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Temporary Meta Machine Learning Jobs in Montreal, QC

... temporary market premium specific to this role that is reassessed annually. TD is committed to ... We're looking for a highly motivated Applied Machine Learning Scientist II to join our AI2 team. In ...

... en temps réel. Vous travaillerez avec des technologies de pointe (incluant les LLMs) et ... Responsabilités principales Machine learning et logique produitAssumer la responsabilité de la ...

We are seeking a Senior Machine Learning (ML) Research Scientist to join our team working on a ... or meta learning. * Expertise in the integration and use of ML libraries such as PyTorch ...

Machine learning généraliste et recherche opérationnelle de façon ponctuelle, quand le contexte ... Tu préfères travailler de chez toi et te rendre au bureau de temps en temps? Aucun souci!; ☀️ ...

Appliquer les regles de Sante et Securite au travail en vigueur de l'entreprise en tout temps ... Machine Operator By submitting your CV or application you are consenting to Airbus using and ...

Temporary contract with the possibility of becoming permanent Forklifts used: Reach & Double Reach ... A career at Lineage starts with learning about our business and how each team member plays a part ...

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Temporary Meta Machine Learning information

What is a temporary Meta machine learning job?

Temporary Meta Machine Learning jobs are short-term positions at Meta (formerly Facebook) that focus on developing, deploying, or researching machine learning models and technologies. These roles may support ongoing projects, fill gaps during employee leave, or address spikes in workload. Responsibilities can include data preprocessing, model training, evaluation, and collaborating with cross-functional teams. Temporary roles often give candidates exposure to Meta's cutting-edge AI tools and processes, and may sometimes lead to permanent opportunities.

What are the key skills and qualifications needed to thrive as a temporary Meta machine learning engineer?

To thrive as a Temporary Meta Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning, typically with experience in Python and relevant ML frameworks. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms, and version control systems is often required, along with a proven ability to rapidly learn new technologies. Strong problem-solving skills, adaptability, and effective communication are essential for collaborating within dynamic teams and meeting project goals on tight timelines. These skills ensure that you can quickly contribute to impactful ML projects, deliver results efficiently, and integrate well into fast-paced, innovative environments.

What are some common challenges faced by professionals in temporary machine learning roles at Meta, and how can they be addressed?

Professionals in temporary machine learning roles at Meta often encounter challenges such as quickly acclimating to complex codebases, integrating with established teams, and delivering impactful results within a limited timeframe. Success in these roles typically requires strong technical skills, adaptability, and effective communication. Proactively seeking guidance, leveraging available documentation, and collaborating closely with permanent team members can help overcome these hurdles and maximize contributions during the temporary assignment.

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

AspectTemporary Meta Machine LearningData Scientist
CredentialsTypically requires a background in computer science, statistics, or related fields; certifications in machine learning or data analysis are commonRequires a degree in computer science, statistics, or related fields; certifications like Certified Data Scientist are advantageous
Work EnvironmentProject-based, often contract roles within tech companies, startups, or consulting firmsFull-time or contract roles in various industries including finance, healthcare, and tech
Industry UsagePrimarily in tech, AI, and machine learning-focused companiesWidely used across multiple industries including finance, healthcare, marketing, and tech

Temporary Meta Machine Learning roles focus on short-term projects involving machine learning model development and deployment, often requiring specialized technical skills. Data Scientist roles are broader, encompassing data analysis, statistical modeling, and insights generation across diverse industries. While both roles require strong analytical skills and technical knowledge, Temporary Meta Machine Learning positions are more specialized in AI and machine learning applications.

What are popular job titles related to Temporary Meta Machine Learning jobs in Montreal, QC?

For Temporary Meta Machine Learning jobs in Montreal, QC, the most frequently searched job titles are:

What job categories do people searching Temporary Meta Machine Learning jobs in Montreal, QC look for?

The top searched job categories for Temporary Meta Machine Learning jobs in Montreal, QC are:

What cities near Montreal, QC are hiring for Temporary Meta Machine Learning jobs?

