367 Machine Learning Specialists jobs in Canada

Senior Data Scientist, Artificial Intelligence & Machine Learning

Join to apply for the Senior Data Scientist, Artificial Intelligence & Machine Learning role at BMO

Senior Data Scientist, Artificial Intelligence & Machine Learning

Join to apply for the Senior Data Scientist, Artificial Intelligence & Machine Learning role at BMO

This role is with the AI and Advanced Analytics team that sits within the Chief Data and Analytics Officer for Risk and Finance organization. AI and Advanced Analytics team has the responsibility to create and execute on a roadmap for development and adoption of AI-powered tools across Risk and Finance groups
Key responsibilities and qualifications for the role are as follows:

• Uses Large Language Models and Machine Learning techniques to develop AI-powered tools for a wide range of applications including predictive modeling, financial analysis and risk management.
• Leverages techniques such as prompt engineering, retrieval-augmented generation (RAG), quantization, and low rank adaptation (LoRA) to adapt LLMs to the specific context of the organization.
• Uses advanced Machine Learning techniques to mine and analyze large sets of structured and unstructured data to obtain insights or develop predictive models.
• Designs and develops agentic solutions to transform business processes with a clear goal of increasing efficiency and effectiveness to enhance the firm’s balance sheet and risk management capabilities.
• Keeps principles of Responsible AI front and center in the design of AI-powered tools.
• Works closely with technology teams to productionize and implement developed tools.
• Helps with governance and other activities related to executing the bank’s strategy on AI.
  

• Mathematics, statistics & programming.
• In-depth understanding of large language models.
• In-depth understanding of supervised and unsupervised Machine learning techniques.
• Creative thinking.
• Critical thinking.
• Data visualization.
• Data wrangling.
• Data preprocessing.
• Data driven decision making.
  

• Effective verbal & written communication skills.
• Analytical and problem-solving skills.
• Ability to influence and work collaboratively
• Able to manage ambiguity.
• Influence skills.
• Collaboration & team skills; with a focus on cross-group collaboration.
  

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Part-time

Job function

• Job function

  Engineering and Information Technology

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Get notified about new Senior Software Engineer jobs in Toronto, Ontario, Canada.

Senior Engineering Manager, Developer Experience

Senior Software Engineer (Network Platform Team)

Senior Software Engineer, Business Process & Automation

Senior Software Engineer, Audio-Video Processing (Req ID: 2025-14)

Senior Manager, Developer Security Enablement and Operations

Mississauga, Ontario, Canada CA$105,200.00-CA 151,933.33 2 weeks ago

Senior Software Quality Assurance Specialist - Propulsion Thermal Simulation Lead

Lead Data Scientist - Articial Intelligence Specialist

Lead Data Scientist - Feature Engineering

Toronto, Ontario, Canada CA 150,000.00-CA 200,000.00 1 month ago

Senior Software Engineer, Backend - Fintech

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Date limite pour présenter sa candidature :

Adresse :

Groupe de famille d'emploi :

This role is with the AI and Advanced Analytics team that sits within the Chief Data and Analytics Officer for Risk and Finance organization. The AI and Advanced Analytics team is responsible for creating and executing a roadmap for the development and adoption of AI-powered tools across Risk and Finance groups.

Responsibilities include:

• Utiliser des algorithmes et des technologies analytiques avancés (p. ex., apprentissage machine, apprentissage profond, intelligence artificielle) pour explorer et analyser de grands ensembles de données structurées et non structurées afin d’obtenir des renseignements.
• Concevoir et construire de nouveaux processus pour la modélisation des données.
• Élaborer des modèles prédictifs et tirer parti de la technologie des mégadonnées pour concevoir des solutions qui permettent d’éclairer la prise de décisions d’affaires, d’améliorer l’expérience client et de stimuler la productivité.
• Collaborer avec d’autres professionnels et équipes liés aux données et aux analyses afin d’optimiser, de peaufiner et de faire évoluer l’analyse vers des solutions d’analyse évoluées.

