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Contract Meta Machine Learning Jobs in Toronto, ON

Partner across data science, backend and product on the producer to consumer contract (models ... Machine Learning Platform Exposure: Experience supporting machine learning workflows, feature ...

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 ...

Senior Data Scientist

Toronto, ON · On-site

CA$103K - CA$192K/yr

Data Analytics & Reporting This is a 12 month contract hybrid role in Toronto We are seeking a Senior Data Scientist to join our team on a 12-month contract to support key machine learning initiative.

This is a 16 month contract role Role Summary Within Sun Life, theData and Analytics COEcomprisedof ... Data Science and Machine Learning * Translate business goals into analytical problems;

AI Technical Specialist

Toronto, ON · Hybrid

CA$82K - CA$113K/yr

Technical Skills - Must Have Understanding of agentic AI, machine learning, Generative AI, and ... Employment contracts are shared directly by members of the Medcan Talent Acquisition or Human ...

New

Data Analytics & Reporting We are seeking a Senior Manager to join our team on a 12-month contract to support key machine learning initiative. Responsibilities: Uses advanced analytical algorithms ...

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Contract Meta Machine Learning information

What are the key skills and qualifications needed to thrive as a Contract Meta Machine Learning Engineer, and why are they important?

To thrive as a Contract Meta Machine Learning Engineer, you need a strong background in computer science, statistics, and advanced machine learning concepts, often supported by a relevant degree or equivalent experience. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and version control systems is essential, along with experience in meta-learning techniques. Strong analytical thinking, problem-solving abilities, and effective communication skills help you design innovative solutions and collaborate with diverse teams. These competencies are crucial to efficiently develop, implement, and optimize meta-learning models that address complex, evolving business challenges.

What is the difference between Contract Meta Machine Learning vs Contract Data Scientist?

AspectContract Meta Machine LearningContract Data Scientist
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related fields; experience with machine learning frameworksMaster's or PhD in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentFocus on developing and deploying machine learning models, often in AI projectsData analysis, modeling, and interpretation to inform business decisions
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, and tech firms

Contract Meta Machine Learning roles primarily focus on building and deploying machine learning models, often requiring advanced technical skills in AI. Contract Data Scientist positions involve analyzing data, creating models, and deriving insights for business strategies. While both roles require strong analytical skills and similar educational backgrounds, Meta Machine Learning roles are more specialized in AI development, whereas Data Scientist roles emphasize data analysis and interpretation.

What are some of the unique challenges faced by contract machine learning engineers at Meta, and how can candidates prepare for them?

Contract machine learning engineers at Meta often work on high-impact projects with tight deadlines and rapidly evolving requirements. One of the main challenges is quickly integrating into existing teams and understanding Meta's large-scale data infrastructure and proprietary tools. To prepare, candidates should familiarize themselves with Meta's open-source frameworks, practice adapting to new codebases, and be ready to communicate effectively with cross-functional stakeholders. Building strong collaboration skills and maintaining flexibility will help contract engineers deliver value efficiently in this fast-paced environment.

What are Contract Meta Machine Learning professionals?

Contract Meta Machine Learning professionals are specialists hired on a contractual basis to design, develop, and optimize machine learning models, often focusing on meta-learning techniques. Meta-learning, sometimes called 'learning to learn,' involves creating algorithms that can adapt to new tasks with minimal data or retraining. These professionals typically work with organizations to solve complex, data-driven problems, leveraging advanced AI techniques for efficiency and scalability. They may also help integrate these solutions into existing systems and provide guidance on best practices for model deployment.
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 are popular job titles related to Contract Meta Machine Learning jobs in Toronto, ON? For Contract Meta Machine Learning jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Contract Meta Machine Learning jobs in Toronto, ON look for? The top searched job categories for Contract Meta Machine Learning jobs in Toronto, ON are:
Infographic showing various Contract Meta Machine Learning job openings in Toronto, ON as of July 2026, with employment types broken down into 1% As Needed, 62% Full Time, 19% Part Time, 1% Temporary, and 17% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.
Senior Machine Learning Engineer, Growth

Senior Machine Learning Engineer, Growth

HelloFresh

Toronto, ON • Hybrid

Other

Medical, Dental, PTO

Re-posted 19 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 23 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