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Machine Learning Engineer Biotech Jobs in Toronto, ON

Fullscript

Staff, Machine Learning Engineer

Toronto, ON · On-site +1

The Opportunity We're hiring a Staff Machine Learning Engineer to join our AI team and help shape the next generation of Fullscript's AI-powered experiences. You'll work on building innovative AI ...

Cibc

Machine Learning Engineer Co-op

Toronto, ON · On-site +1

To learn more about CIBC, please visit CIBC.com What you'll be doing CIBC's Enterprise AI Infrastructure & ML Ops team is hiring a Machine Learning Engineer Co-op. As an ML Engineer Co-op, you will ...

Redhat

Senior Machine Learning Engineer

Toronto, ON · On-site +1

As a Machine Learning Engineer focused on model optimization algorithms, you will work closely with our product and research teams to develop SOTA deep learning software. You will collaborate with ...

Workday

Senior Machine Learning Engineer

Toronto, ON

Experience: 7+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP. * Programming Mastery: Expert-level proficiency in Python ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

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 ...

Clearway

Machine Learning Developer

Maple, ON · On-site

The Machine Learning Developer is responsible for the design, training and optimization of machine learning models for research and production, ensuring they are scalable, accurate, and reliable.

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Machine Learning Engineer Biotech information

What does a Machine Learning Engineer do in the biotech industry?

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, and why are they important?

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:
What are popular job titles related to Machine Learning Engineer Biotech jobs in Toronto, ON? For Machine Learning Engineer Biotech jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Biotech jobs in Toronto, ON look for? 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 June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Staff, Machine Learning Engineer

Fullscript

Toronto, ON • On-site, Remote

Full-time

Retirement, PTO

Posted 19 days ago

Job description

About Fullscript

We're an industry-leading health technology company on a mission to help people get better. We started in 2011 with one simple idea. Make it easier for practitioners to access the products they trust so they can deliver better care.

That simple idea grew into a platform that powers every part of care. Today, more than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements. Over 10 million patients rely on Fullscript to stay connected to their care plans and follow through on treatment.

We build tools that make care smarter and more human. Tools that save time, simplify decisions, and help practitioners stay closely connected to the people they care for. When everything they need is in one place, they can focus on what matters most: helping people get better.

This is your invitation.

Bring your ideas, your grit, and your care for people.
Join us and shape the future of care.
The Opportunity

We're hiring a Staff Machine Learning Engineer to join our AI team and help shape the next generation of Fullscript's AI-powered experiences. You'll work on building innovative AI capabilities that help clinicians provide better services and help patients improve their health.

This is a senior individual contributor role for someone who can go beyond implementation. In addition to building high-quality systems, you'll help define technical direction, guide architecture decisions, and identify where AI can create meaningful value in clinical workflows. You'll work with a high degree of autonomy and partner closely with engineering, product, analytics, and medical stakeholders to deliver scalable, reliable, and clinically useful AI experiences.

What you'll do
  • Lead the design, development, and deployment of production, multi-turn LLM-powered features, including summarization tools and clinician-facing conversational agents that support follow-up questions and reasoning over clinical context
  • Own backend services in Python that integrate LLM agents with Fullscript's platform and support reliable production use
  • Help define technical direction for prompting, grounding, safety, and orchestration strategies used across clinical AI workflows
  • Establish and improve evaluation approaches for LLM outputs, including accuracy, hallucinations, edge cases, and overall feature quality
  • Shape engineering patterns for model-related workflows, including testing, CI/CD, observability, and version control
  • Partner with medical, product, and engineering teams to identify high-value opportunities for AI and turn them into practical, scalable product capabilities
  • Work cross-functionally with engineering, analytics, and medical SMEs to refine requirements and ensure data and system design support clinical use cases
  • Provide technical leadership across projects by creating clarity in ambiguous problem spaces, guiding tradeoff decisions, and raising the quality bar for the team
  • Stay current with the latest LLM research and emerging AI technologies, and help assess where they can be applied effectively at Fullscript
What you bring to the table
  • 6+ years of experience building and implementing machine learning applications in production, including meaningful experience with LLM-powered agents, conversational experiences, or agent-based workflows
  • A track record of owning complex technical problems end to end and shaping implementation beyond your immediate code contributions
  • Experience designing and deploying AI systems that answer open-ended questions, support follow-up interactions, and operate reliably in production
  • Strong experience with LLM application frameworks and tooling, such as LangChain, LangGraph, or similar orchestration and RAG frameworks
  • Familiarity with evaluation and monitoring frameworks for LLM outputs, conversational quality, and system reliability
  • Knowledge of MCP, agent orchestration patterns, or related approaches for building multi-step AI systems
  • Strong proficiency in Python and SQL
  • Experience making sound technical decisions around quality, safety, maintainability, and scalability in production AI systems
  • Strong communication and collaboration skills, with the ability to work effectively across technical and non-technical stakeholders
Bonus if you have
  • Experience defining technical direction for AI or machine learning systems across multiple projects or teams
  • Experience building clinician-facing, healthcare-adjacent, or other high-trust AI experiences
  • Experience with recommendation systems, personalization, or other applied ML systems beyond LLMs
  • Experience with modern retrieval, grounding, or evaluation patterns for LLM applications
  • Experience working closely with domain experts to build systems in complex or highly contextual problem spaces
What we can offer you
  • Competitive Salaries
  • Remote-first flexibility to work where you work best, with Ottawa, Toronto, or Calgary preferred for this role.
  • Flexible PTO and competitive pay, because work-life balance matters
  • RRSP/401k match and stock options to invest in your future
  • Premium benefits package with customizable coverage, paramedical services, and an HSA.
  • Fullscript discounts to save on high-quality wellness products
  • Continuous learning opportunities to grow your skills and career

Fullscript shares salary ranges to support transparency and help candidates make informed decisions. The range shown reflects base salary only and does not include stock options, wellness stipends, or other benefits that are part of Fullscript's total rewards package.

Final compensation depends on experience, skills, and location. We review pay regularly to stay aligned with market data and internal equity. Benefits and total rewards may vary by region.

Why Fullscript

Great work happens when people feel supported, trusted, and inspired. At Fullscript, we stay curious and keep finding smarter ways to make care better. We grow together, take on new challenges, and focus on impact. We put people first, work as a team, and leave egos at the door.

What to Know Before You Apply

We're grateful for the interest in joining Fullscript. To make sure your application reaches our hiring team, please apply directly through our careers page.

A quick note: Due to the high volume of applications, we're not able to respond to phone or email inquiries about application status. If there's a match, our team will reach out directly.

Fullscript is an equal opportunity employer committed to creating an inclusive workplace. Accommodations are available upon request at [email protected].

All offers are contingent on successful background checks conducted in compliance with federal, state, and provincial laws.

We use AI tools to support parts of the hiring process, including screening and reviewing responses. Final hiring decisions are always made by people and follow all applicable privacy and employment laws in Canada and the U.S.

Learn More
www.fullscript.com
@fullscriptHQ on instagram
@fullscript on YouTube
FullScript on LinkedIn
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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