predictive scoring, orchestrate complex LLM-based agents for creative intelligence. As the ML engineering expert for the team, you will drive the maturation of algorithmic prototypes into high-performance production systems with maximum Speed & Agility, shaping the future of how HelloFresh automates marketing at an unprecedented scale.

Lettuce share what this role will be responsible for

As a core member of the engineering team, you will focus on productionizing ML infrastructure across several domains:

  • Build robust integration layers for visual AI pipelines that process multi-modal embeddings that power various predictive models.
  • Transition proof-of-concept models into resilient production microservices and architect LLM-based orchestration frameworks.
  • Engineer high-throughput, low-latency data pipelines to process 1P data and pipeline signals into external platforms like Meta and Google.
  • Collaborate with data scientists and other engineers in a cross-functional team to improve HelloFresh's value forecasting efficiency.
  • Establish CI/CD processes, feature stores, and drift detection to ensure continuous delivery and model reliability.
  • All other duties, as assigned

Sound a-peeling? Here's what we're looking for

  • Experience leading the end-to-end lifecycle of production ML systems, from architectural design to scalable deployment and monitoring.
  • Expertise in leveraging hyperscaler ecosystems (AWS, GCP, Azure) to build cost-effective, resilient, and automated ML infrastructure.
  • Deep technical proficiency with modern ML frameworks (PyTorch, TensorFlow, HuggingFace)
  • Expert programming skills in Python and PySpark.
  • A BS/MS in Computer Science or a related engineering field, coupled with a proven track record of bringing ML systems from prototype to high-traffic production.
  • Proven experience engineering robust data architectures that reliably process and combine diverse data formats, ranging from structured offline conversion data to unstructured multimedia assets.
  • A demonstrated bias for action and extreme ownership, eager to adopt Gen AI tools to creatively solve architectural challenges and enhance engineering velocity.

Let's cut to the cheese, this is why you'll love it here

  • Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
  • Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
  • Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
  • Family Benefits - A parental leave top-up program for expectant parents.
  • Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
  • Work Hard & Have Fun - From team socials to engaging company days, you'll have plenty of opportunity to experience the fun!
  • Diversity & Inclusion Initiatives - With impactful ERG's like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
  • Food Puns - this one is kind of a big dill if you haven't already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

#Engineering

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.


What HelloFresh employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


HelloFresh logo

About HelloFresh

Sourced by ZipRecruiter

HelloFresh is a meal-kit company based in Berlin, Germany. It is the largest meal-kit provider in the United States and also has operations in Australia, Canada, New Zealand, and the United Kingdom, as well as Europe (Germany, Austria, Switzerland, Belgium, Netherlands, Luxembourg, France, Italy, Ireland, Spain and Scandinavia). HelloFresh’s mission is to change the way people eat forever by helping consumers save money with every meal, democratizing access to high-quality food, allowing everyone to enjoy a varied and tasty diet, and reducing food waste through CO2 neutral delivery of every box.

Industry

Food services and drinking places

Company size

1,001 - 5,000 Employees

Headquarters location

New York, NY, US