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Machine Learning Engineer Biotech Jobs in Toronto, ON

ServiceNow

Senior Machine Learning Engineer

Toronto, ON · On-site +1

The Machine Learning Developer designs, builds, ships, and operates applications whose core behavior is model-driven rather than explicitly authored. The Developer builds the engine behind ServiceNow ...

Thri5 Inc.

AI / Machine Learning Engineer

Toronto, ON · On-site

Your Role As an AI / Machine Learning Engineer at Thri5, you'll help build the agent layer that powers our System of Actions. You'll design and implement multi-agent Co-pilot systems that orchestrate ...

YO AI Labs

Machine Learning Engineer - Remote

Toronto, ON · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software ...

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Machine Learning Engineer Biotech information

What does a machine learning engineer do in biotech?

A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.

How do machine learning engineers in biotech typically collaborate with research scientists and domain experts?

Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.

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

To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.

What is the difference between Machine Learning Engineer Biotech vs Data Scientist Biotech?

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech companies, healthcare, research institutions

While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.

What are the most commonly searched types of Machine Learning Engineer Biotech jobs in Toronto, ON?

The most popular types of Machine Learning Engineer Biotech jobs in Toronto, ON are:

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For Machine Learning Engineer Biotech jobs in Toronto, ON, the most frequently searched job titles are:

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The top searched job categories for Machine Learning Engineer Biotech jobs in Toronto, ON are:

Machine Learning Engineer Biotech jobs near you
Infographic showing various Machine Learning Engineer Biotech job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer (Toronto, ON)

Traffix

Toronto, ON

Full-time

Re-posted 14 days ago

Job description

Introduction: As a Machine Learning Engineer I at TRAFFIX you will work with your colleagues to support the productization of data models. This involves taking models created by our data science team and assisting in producing viable azure services which can orchestrate and achieve complex calculations utilizing these models as well as your own solutions tandem. Our team is still young and lean, this means that your solutions will likely involve end to end work thus involving database work, function app buildout, and light infrastructuring + solutioning.

Responsibilities: Work with senior team members to ingest product development requirements from cross-functional teams (engineering, product, business) Elicit needs, and translate to workable development tasks Hypothesize approaches and solutions to potential product needs Conduct runtime analysis and solution proofing to plan + design solutions Work with colleagues to create, deploy, and manage software services using Azure-based technologies Create detailed technical solution designs + documentation for technical projects Develop function-based solutions using backend + solution languages such as Python and C# Develop software that integrates and ties together data products from our data team Contribute to data model products and heuristic approaches Ensure use of best practices, reuse of core components and common design paradigms for developments Oversee and/or implement UAT testing of solutions. Coordinate with colleagues on releases and implementation of products Requirements: Bachelor's Degree in Computer Science, Mathematics, Statistics or equivalent combination of education and experience. Strong foundation in mathematics, statistic, and software design Knowledge in Data models, data model components and integrating with them High proficiency in API development, Deployment-ready functional development, enterprise level software solutioning High proficiency in solutioning, critical thought process Familiarity performance and solution proofing (Runtime analysis) Experience working with enterprise platforms (Azure, AWS, GCP) Azure strongly preferred Very Strong knowledge in Python High proficiency in SQL Knowledge in C# highly desired Excellent written and verbal communication skills.

Excellent Critical Thinking skills to tackle complex data issues Knowledge in version control (git, CI/CD) Preferences: Logistics industry experience is preferred but not required. Experience in Puppeteer or similar web crawling tools is preferred but not required. Experience in working with large datasets (structured & unstructured) TRAFFIX gives equal consideration for a job and terms and conditions of employment to all individuals and that the employer does not discriminate based on race, color, religion, age, marital status, national origin, disability or sex including sexual orientation, and gender identity or expression.

Department: Technology This is a full time position

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