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Machine Learning Research Intern Jobs in Montreal, QC

LawZero

Machine Learning Manager

Montreal, QC

We are seeking a Machine Learning (ML) Manager to join our growing team dedicated to a novel AI ... As both a people manager and technical leader, you will guide research team members and spearhead ...

LawZero

Senior ML Research Scientist

Montreal, QC

We are seeking a Senior Machine Learning (ML) Research Scientist to join our team working on a novel AI safety agenda. In this role, you will design and implement innovative ML models aimed at ...

Jumio

Senior Machine Learning Engineer

Montreal, QC · On-site

We're looking for a Senior Machine Learning Engineer with strong computer vision expertise to join ... Research Publications in top computer vision venues (CVPR, ICCV, ECCV) * Large Scale Search:

LawZero

Senior ML Research Developer

Montreal, QC

We are seeking a senior machine learning (ML) research developer to join our team working on a novel AI safety agenda. In this role, you will work closely with ML research scientists to solve ...

SAP

Senior AI Machine Learning Engineer

Montreal, QC · On-site

About the Role We are hiring a Senior Machine Learning Engineer Scientist to lead the development ... You will own key architecture decisions, mentor engineers and researchers, and build high ...

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All JobsMachine Learning Research Intern JobsMachine Learning Research Intern Jobs in Montreal, QC

Machine Learning Research Intern information

See Montreal, QC salary details

$18.9K

$121.5K

$221.9K

How much do machine learning research intern jobs pay per year?

As of Aug 19, 2026, the average yearly pay for machine learning research intern in Montreal, QC is $121,475.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,383.00 and $172,014.00 per year, depending on experience, location, and employer.

What does a machine learning research intern do?

A Machine Learning Research Intern assists in the development, implementation, and evaluation of machine learning models and algorithms under the supervision of experienced researchers. They often preprocess data, run experiments, analyze results, and contribute to research papers or technical reports. Interns also stay up to date with the latest advancements in machine learning, participate in team meetings, and sometimes help in coding or optimizing existing models. This role provides hands-on experience in applying theoretical knowledge to real-world problems and prepares interns for careers in AI research or development.

What are the key skills and qualifications needed to thrive as a machine learning research intern?

To thrive as a Machine Learning Research Intern, you need a strong foundation in mathematics, statistics, programming (especially Python), and an understanding of machine learning algorithms, typically supported by ongoing or completed studies in computer science or related fields. Familiarity with technical tools such as TensorFlow, PyTorch, scikit-learn, and experience with data analysis libraries are commonly required. Curiosity, problem-solving ability, and effective communication skills help interns stand out by enabling them to collaborate, share insights, and adapt to new research challenges. These skills ensure interns can contribute meaningfully to research projects, quickly learn new techniques, and effectively communicate their findings.

What are some typical challenges faced by machine learning research interns during their projects?

Machine Learning Research Interns often encounter challenges such as dealing with limited or messy datasets, tuning complex model architectures, and balancing innovative research with practical implementation. Additionally, they may need to quickly familiarize themselves with unfamiliar frameworks or tools and effectively communicate technical findings to both technical and non-technical team members. Successfully navigating these challenges can provide valuable learning experiences and help interns build strong problem-solving skills for future roles.

What are popular job titles related to Machine Learning Research Intern jobs in Montreal, QC?

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Machine Learning Research Intern jobs near you
Infographic showing various Machine Learning Research Intern job openings in Montreal, QC as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 19% Part Time, 3% Contract, and 1% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $121,475 per year, or $58.4 per hour.

Machine Learning Research Scientist

Valence Labs

Montreal, QC • Hybrid

Full-time

Re-posted 18 days ago

Job description

About Valence Labs

Valence Labs is Recursion's frontier AI research engine. We lead high-impact research
programs designed to materially expand Recursion's ability to discover and develop medicines for complex diseases. Our team balances near-term pragmatism with a long-term view of where the field is heading in the next 3-5 years, incubating, designing, and productizing the approaches we believe will define the future of drug discovery. 

Our work is driven by optimism, purpose, and a shared vision for a healthier tomorrow. We publish in top journals and conferences, contribute to open science, and engage with some of the world's most active ML-for-drug-discovery research communities. Our teams are based in London and Montreal, with deep ties to Mila, the world's largest deep-learning research institute.

About the role

We are seeking a Research Scientist with a hybrid research-engineering mindset to join our team. In this role, you will be at the forefront of developing generative architectures and foundation models that ground machine learning in real-world biological discovery. 

A successful candidate will have most of the following:

  • PhD (or equivalent) with significant academic or industry research experience in a related technical field involving machine learning applied to drug discovery.
  • Scientific knowledge of biology, chemistry, or physics, along with previous experience working in a scientific environment across disciplines.
  • Impactful research track record, including designing new neural networks to model molecular or biological systems, proposing new theories, or applying novel ML techniques to real-world problems.
  • Strong technical and engineering skills, including the ability to rapidly prototype ML models (Python proficiency required; Rust preferred for high performance molecular encoding or data pipelines).
  • Leadership and communication skills, including a lead authorship record in peer-reviewed conferences (e.g., NeurIPS, ICML, ICLR) or journals (e.g., Nature, Science, JACS).
  • Interdisciplinary empathy, with a proven ability to work effectively with interdisciplinary teams of dry and wet scientists.

Key Responsibilities 

  • Model Innovation: Research and develop state-of-the-art architectures (e.g., flow matching, diffusion models, geometric deep learning) tailored to specific biological or chemical challenges.
  • Scalable Engineering: Build and maintain ML systems capable of processing massive datasets on high-performance compute clusters (BioHive).
  • Biological Grounding: Ensure ML predictions are biologically trustworthy and actionable by collaborating closely with drug discovery teams.
  • Open Science & Collaboration: Publish findings in top-tier venues and contribute to the broader scientific community. 

Working Location & Compensation:

This is an office-based, hybrid position at either of our offices located in Montreal, Quebec, Canada. Employees are expected to work in the office at least 50% of the time.

Compensation packages are competitive and commensurate with the skills and level of experience required for this role. In addition to base salary you will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. 

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