Qualifications :

• Généralement de cinq à sept années d’expérience professionnelle pertinente avec diplôme d’études postsecondaires dans un domaine connexe, ou combinaison équivalente de scolarité et d’expérience.
• Compétences de niveau intermédiaire : Mathématiques, statistiques, apprentissage profond, apprentissage machine, éthique, pensée créative, pensée critique.
• Compétences de niveau avancé : Mégadonnées, visualisation des données, programmation, préparation et prétraitement de données, raisonnement créatif, communication, collaboration, analyse, résolution de problèmes, influence, prise de décisions basées sur les données, connaissances techniques approfondies.

Salaire :

Type de rémunération :

Ce qui précède représente la fourchette et le type de rémunération de BMO Groupe financier. Les salaires varient selon l’emplacement, compétences, expérience, études et qualifications, et peuvent inclure des commissions, primes, avantages sociaux, etc.

À propos de nous :

Chez BMO, notre raison d’être est de faire une différence positive dans la vie de nos clients, collectivités et employés. Nous valorisons la diversité, l’inclusion et offrons un milieu de travail accessible et équitable. Pour plus d’informations, visitez

Join to apply for the Machine Learning Engineer role at Pinnacle

Join to apply for the Machine Learning Engineer role at Pinnacle

Job Title : Machine Learning Engineer - Sports Modeler

Reports to : Machine Learning Technical Lead or Sport Modelling Team Lead

Location : Toronto

About us :

Welcome to Pinnacle, the ultimate destination for sports enthusiasts seeking an exhilarating sportsbook and gaming experience! Established in 1998, we have solidified our position as one of the globe's foremost licensed online gaming companies. With our cutting-edge offerings, we guarantee an electrifying experience that will keep you on the edge of your seat.

Pinnacle invites you to join our team and become an instrumental figure in the exciting realm of sports betting. Our vibrant team is fueled by passion and driven by innovation, working together to redefine the landscape of sports betting and gaming. Together, we constantly strive to surpass limitations and deliver unparalleled experiences to sports enthusiasts worldwide. Prepare yourself for a thrilling journey and discover sports in an entirely new dimension with Pinnacle!

Job Purpose :

We are seeking a Machine Learning Engineer for a role encompassing sports modelling, algorithm development, and both building and utilizing tools to support model evaluation and performance analysis. The ideal candidate will have experience working with traditional statistical learning techniques, probabilistic graphical models, and a deep understanding of data analysis and visualization. Proficiency in R is strongly preferred, as is a demonstrated ability to work with large datasets, develop intuitive visualization tools, and deliver insights to inform decision-making. A passion for sports, sports analytics, sports betting, and fantasy sports is also beneficial.

The ideal candidate should have :

• A degree in Computer Science, Statistics, Mathematics, or a related field. Advanced degrees (MS / PhD) specializing in Machine Learning or Statistics are highly desirable.
• Experience with statistical computing in R, with proficiency in modern R packages and technologies such as data.table, dplyr, tidyr is preferred.
• Strong experience building and utilizing existing tools for model evaluation and performance analysis, ideally in R utilizing visualization tools such as ggplot2, shiny, and plotly.
• Deep knowledge of traditional machine learning techniques, such as linear regression, generalized linear models (GLMs), and generalized additive models (GAMs).
• Expertise in probabilistic graphical models, such as directed acyclic graphs (DAGs) and Markov chains, is a strong plus.
• Demonstrated ability to work with large datasets efficiently and develop optimized code, with tools such as Rcpp, microbenchmark, and profviz, is a big plus.
• Experience working with relational databases such as SQL server, PostgreSQL or Google BigQuery.
• A passion for sports, sports analytics, sports betting, or fantasy sports is highly beneficial.

