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Contract Meta Machine Learning Jobs in Toronto, ON

We build ground breaking AI technology that can read and understand contract language to make every ... About the Role As a Machine Learning Engineer, you will help develop tailored user experiences ...

Principal Software Engineer

Toronto, ON · On-site

CA$220K - CA$300K/yr

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 ...

... contract awards. We are currently seeking skilled candidates to join our team and encourage ... Experience with machine learning frameworks such as TensorFlow and PyTorch * Familiarity with LLM ...

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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 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:
Machine Learning Engineer - Evisort

Machine Learning Engineer - Evisort

Workday

Toronto, ON • On-site

Full-time

Posted 5 days ago


Workday rating

9.2

Company rating: 9.2 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

13th of 186 rated software companies


Job description

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back. In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.

About the Team

Join the Evisort AI team at Workday, which powers Document Intelligence AI and Workday's CLM and Contract Intelligence offerings. Our mission is to change the way business deals get done.
We build ground breaking AI technology that can read and understand contract language to make every part of the deal-making process from drafting, negotiating, reviewing, approving, or managing the contracts happen faster, better, with reduced risks. We build AI first products, and automate manual work, freeing up our customers time and accelerating their businesses.
You will be joining the Evisort AI team, which functions as a startup within Workday. This is your opportunity to build at the pace of innovation of a startup, while backed by the enormous support and impacting Workday's incredible customer base of 70M+ users.

About the Role

As a Machine Learning Engineer, you will help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis. You will collaborate with other engineers to deliver ML solutions across Workday's product ecosystem and utilize software and data engineering stacks to enable training, deployment, and lifecycle management of various ML models. You will develop and deploy new products at scale and leverage Workday's vast computing resources on rich datasets to deliver transformative value to our customers.

In addition to contributing to feature and service development, you must have an approach of continuous improvement, passion for quality, scale, and security. You must be curious and prepared to question or challenge choices and practices where they don't make sense to you or could be improved. You also should have a product approach and strong intuition around how ML can drive a better customer experience. Lastly, a strong sense of ownership and teamwork are essential to succeed in this role.

About You

Basic Qualifications

MLE

  • 5+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation

  • 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow

  • 2+ years of professional experience in building services to host machine learning models in production at scale

  • 2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases

  • 2+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)

  • Bachelor's (Master's or PhD preferred) degree in engineering, computer science, physics, math or equivalent

Sr. MLE

  • 6+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation

  • 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow

  • 3+ years of professional experience in building services to host machine learning models in production at scale

  • 3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases

  • 3+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)

  • Bachelor's (Master's or PhD preferred) degree in engineering, computer science, physics, math or equivalent

Other Qualifications:

  • Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation

  • Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases

  • Professional experience in independently solving ambiguous, open-ended problems and technically leading teams

  • Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders

  • Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement.


Workday Pay Transparency Statement

Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.

Primary Location: CAN.BC.VancouverPrimary Location Base Pay Range: $128,000 CAD - $192,000 CADPrimary CAN Base Pay Range: $128,000 - $192,000 CAD


Our Approach to Flexible Work

With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.


At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates' privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.


Workday logo

About Workday

Sourced by ZipRecruiter

Workday's journey began with a transformative idea generated during a breakfast conversation between its founders in sunny California. What set us apart from the start was our people-centric culture, driven by the core value of prioritizing our employees. At Workday, the happiness, growth, and contributions of every team member are at the heart of who we are. Our collaborative and employee-focused culture is the key ingredient for our business success. We not only care for our people but also for the communities and the environment, all while maintaining profitability. Embrace your uniqueness, as we encourage our Workmates to shine brightly in their authentic selves. Our passion and energy make us distinct, and we are inspired to create a brighter workday for everyone.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

Pleasanton, CA, US

Year founded

2005