ZipRecruiter

Log In

1

Deep Learning Developer Jobs in Toronto, ON (NOW HIRING)

Synechron

Sr. GenAI Engineer

Toronto, ON · Hybrid

CA$130K - CA$145K/yr

Our challenge Client Capital Markets is seeking a highly skilled AI Engineer with deep expertise in Generative AI, neural networks, and transfer learning to support the development of an innovative ...

Waabi

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions that ...

Waabi

Senior / Staff Perception Engineer

Toronto, ON

CA$158K - CA$269K/yr

You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions that ...

Workday

Principal AI Engineer

Toronto, ON

Engineering, but brighter. About the Role As a Principal AI Engineer in Agent Factory, you'll ... Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms ...

Apertera

Generative AI Engineer

Toronto, ON · On-site

... deep learning frameworks such as TensorFlow or PyTorch and optimizing performance on diverse ... Work closely with software and DevOps engineers to deploy GenAI models. * Document code, algorithms ...

Munich Re

Senior ML Engineer

Toronto, ON · On-site

Collaborating with cross functional teams (Applied Science, DevOps, Data Engineering, Cloud ... and deep learning, with a proven track record of building, hosting, and deploying ML models on ...

Somi AI

Account Solution Architect

Toronto, ON · On-site

$145 - $175/hr

... engineering role. * Proficiency in Python, with hands‑on experience training, fine‑tuning, evaluating, and deploying deep learning models, including modern LLM architectures. * Experience ...

CoreWeave

Account Solution Architect

Toronto, ON · On-site

... field engineering role. * Proficiency in Python, with hands-on experience training, fine-tuning, evaluating, and deploying deep learning models, including modern LLM architectures. * Experience ...

next page

Showing results 1-20

All JobsDeep Learning Developer JobsDeep Learning Developer Jobs in Toronto, ON

Deep Learning Developer 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 Developer or AI research lead, often involving advanced skills in machine learning frameworks, data modeling, and programming. Such roles usually require extensive experience, specialized knowledge, and may include responsibilities like developing innovative AI solutions or leading AI teams in tech companies or research institutions.

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other roles expected to persist include AI ethics specialists and AI system trainers, as human oversight and ethical considerations remain essential. These jobs involve complex problem-solving and domain expertise that are difficult to fully automate.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

What engineer makes $500,000 a year?

Highly experienced deep learning developers or AI engineers with specialized skills in neural networks, large-scale data processing, and advanced machine learning frameworks can earn $500,000 or more annually, especially in senior or leadership roles at major tech companies or startups. Such roles often require advanced degrees, extensive experience, and a strong track record of deploying impactful AI solutions.

What engineers make $300,000 a year?

Deep learning developers and AI engineers with extensive experience, advanced skills in machine learning frameworks, and strong domain expertise can earn $300,000 or more annually, especially in high-demand industries or senior roles. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups with significant funding.
Deep Learning Developer jobs near you
Infographic showing various Deep Learning Developer job openings in Toronto, ON as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, 25% Hybrid, and 25% Remote job distribution.
Sr. GenAI Engineer

Sr. GenAI Engineer

Synechron

Toronto, ON • Hybrid

CA$130K - CA$145K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 16 days ago

Job description

We are

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron's progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 16,850+, and has 60 offices in 20 countries within key global markets.

Our challenge

Client Capital Markets is seeking a highly skilled AI Engineer with deep expertise in Generative AI, neural networks, and transfer learning to support the development of an innovative, strategic data analytics platform. This role will lead the design, development, and implementation of advanced machine learning models and architectures, focusing on zero-shot, few-shot learning, and retrieval-augmented generation (RAG). The ideal candidate will be a thought leader in AI, capable of building agentic frameworks for capital markets use cases such as summarization, conversational AI, and information extraction, and embedding these tools into existing systems for key personas including Research, Banking, Sales, and Trading.

Additional Information*

The base salary for this position will vary based on geography and other factors.In accordance with law, the base salary for this role if filled within Toronto, ON is CAD $130k - CAD $145k/year & benefits (see below).

The Role

Responsibilities:

  • Develop Agentic Frameworks:Build advanced agentic frameworks tailored for capital markets applications, including summarization, conversational AI, and information extraction.
  • Embed Generative AI Tools:Integrate cutting-edge Generative AI frameworks into current Capital Markets tools, enhancing functionalities for research, banking, sales, and trading functions.
  • Innovate with ML Models:Lead the design and development of innovative machine learning architectures involving zero-shot/few-shot learning, retrieval-augmented generation (RAG), embeddings, and neural networks.
  • Collaborate & Guide:Function as a primary contributor on AI solutions while guiding team members on best practices, code reviews, and deployment strategies.
  • Experiment & Evaluate:Oversee end-to-end AI operations including experimentation, model evaluation, fine-tuning, deployment, and ongoing monitoring.
  • Research & Stay Updated:Keep abreast of advancements in deep learning, NLP, and AI methodologies to continuously improve the platform and solutions.

Requirements:

  • PhD or Master's degree in Computer Science, Machine Learning, Deep Learning, or equivalent experience.
  • 5+ years of hands-on experience building deep learning or machine learning models.
  • In-depth knowledge of machine learning, deep learning, and Generative AI techniques.
  • Proven ability to lead the development of Generative AI solutions, demonstrating expertise in design, implementation, and guiding team best practices.
  • Strong expertise in Natural Language Processing (NLP), information extraction, and related techniques.
  • Knowledge and understanding of embeddings, re-rankers, agentic frameworks, and related architectures.
  • Familiarity with inferencing, model fine-tuning, and various neural network architectures.
  • Experience with end-to-end AI operations including experimentation, evaluation, deployment, and ongoing model monitoring.
  • Strong knowledge of algorithms, data structures, and distributed computing environments.

Preferred, but not required:

  • Experience working on capital markets or financial industry applications.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and distributed computing frameworks.
  • Knowledge of AI lifecycle tools, MLOps practices, and automation pipelines.
  • Understanding of data governance, compliance, and security considerations related to AI in finance.

We offer:

  • A multinational organization with 60 offices in 20 countries and the possibility to work abroad.
  • 15 days (3 weeks) of paid annual leave plus an additional 10 days of personal leave(floating days and sick days).
  • A comprehensive insurance plan including medical, dental, vision, life insurance, and long-term disability.
  • Flexible hybrid policy.
  • RRSP with employer's contribution up to 4%.
  • A higher education certification policy.
  • On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses.
  • Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups.
  • Cutting edge projects at the world's leading tier-one banks, financial institutions and insurance firms.
  • A truly diverse, fun-loving and global work culture.

SYNECHRON'S DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative 'Same Difference' is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.


All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Candidate Application Notice

Apply