Working Environment : We foster a collaborative environment that emphasizes skill development, mentorship, and tackling a combination of theoretical and real-world problems in sports analytics and betting. With opportunities for continuous learning and growth, team members expand their technical expertise, gain exposure to new technologies, and deliver impactful solutions in a fast-paced, dynamic industry, supported by open communication and mutual respect.

Core Responsibilities : This is a key role within the team, focusing primarily on building and iterating on predictive models, and developing tools to support model evaluation and performance analysis. These models are released to real production environments, analyzed by expert traders, and eventually form the basis of the initial layer of our odds engine. The performance of these models are analyzed against our sharp betting clientele and constantly iterated upon based on the changing dynamics of market trends, data feed quality, sport-specific gameplay, and rule changes.

Technical Expertise : A strong background in statistics, machine learning, and algorithm development is essential. Candidates will ideally have advanced proficiency in R, with experience coding for production environments. However, for those who are less experienced with R directly, we offer a highly supportive internal ecosystem with dedicated guidance to help develop R skills.

Development Expertise : Understanding of software principles and functional coding principles are necessary. Experience deploying models to production in real world applications with feedback from senior teammates and key stakeholders is a strong plus. Experience with code optimization, Rcpp / C++, and R package development are highly valued. Experience using tools like GIT, JIRA, along with participating in peer reviews to ensure high quality, maintainable code in a collaborative development environment is highly desired.

Data and Evaluation Focus : Demonstrated ability to work with large datasets, optimize code for performance, and deliver insights through well-designed tools is critical. Experience with Shiny for building tools and ggplot2 or similar libraries for data visualization is highly valued.

Soft Skills : Strong communication skills (both verbal and written) are required to convey complex information effectively. The ideal candidate will also have strong analytical, conceptual, and problem-solving abilities, with attention to detail.

Domain Knowledge : A thorough understanding and passion for sports, sports analytics, and sports betting markets is highly desirable. Experience working with sports betting markets, financial markets, or similar applications is a plus.

Bonus Skills : Experience with Bayesian techniques and their implementation to solve practical problems with software like STAN or NIMBLE, is a plus, though not required. Familiarity with Rcpp, C++, and tools like profvis, microbenchmark, parallel is a strong plus

We are an equal opportunity employer dedicated to fostering an inclusive and diverse workplace. We prioritize hiring the best candidates based on their skills and qualifications, irrespective of race, gender, age, religion, or any other characteristic. Our strength lies in our diverse teams, and we proudly celebrate and empower everyone to embrace and promote diversity throughout their time with us.

Seniority level

Seniority level

Associate

Employment type

Employment type

Full-time

Job function

Job function

Information Technology and Research

Gambling Facilities and Casinos

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Machine Learning Engineer • Toronto, ON, Canada

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This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

115,000.00 / yr - $130,000.00 / yr

Direct message the job poster from Harnham

Building AI / ML & Data / Software Engineering Teams Across The US

Location : Toronto

Salary : $15,000 – $1 0,000 base + 15% Bonus

Company Overview :

Join a fast-growing, innovative organization at the forefront of artificial intelligence, committed to pushing boundaries in generative AI and Large Language Models (LLMs). They are solving cutting-edge problems with scalable machine learning and deploying solutions across industries.

Role Overview :

As a Senior Machine Learning Engineer with a specialization in LLMs, you will play a pivotal role in architecting, building, and deploying high-impact machine learning systems. You’ll collaborate cross-functionally with data scientists, research engineers, and business stakeholders to drive real-world applications of advanced AI.

Key Responsibilities :

• Lead development of ML / LLM solutions for tasks like summarization, classification, Q&A, and RAG.
• Collaborate on transformer models (e.g., GPT, LLaMA, Claude, Mistral).
• Fine-tune and optimize pre-trained LLMs using best practices.
• Build and maintain ML pipelines with MLFlow, Airflow, or Kubeflow.
• Partner with MLOps / DevOps to ensure scalable, secure production systems.
• Deploy models using Docker, Kubernetes, and serving frameworks (e.g., TensorFlow Serving, TorchServe, FastAPI).
• Implement model versioning, blue-green / canary deployments, and performance monitoring.
• Develop scalable data pipelines for text and embeddings.
• Stay up to date with LLM / AI research and apply findings to real-world problems.
• Document workflows and support knowledge sharing across the team.

