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Deep Learning Engineer Jobs in Quebec (NOW HIRING)

LawZero

Senior Distributed ML Engineer

Montreal, QC

A track record of contributing to high-quality research projects in deep learning. The title of Engineer is used for reference purposes and may or may not be the official title of the applicant based ...

Td

Sr. Full Stack Data Science Engineer

Montreal, QC

CA$154K - CA$199K/yr

Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models * Solid cloud ... Data Engineering : ETL/ELT Pipelines, Apache Spark Nice-to-Have * Experience in customer analytics ...

LawZero

Senior ML Research Scientist

Montreal, QC

Benchmark and optimize model performance and efficiency along with ML engineers to ensure the ... A track record of contributing to high-quality research projects in deep learning. What we offer

LawZero

Senior ML Research Developer

Montreal, QC

We are seeking a senior machine learning (ML) research developer to join our team working on a ... A track record of contributing to high-quality research projects in deep learning. What we offer

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Deep Learning Engineer information

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Engineer or AI research director, often involving advanced skills in machine learning frameworks, data modeling, and large-scale system development. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in cutting-edge AI research environments.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What are the key skills and qualifications needed to thrive in the Deep Learning Engineer position, and why are they important?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What engineers make $500,000?

Senior engineers in high-demand fields such as software, data science, and machine learning can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. Roles like senior software engineers, machine learning engineers, and data architects at large tech companies or startups often reach this compensation level through base salary, bonuses, and stock options.

What do deep learning engineers do?

Deep learning engineers develop and implement neural network models to solve complex problems such as image recognition, natural language processing, and speech analysis. They work with large datasets, use frameworks like TensorFlow or PyTorch, and often require knowledge of programming, mathematics, and machine learning principles.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What engineers make $300,000 a year?

Senior deep learning engineers and AI specialists with extensive experience, advanced skills in machine learning frameworks, and strong domain knowledge can earn $300,000 or more annually. These roles often require advanced degrees, certifications, and work in high-demand industries such as technology, finance, or healthcare, typically involving leadership responsibilities and complex project management.
What are popular job titles related to Deep Learning Engineer jobs in Quebec? For Deep Learning Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Deep Learning Engineer jobs in Quebec look for? The top searched job categories for Deep Learning Engineer jobs in Quebec are:
Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Quebec as of July 2026, with employment types broken down into 74% Full Time, 24% Part Time, and 2% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution.

Senior Distributed ML Engineer

LawZero

Montreal, QC

Other

Medical, Retirement, PTO

Posted 24 days ago

Job description

We are seeking a senior distributed 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 difficult training and inference problems using very large models.

Key Responsibilities
  • Collaborate with researchers to accelerate research, model training and inference, and facilitate the use of large-scale models in distributed computing environments.
  • Investigate performance bottlenecks, profile research experiment code, debug reported issues, and optimize the utilization of computing resources.
  • Develop tools and libraries to simplify and orchestrate the use of distributed computing resources for research experiments.
  • Establish, document, and maintain best practices for large-scale, distributed ML model development workflows.
Skills and Qualifications
  • A degree in a relevant computer science field (e.g., computer science, computer engineering, software engineering) is required. An advanced degree (master's or PhD) related to machine learning or distributed ML systems is preferred but not required if the candidate demonstrates exceptional abilities and experience.
  • 3+ years of experience in designing and implementing distributed ML training frameworks, with recent experience using e.g. Megatron, DeepSpeed, HuggingFace Accelerate, FSDP, vLLM,  and/or verl.
  • Ability to collaborate effectively with cross-functional teams, document best practices, and stay updated with the latest advancements in ML and software development.
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and workload managers (e.g., Ray, SLURM).
  • Experience with GPU profiling tools (e.g. PyTorch profiler, PyProf, NVIDIA Nsight).
  • Familiarity with containerization tools (e.g., gRPC, Docker, Kubernetes).
  • Familiarity with data infrastructures and platforms (e.g., vector databases).
  • A track record of contributing to high-quality research projects in deep learning.

The title of Engineer is used for reference purposes and may or may not be the official title of the applicant based on jurisdiction.

What we offer

  • The opportunity to contribute to a unique mission with a major impact.
  • Comprehensive health benefits (including mental health and wellness management account)
  • 20 days of vacation per year upon start
  • Employer contribution of 4% to your retirement savings, with no required employee matching
  • Additional compensation totaling 8% of your salary to apply towards additional retirement savings or bonuses (independent of group and individual performance)
  • A team of passionate world-class experts in their field
  • A collaborative and inclusive work environment in our vibrant office space in the heart of Little Italy, in the trendy Mile-Ex district, close to public transportation

Apply