Design, prototype, and productize scalable machine learning solutions involving LLMs and real-world data. Build agentic systems, rapidly turn research prototypes into production services, and apply statistics and machine learning using Python tools. Collaborate with clients and engineering teams, analyze business and product outcomes, and deliver high-quality solutions in a fast-paced consulting environment.
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’re looking for Machine Learning Engineers who are passionate about building cutting-edge systems with LLMs and real-world data. In this role, you’ll work closely with clients and teammates to design, prototype, and productize scalable machine learning solutions.
You’ll be part of a collaborative, high-performing team that values clear thinking, pragmatic execution, and continuous learning. If you thrive in fast-paced environments, enjoy tackling open-ended problems, and care deeply about the quality and impact of your work, we’d love to connect.
Qualifications- Must have: Expertise in LLM engineering, including familiarity with popular LLM providers and their best practices. Experience building or working with agentic systems (e.g. tool use, memory, planning, multi-agent coordination) is a strong plus. Show us your LLM projects and detail your ownership and contributions.
- Strong ability to rapidly prototype cutting-edge tools and research ideas, with a track record of turning prototypes into production-ready services.
- Hands-on experience with statistics and machine learning. Comfortable working with the Python ML stack: Pandas, Numpy, scikit-learn, XGBoost, PyTorch, etc. Proficient with development tools such as Git, Docker, SQL, Bash, and FastAPI.
- Strong analytical mindset and business acumen; able to think critically about data and its impact on product or business outcomes.
- Bachelor's degree or higher (e.g., MS or PhD) in Computer Science or a related engineering field involving coding.
- Bonus: Familiarity with AWS or Azure, GitHub Actions, Spark, Neo4j Cypher, and graph databases.
We have competitive compensation.
We believe in accountability and NOT micro-management.
Similar Jobs
Big Data • Fintech • Mobile • Payments • Financial Services
Own and improve leadership development programs for aspiring, first-time, and newly hired people leaders. Design scalable learning journeys, workshops, peer communities, coaching, assessments, and practical leadership resources. Partner with People teams to connect development with hiring, onboarding, promotions, and growth. Use data, feedback, and emerging technologies to measure impact and continuously improve programs while managing vendors, communications, resources, and budgets.
Top Skills:
Ai Tools
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Prospect restaurants, manage the full sales cycle, conduct product demonstrations, develop customized solutions, negotiate with decision-makers, and close new accounts across the North York/North Toronto territory. The role requires maintaining sales activity in Salesforce, collaborating with internal teams to ensure successful delivery, analyzing competitors, and meeting sales goals. This is a field-based position requiring local residency or relocation and reliable transportation.
Top Skills:
CRMSalesforce
Cloud • Security • Software • Cybersecurity • Automation
Build and maintain fullstack features for GitLab’s post-purchase subscription lifecycle, including renewals, billing accounts, auto-renewal, overages, reconciliations, and subscription visibility. Partner with Product and Design, integrate billing and customer systems, write reliable tested code, support safe rollouts and monitoring, participate in code reviews and incident response, and reduce technical debt and architectural risk.
Top Skills:
Ruby On RailsSalesforceStripeVueZuora
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