Required Qualifications :

Preferred Experience :

Compensation and Benefits :

How to Apply :

To express your interest in this opportunity, please submit your CV via the "Apply" link on this page. We look forward to hearing from you!

Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

Analyst

Industries

Research Services and Software Development

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Machine Learning Engineer II, Tim Hortons

Software Engineer, Backend (All Levels / All Teams)

Toronto, Ontario, Canada CA$155,0 0.00-CA 180,000.00 16 hours ago

Software Engineer I, Entry Level (Fall 2024-Spring 2025) - Toronto

Data Scientist, Decisions - New Product Development

Applied Machine Learning Scientist (Early Career)

Toronto, Ontario, Canada CA 150,000.00-CA 400,000.00 3 weeks ago

Data Scientist, Algorithms, Real-Time Supply Management

Data Scientist, Causal Inference - New Product Development

Data Scientist, Algorithms - Rider Pricing (Optimization)

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Posted onJuly 31, 2025 by Employer details Wireframe Solutions

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machine learning engineer

Posted onJuly 31, 2025 by Employer details Wireframe Solutions

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Job details

• Location Toronto , ON
• Work location Hybrid
• Salary 80,000 to 100,000 YEAR annually
• Terms of employment Permanent employment Full time
• Starts as soon as possible
• vacancies 1 vacancy
• Source indeed.com #

• Toronto, ON

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Join to apply for the Machine Learning Engineer role at Valence

Join to apply for the Machine Learning Engineer role at Valence

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Valence has built the first-to-market AI native coaching platform for enterprise, offering personalized, expert, and human-like guidance & support to any leader or employee. At Valence, we're not just talking about the future of work – we're actively shaping it.
From your first interaction with us, you'll notice we're different. By working here you won't just implement solutions for our clients; you'll be helping to architect the future of leadership in the age of generative AI. And we'll be honest – this is not for everyone. But for those with an insatiable desire to work fast on complex, unsolved challenges with some of the best talent in tech, this could be the career-defining opportunity you've been waiting for.
The Role
This role is a Machine Learning Engineer role for our conversational AI coaching product designed for Fortune 500 enterprises, reporting into our Head of AI. In this role you will implement, and optimize machine learning models that power our coaching insights and recommendations. This role is focused on the development and optimization of machine learning models and algorithms, optimizing the underlying ML infrastructure and model development. This role will directly impact our product's core and shape the future of AI-driven leadership coaching for Fortune 500 enterprises.
About Valence
We're a Series A B2B SaaS company, backed by Insight Partners, that's pioneering the first generative AI leadership coach for large enterprises. Our mission is to transform how the world's biggest companies approach learning and development, helping teams work better together. We've been featured in Harvard Business Review, and our client list reads like a Who's Who of global business, including Coca-Cola, Nestlé, General Mills, ServiceNow, AstraZeneca, Prudential, Citi, CVS and Bristol Myers Squibb.
What You'll Do

• You will develop scalable data pipelines, optimize models for performance and accuracy, and evaluate them to ensure they are production-ready.
• Develop, design and implement improvements in user experience in conversational interactions leveraging LLMs in new ways to advance product goals
• Work with the product team to analyze user behavior and prioritize evolving requirements
• Experiment at a high velocity, conducting statistical analyses, to optimize the end user experience
• Research and development on new Conversational AI approaches leveraging cutting edge LLM/NLP advancements
• Documentation of models, prompts, and processes to increase replicability and drive quality improvements.
• Stay current with the latest leading research advancements in ML, LLMs, and Conversational AI
• Support other coding and feature development where required
  

