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Machine Learning Engineer Biotech Jobs in Toronto, ON

United Airlines

Machine Learning Engineer

Toronto, ON · On-site

Five or more years building Deep Learning or Machine Learning models in production environments ... engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data ...

Redhat

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 ...

BDO Canada

Senior Machine Learning Engineer

Toronto, ON

CA$84K - CA$128K/yr

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

BDO Canada

Senior Machine Learning Engineer

Oakville, ON

CA$84K - CA$128K/yr

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

Td

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$170K - CA$250K/yr

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Architect scalable machine learning and ...

TheAppLabb

Sr. Machine Learning Engineer

Toronto, ON · On-site

We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful insights that drive strategic decision-making. The Opportunity Summary We are seeking an experienced ...

The App Labb

Sr. Machine Learning Engineer

Toronto, ON · On-site

We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful insights that drive strategic decision-making. The Opportunity Summary We are seeking an experienced ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Day-to-day as a Machine Learning Engineer: * Join a world-class team of AI developers with an extensive track record. * Architect scalable machine learning and Gen AI systems that integrate with ...

Serve Robotics

Lead Machine Learning Engineer

Toronto, ON · Remote

$225K - $260K/yr

Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...

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All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Toronto, ON

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:
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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.
Machine Learning Engineer (Canada)

Machine Learning Engineer (Canada)

Tiger Analytics Inc.

Toronto, ON

Full-time

Posted 28 days ago

Job description

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for a motivated and passionate Machine Learning Engineers for our team.

As part of this job, you will be responsible for:

  • Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
  • Creating Scalable Machine Learning systems that are highly performant
  • Building reusable production data pipelines for implemented machine learning models
  • Writing production-quality code and libraries that can be packaged as containers, installed and deployed

Requirements

  • Bachelor's degree or higher in computer science or related, with 5+ years of work experience
  • Ability to collaborate with Data Engineers and Data Scientist to build data and model pipelines and help running machine learning tests and experiments
  • Ability to manage the infrastructure and data pipelines needed to bring ML solution to production
  • End-to-end understanding of applications being created and maintain scalable machine learning solutions in production
  • Ability to abstract complexity of production for machine learning using containers
  • Ability to troubleshoot production machine learning model issues, including recommendations for retrain, revalidate, and improvements
  • Experience with Big Data Projects using multiple types of structured and unstructured data
  • Ability to work with a global team, playing a key role in communicating problem context to the remote teams
  • Excellent communication and teamwork skills

Additional Skills Required:

  • Python, Spark, Hadoop, Docker, with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design
  • Test-driven development (prefer py. test/nose), experience with Cloud environments
  • Proficiency in statistical tools, relational databases, and expertise in programming language like python/SQL is desired.

Good to have:

  • Knowledge of ML frameworks like Scikitlearn, Tensorflow, Keras, etc.
  • Knowledge of MLflow, Airflow, Kubernetes
  • Knowledge on any of the cloud-native MLaaS offerings like AWS SageMaker, AzureML, or Google AI platform

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

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