Design, prototype, and productize scalable machine learning solutions using LLMs. Collaborate with clients and teammates to build production-ready systems, rapidly iterate prototypes, apply statistics and ML, and implement tooling and infrastructure for deployment and model-driven features.
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
Artificial Intelligence • Productivity • Software • Automation
Own enterprise pipeline generation through signal-led, multi-channel demand gen campaigns. Partner with Enterprise AEs to target accounts, design ABM plays, run frequent experiments, craft outbound messaging, and build AI-driven workflows that automate engagement and accelerate deals from first touch to closed-won.
Top Skills:
6SenseAgentsAi-Powered WorkflowsApolloClayDemandbaseGong EngageHubspotLlmsZoominfo
Artificial Intelligence • Productivity • Software • Automation
Run and maintain Zapier's incident program operations: manage incident tooling and on-call systems, build AI-powered automations and dashboards, maintain runbooks and enablement, operate reporting and observability, coordinate cross-functional stakeholders, and drive continuous improvement to keep incident response reliable and scalable.
Top Skills:
APIsClaudeCodaCopilotCursorDatabricksDatadogGitlabGoogle WorkspaceGrafanaGraylogIncident.IoJIRALookerOpensearchPagerdutyPrometheusSlackSlack ApisSQLZapier AiZendesk
Cybersecurity
Lead product marketing for Enterprise Password Manager: own messaging, positioning, competitive strategy, launches, and field enablement. Translate technical concepts (passkeys, machine credentials, zero-knowledge) into narratives for IT, security engineers, and CISOs. Build competitive intelligence, inform product strategy, and produce sales tools that drive displacement of incumbents.
Top Skills:
Ai AgentsAi/MlApi KeysCertificatesCredentials SecurityDirectory ServicesEnterprise VaultingIamIdentity SecurityMachine SecretsMdmPasskeysPassword ManagementSsoZero-Knowledge Architecture
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