• Bachelor's degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience
• 3+ years of professional experience (or equivalent) in software engineering, AI/ML development (ideally including a Master's or Ph.D. in Computer Science, ML, Data Science, or a related field)
• Practical experience and theoretical knowledge of language technologies such as: dialogue/conversational systems, NLP, and Information Retrieval
• Strong foundation in data structures, algorithms, and software engineering principles
• Proficiency in Python and relevant deep learning frameworks; training (e.g. PyTorch, Tensorflow, JAX, Hugging Face Transformers/Adapters), serving (e.g., Hugging Face TGI//outlines, vLLM)
• Experience with LLM model development and deployment ideally including experience with model distillation, supervised fine-tuning using RLHF/DPO, and automatic prompt tuning (e.g. DSPy, TextGrad)
• Experience with cloud deployment of ML systems (e.g., AWS, GCP, Azure) including and open systems (e.g. Docker and Kubernetes) and associated ML services
• Strong analytical and problem-solving skills
• Experience structuring and running data-backed experiments
• Strong written and verbal communication skills
• Exposure to early-stage startups, preferably B2B SaaS
  

• Ownership of projects and strategic priorities regardless of seniority
• Strong ties to the executive team, a culture of transparency and engagement with strategic decisions
• Options from day one, which means you will be on the ownership track right away
• Competitive salary and equity packages
• Comprehensive health coverage (medical, dental, and vision) from day 1
• Provision of anything you need to be successful - learning tools, hardware, office equipment, software
• Generous PTO, company-wide R&R shutdowns and paid leave for parents.
• A WFH stipend, phone stipend and support to work in a We Work or other space as preferred
  

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Technology, Information and Internet

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Data Scientist, Decisions - New Product Development

Software Engineer, Backend (All Levels / All Teams)

Data Scientist, Algorithms, Real-Time Supply Management

Software Engineer I, Entry Level (Fall 2024-Spring 2025) - Toronto

Applied Machine Learning Scientist (Early Career)

Data Scientist, Causal Inference - New Product Development

Toronto, Ontario, Canada CA$125,000.00-CA$150,000.00 2 weeks ago

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Ideogram is on a mission to make professional-quality design accessible to everyone. We’re building an AI-native application that helps creative individuals and teams produce high-quality content faster and at a lower cost. We are pushing the boundaries of what’s possible with AI, with a focus on creativity and a high standard for trust and safety. Our headquarters is in downtown Toronto, and we have a growing presence in NYC. Read our Ideogram 3.0 and Canvas blog posts, and try our product at ideogram.ai to get a glimpse of what we're building.

About the role

As a Machine Learning Engineer, you will build and deploy state of the art machine learning models at scale. You will work with a creative and ambitious team of engineers and researchers who are building the future of the creative economy with highly complex challenges.You will work directly with some of the best machine learning experts in the world, who have an exceptional track record of setting the vision and executing generative AI projects.

What we're looking for

• 5+ years of experience in developing machine learning models in JAX, PyTorch, or TensorFlow

• Experience in implementing Machine Learning foundations (e.g., Transformer, VAE, Denoising Diffusion models) from scratch

• Track record in machine learning innovation and familiarity with Deep Learning and advanced Machine Learning

• End-to-end understanding of generative media applications and excitement for pushing the state-of-the-art in generative AI

• Ability to debug machine learning models to iteratively improve model quality and performance

• Nice to have: Familiarity with kubernetes and docker

• Optional: Experience in low-level machine learning optimization, e.g., writing CUDA kernel code

Founding Team

Our founding team consists of world-renowned AI experts including Mohammad Norouzi, Jonathan Ho, William Chan, and Chitwan Saharia. This team has previously led transformative AI projects at Google Brain, UC Berkeley, CMU, and the University of Toronto. Our fundamental work in AI includes: Imagen: Google’s text-to-image system, Imagen Video for video synthesis, Denoising Diffusion Models, which is the foundation of the recent generative media transformation.

