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Tensorflow Jobs in Ontario (NOW HIRING)

Proficiency with frameworks such as PyTorch, TensorFlow and scikit-learn * Practical knowledge of CNNs and modern computer vision architectures * The ability to adapt open-source models to specific ...

AI Applied Senior Engineering Lead

Mississauga, ON ยท On-site

CA$145K - CA$217K/yr

Handson experience with LLMs, RAG, prompt engineering, MCPs, and agent frameworks (e.g., Google ADK) Practical experience with ML frameworks and libraries (TensorFlow, PyTorch, Scikitlearn, NumPy ...

Data Scientist

Cambridge, ON ยท On-site

CA$600/day

... TensorFlow, PyTorch, Scikit-learn) โ€ข Experience with databases (SQL, Influx) โ€ข Knowledge of data warehousing and ETL processes โ€ข Familiarity with tools like Hadoop, Spark, or Kafka โ€ข ...

Apps Dev Tech Lead Analyst

Mississauga, ON ยท On-site

CA$120K - CA$170K/yr

... or TensorFlow, including finetuning and embeddings Strong understanding of prompt engineering, workflow design, and GenAI optimization (latency, cost, accuracy) Experience deploying GenAI systems ...

Strong Python proficiency across pandas, scikit-learn, PyTorch, and TensorFlow * Strong SQL and large-scale data manipulation experience * Solid grounding in statistical modeling, machine learning ...

Experience building and training machine learning models (regression, classification, clustering) using frameworks like Scikit-learn, TensorFlow, or PyTorch What's In It For You? We thrive on the ...

Showing results 41-60

Tensorflow information

See Ontario salary details

$30

$63

$96

How much do tensorflow jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for tensorflow in Ontario is $63.56, according to ZipRecruiter salary data. Most workers in this role earn between $48.08 and $86.78 per hour, depending on experience, location, and employer.

What is a TensorFlow?

A TensorFlow job typically involves developing, training, and deploying machine learning models using TensorFlow, an open-source AI framework. Responsibilities may include data preprocessing, building neural networks, optimizing model performance, and integrating models into applications. These roles are common in industries like healthcare, finance, and autonomous systems, requiring skills in Python, deep learning, and TensorFlow's ecosystem.

What does a TensorFlow developer do?

As a TensorFlow Developer, your day-to-day responsibilities often include designing and building machine learning models, preprocessing data, conducting model training and evaluation, and deploying models to production environments. You may also work closely with data scientists, software engineers, and product managers to identify use cases, define project requirements, and optimize system performance. Regular tasks can involve using tools for data visualization, debugging, and performance tuning, as well as keeping up with the latest advancements in machine learning techniques. Collaboration and clear communication are key, as projects often require input and feedback from multiple technical and non-technical stakeholders.

What are the key skills and qualifications needed to thrive in the TensorFlow position?

To thrive in a TensorFlow Developer role, you need strong programming skills in Python, deep learning knowledge, and hands-on experience with TensorFlow and related AI frameworks. Familiarity with tools like Keras, TensorBoard, and cloud platforms such as Google Cloud is often required, and TensorFlow Developer certifications are highly valued. Excellent problem-solving, communication, and teamwork skills help professionals navigate complex projects and collaborate effectively with cross-functional teams. These skills and qualities ensure the successful design, deployment, and optimization of machine learning models in real-world applications.

What jobs use TensorFlow?

Jobs that use TensorFlow include machine learning engineer, data scientist, AI researcher, and deep learning engineer. These roles involve developing and deploying neural network models, often requiring programming skills in Python and knowledge of machine learning frameworks. TensorFlow is widely used in industries such as technology, healthcare, finance, and automotive for tasks like image recognition, natural language processing, and predictive analytics.

What are popular job titles related to Tensorflow jobs in Ontario?

For Tensorflow jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Tensorflow jobs in Ontario look for?

The top searched job categories for Tensorflow jobs in Ontario are:

Infographic showing various Tensorflow job openings in Ontario as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $132,215 per year, or $63.6 per hour.

Machine Learning Engineer

Toronto, ON โ€ข On-site

Full-time

Medical, Dental

Posted 14 days ago


Job description

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our products to the next level in terms of visual intelligence. 

Our Company 

Invision AI is building a universal AI platform for computer vision applications. Powered by a unique multi-camera stack that generates high-integrity 3D digital twins of dynamic environments, our technology powers disruptive, market-leading solutions in intelligent infrastructure and global Transportation. 

The Role

As a Machine Learning Engineer, you will work across the full machine learning lifecycle, from data collection and labeling strategy through training, evaluation, deployment, monitoring, and ongoing improvement.

Your focus will be developing and maintaining computer vision models used in real-world products. While the work may involve researching and implementing new approaches, this is primarily an applied engineering position. We are looking for someone with a track record of building, shipping, and maintaining production ML systems.

The position includes working on projects that expand and strengthen our capabilities in object detection, image classification, geospatial tracking, and sensor fusion, with models deployed to resource-constrained edge devices.

Working within a collaborative team, you will build accurate, efficient, and principled solutions. As a key contributor to the company's next stage of growth, you will help advance our products, solve challenging customer problems, and shape our ML engineering practices in a fast-moving environment.

Location

This is a full-time, hybrid position based in Toronto. You will work from our downtown Toronto office three days per week.

What You'll Do

  • Recommend, develop, evaluate, and deploy ML models across our product lines
  • Build and improve data-labeling, training, and evaluation pipelines
  • Establish evaluation methods that connect model performance to product and business outcomes
  • Prototype new product capabilities using appropriate technologies
  • Optimize models for latency, memory usage, power consumption, and accuracy on edge devices
  • Diagnose and resolve issues affecting deployed models
  • Monitor production performance and identify model drift, data-quality problems, and retraining needs
  • Write maintainable, well-tested code and clear technical documentation
  • Participate in design reviews, code reviews, and technical planning
  • Share ML knowledge and collaborate with software, product, and other engineering teams

Requirements

Must Have

  • A track record of developing and deploying production computer vision models
  • Strong Python software development skills
  • Proficiency with frameworks such as PyTorch, TensorFlow and scikit-learn
  • Practical knowledge of CNNs and modern computer vision architectures
  • The ability to adapt open-source models to specific products and use cases
  • Hands-on work optimizing models for resource-constrained or edge environments
  • Knowledge of experiment tracking, dataset versioning, and ML observability
  • Skill in designing evaluation metrics that reflect product and business requirements
  • An understanding of model monitoring and production troubleshooting
  • Working knowledge of embedded systems and their constraints
  • Sound software engineering practices, including automated testing, code review, version control, and continuous integration
  • Strong written and verbal communication skills
  • Must be legally entitled to work in Canada

Bonus Skills

  • Familiarity with Docker or other container technologies
  • C++ development skills
  • GPU programming or performance-optimization knowledge
  • Knowledge of model compression techniques, including quantization, pruning, and knowledge distillation
  • Familiarity with edge inference tools such as ONNX Runtime, TensorRT
  • Familiarity with traditional, non-ML image-processing techniques
  • A background in sensor fusion or geospatial data

Benefits

  • A Mission that Matters: The opportunity to work on projects that make the world safer and greener 
  • Excellence: A culture of very high technical standards where quality engineering is valued over quick hacks 
  • Technical Challenge: A wide variety of technology and tasks, including web development, distributed and edge computing, ML, real-time processing, and computer vision 
  • Growth Environment: Join an international team where your voice is heard and your impact is visible 
  • Compensation and benefits: Competitive salary package including equity, allowing you to share in the success you help build. Benefits: RRSP Plan, Health and Dental and 4 weeks holiday.