Cities near Montreal, QC with the most Temporary Meta Machine Learning job openings:

Applied Machine Learning Scientist II

Td

Montreal, QC • On-site

CA$125K - CA$154K/yr

Full-time

Posted 20 days ago


Job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$125,500 - $154,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

We're looking for a highly motivated Applied Machine Learning Scientist II to join our AI2 team. In this role, you'll apply expertise across the end-to-end AI and machine learning lifecycle, including model development, evaluation, testing, validation, deployment, and monitoring for both traditional machine learning and Generative AI solutions. You'll work closely with business, technology, risk, governance, and implementation partners to bring AI capabilities to life and deliver measurable business impact.

This role offers an excellent opportunity to combine hands-on machine learning expertise with broader responsibilities related to AI solution assessment, vendor model evaluation, implementation, and governance. You will be expected to work with multiple business partners to advance the use of Machine Learning and AI at TD while supporting the responsible adoption of both internally developed and third-party AI solutions.

KEY ACCOUNTABILITIES

Develop, deploy, and maintain Predictive and Generative AI solutions for use cases such as Agentic AI, LLM-based models, Pricing, and Anomaly Detection.
Lead the evaluation, implementation, testing, monitoring, and ongoing lifecycle management of both internally developed and third-party AI/ML solutions.
Assess vendor-provided and out-of-the-box AI models, including their capabilities, limitations, performance characteristics, implementation considerations, and governance implications.
Translate business problems into analytical frameworks and collaborate with cross-functional teams to define success metrics, testing methodologies, and solution approaches.
Conduct rigorous model evaluation, documentation, A/B testing, validation support, and monitoring to ensure model performance, fairness, stability, and compliance with Responsible AI principles.
Communicate complex technical results to technical and non-technical stakeholders and provide actionable recommendations regarding model performance, implementation, and risk.

JOB REQUIREMENTS

Communication & Relationship Skills
Excellent written and verbal communication.
Comfortable and effective when interacting with a wide range of business partners and stakeholders.
Ability to develop and maintain strong internal relationships across business, technology, risk, and governance functions.
Ability to translate complex technical concepts and analytical findings into clear business language.

Strategic Thinking & Judgment
Creative, out-of-the-box thinker with strong conceptual and problem-solving skills.
Motivated to constantly identify innovative ways to enhance analytical solutions and AI implementation practices.
Capable of quickly identifying drivers of model performance variation, implementation risks, and monitoring concerns.
Ability to evaluate internally developed and vendor-provided AI solutions while balancing business value, performance, and governance requirements.

Technical Competencies
Proficiency in Python and modern machine learning frameworks and tools.
Experience developing, evaluating, and deploying machine learning and Generative AI solutions.
Strong understanding of model evaluation methodologies, experimentation, statistical testing, and performance monitoring.
Experience with structured and unstructured data, feature engineering, and model interpretability techniques.
Exposure to LLMs, agentic AI systems, and practical Generative AI applications.
Familiarity with model governance, Responsible AI principles, model validation, and model risk management practices.
Experience with SQL, Azure Cloud, Azure ML Services, or Databricks is an asset.

Education & Experience

Undergraduate degree in Science, Technology, Engineering, Mathematics, Economics, Finance, or a related quantitative discipline.
Graduate degree is considered an asset.
5+ years of relevant experience in machine learning, advanced analytics, data science, model evaluation, or related fields.

Nice to Have

Experience working in financial services or regulated environments.
Familiarity with model validation, model risk management, governance, or audit processes.
Experience evaluating vendor-provided analytical solutions, AI platforms, or commercial Generative AI products.
Familiarity with causal inference, anomaly detection, or agentic AI systems.

Who We Are:

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We're delighted that you're considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we're committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.


Colleague Development

If you're interested in a specific career path or are looking to build certain skills, we want to help you succeed. You'll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

If you're passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.

We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you've got everything you need to succeed in your new role.

Interview Process
We'll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.


Accommodation
Your accessibility is important to us. Please let us know if you'd like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.
We look forward to hearing from you!

Language Requirement (Quebec only):

Maitrise d'une langue autre que le francais pour offrir du soutien ou traiter avec des employes ou des collegues qui ont besoin de services et de soutien dans une langue autre que le francais.