Company Culture

We're a single flat team that transcends engineering, research, product, and operation roles. Everyone is willing to do whatever is necessary to make our company and customers successful. We believe that a small, dedicated team with a collaborative culture can move faster and build better and more coherent products than large hierarchical organizations. At Ideogram, we provide mentorship and support to help our employees grow with the company and achieve their ambitious career goals.

Ideogram is committed to welcoming everyone, regardless of gender identity, orientation, or expression. Our mission is to remove exclusivity and barriers and encourage new thinking and perceptions, in a space of belonging. It is not about race, gender, or age, it is about the people.

Join to apply for the Machine Learning Engineer role at PENN Interactive

Join to apply for the Machine Learning Engineer role at PENN Interactive

PENN Entertainment, Inc. is North America’s leading provider of integrated entertainment, sports content, and casino gaming experiences. From casinos and racetracks to online gaming, sports betting and entertainment content, we deliver the experiences people want, how and where they want them.
We’re always on the lookout for those who are passionate about creating and delivering cutting-edge online gaming and sports media products. Whether it’s through ESPN BET, Hollywood Casino, theScore Bet Sportsbook & Casino, or theScore media app, we’re excited to push the boundaries of what’s possible. These state-of-the-art platforms are powered by proprietary in-house technology, a key component of PENN’s omnichannel gaming and entertainment strategy.
When you join PENN Entertainment’s digital team, you’ll not only work on these cutting-edge platforms through theScore and PENN Interactive, but you’ll also be part of a company that truly cares about your career growth. We’re committed to supporting you as you expand your skills and explore new opportunities.
With locations throughout North America, you can build a future at PENN Entertainment wherever you are. If you want to challenge conventions in gaming, media and entertainment, we want to talk to you.
About The Role & Team
The Data Science & Machine Learning team is responsible for building models and APIs to help improve all of Penn Entertainments digital offerings. Our team values creativity, collaboration, ingenuity, and ownership.
As a Machine Learning Engineer, you'll be instrumental in crafting the next generation of user experiences. You will design, build, and deploy sophisticated machine learning models and infrastructure that directly impact how users discover content, engage with our community, and explore the full spectrum of Penn Entertainment's offerings. This role offers a unique chance to contribute to high-impact projects while helping to advance our cutting-edge ML platform.
About The Work
We’re focused on projects that directly improve user engagement and satisfaction. Some examples include:

• Personalized Recommendation Engines – Help users discover the games, promotions, and content they care about most through behavioral, contextual, and collaborative filtering models.
• Chat Toxicity Detection – Ensure a safe and welcoming community environment with NLP-based classification.
• Cross-sell Propensity Modeling – Predict which offerings resonate with each user and surface the right experience at the right time.
• Dynamic Personalization – Enable real-time decision-making in product features, content feeds, and user journeys using machine learning.
  

• Build and optimize end-to-end machine learning pipelines from data ingestion to deployment.
• Work closely with Product, Marketing, and Operations teams to align ML solutions with business goals.
• Improve our ML platform and deploy infrastructure using MLOps best practices.
• Evaluate and integrate new tools, models, and frameworks to enhance scalability and performance.
• Clearly communicate technical concepts to both technical and non-technical stakeholders.
• Document your systems and workflows using Git, Confluence, and related tools.
  

• 3+ years of professional experience as a Machine Learning Engineer or in a similar role.
• A background in Computer Science, Data Science, Engineering, or a related technical field.
• Strong programming skills in Python and SQL. Bonus for Go, Rust, Scala, R, or C++.
• Experience with Docker, Kubernetes, Terraform, and scalable deployment tools.
• Hands-on experience building CI/CD pipelines for ML systems.
• Proficiency in orchestration tools like Airflow, Kubeflow, or Dagster.
• Experience working on or contributing to dbt projects.
• Comfort working in cloud environments like AWS, GCP, or Azure.
• Familiarity with ML frameworks such as PyTorch, TensorFlow, Keras, or similar.
  

