Design, prototype, and productionize machine learning models for real-world problems using structured and unstructured data. Implement scalable ML systems, apply statistical methods, rapidly prototype research papers, and collaborate with engineering teams to deliver data-driven solutions.
Company Description
You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities.
Job DescriptionWe are looking for Data Scientists who are passionate about solving real world problems. You enjoy working with both structured and/or unstructured data and are motivated to productize scalable machine learning models. Critical thinking and problem-solving skills are essential for this role.
Qualifications- BS (or higher, e.g., MS, or PhD) in Computer Science or related engineering field involving coding
- Experienced implementing and scaling machine learning models in production environments
- Strong understanding of machine learning theory
- Hands on experience with Statistics
- Capable of quickly implementing prototypes of cutting-edge research papers
- Proficient in Python (i.e. Pandas, Numpy, scikit-learn, etc), R, TensorFlow, amongst other data science related tools and libraries
- Analytical mind and strong business acumen
If you're passionate about data science and is hungry to learn, please apply!
Additional Information- We have competitive compensation.
- Work on cool projects based on your interests and skills. We believe in accountability and NOT micro-management.
Similar Jobs
Agency • Information Technology • Professional Services • Software
Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.
Top Skills:
Amazon BedrockGoogle Model GardenHugging FaceKerasLangchainNvidia NimOpenai ApiPythonPyTorchTensorFlow
Artificial Intelligence • Information Technology • Software
As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.
Top Skills:
Data ScienceMachine Learning
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Senior Principal Platform Architect advises customers on ServiceNow platform architecture, instance strategy, integrations, technical governance, and long-term health. Works across sales and delivery, mentors teams, supports presales, leads large program architecture, and aligns platform to enterprise strategy and best practices.
Top Skills:
AICloudIt4ItServicenowTogaf
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