• Experience building real-time personalization or recommendation systems at scale.
• Familiarity with virtual feature stores like Feast or Featureform.
• Exposure to working with or deploying large language models (LLMs) in production.
  

• Competitive compensation package
• Fun, relaxed work environment
• Education and conference reimbursements.
• Parental leave top up
• Opportunities for career progression and mentoring others
  

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Gambling Facilities and Casinos

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Get notified about new Machine Learning Engineer jobs in Toronto, Ontario, Canada.

Frontend Software Engineer (Remote - Canada)

Full Stack Software Engineer (Remote Canada)

Front End and Full Stack Developer (Remote - Ontario, Canada ONLY)

Intermediate Software Developer, Frontend

Toronto, Ontario, Canada CA$125,000.00-CA$150,000.00 1 month ago

Software Engineer, Backend - (Consumer - Products)

Senior Software Developer – Lab Integrations

Software Engineer I (Consumer Servicing)

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Are you seeking an exciting opportunity to work with groundbreaking, well-known Web3, Blockchain and Fortune 100 organizations?

Our client in Toronto is looking for a skilled Machine Learning Engineer to join their well-funded venture (USD 8.5M raised), focused on tackling unique treasury, accounting, and asset management challenges. They have processed over $100B in transactions in the last year!

About the Role :

As a Machine Learning Engineer, you will be at the forefront of innovation, collaborating with a dynamic team to shape the product vision and build AI products relating to finance and crypto.

We seek individuals with an entrepreneurial spirit, genuine enthusiasm for Web3 and Blockchain, and a passion for mastering web technologies and techniques. Your expertise will play a vital role in solving complex problems and driving the evolution of their products.

Responsibilities :

• Design, develop, and deploy machine learning models for various applications in crypto finance, such as predictive analytics, fraud detection, transaction classification, and risk management.
• Fine-tuning ML models for specific use cases, such as developing heuristics that detect fraudulent transactions, enhancing reconciliation processes by analyzing historical transaction data and providing greater explainability for the on-chain transactions our customers must later reconcile.
• Automating the deployment of ML models to production environments using tools and frameworks like Docker, Kubernetes, and CI / CD pipelines, ensuring high availability, low latency, and accuracy.
• Implementing monitoring solutions to track model performance metrics, detect drift, and trigger re-training to maintain prediction accuracy and reliability.
• Working with the Platform Engineering team, improving the state of the company's architecture to unlock faster training and deployment cycles.
• Collaborating with the full-stack engineering team to ensure seamless integration of ETL processes, data warehousing, and streaming to facilitate efficient model training and evaluation.

Does this sound like you?

• 5+ years of experience working on production web apps
• Built ML models from scratch and deployed them into production environments
• Familiarity and interest in accounting, FinTech products, and / or crypto
• Hands-on experience with ML frameworks (TensorFlow, PyTorch)
• Hands-on experience with orchestration tools (Airflow, Docker, and Kubernetes)
• Experience with building and maintaining processing pipelines (Apache Spark, Airflow, or Kafka)
• A Bachelor's Degree in Computer Science or a related field or equivalent experience demonstrating your commitment to continuous learning and growth.
• Strong communication skills when interacting with tech and non-tech stakeholders

Perks and Benefits :

• The role is based in Toronto; local candidates open to coming onsite a few days a week are preferred.
• Flexibility in work arrangements, including remote opportunities.
• Competitive salary and attractive equity options to share in the venture's success.
• Opportunities for growth and taking on exciting responsibilities.
• Exposure to cutting-edge technologies
• Enjoy the fast-paced and dynamic environment of working at a startup, combined with the stability of a larger company
• Work alongside a world-class team from top tech companies

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Machine Learning Engineer • Toronto, ON, Canada