Senior/Staff Applied AI Engineer in Toronto

About Tali Clinicians are drowning in paperwork. We're giving them their time back. Tali AI is one of the fastest-growing startups in Canada, on a mission to make healthcare more accessible with AI. We're building the clinical operating system: an ambient AI scribe, a billing agent, scheduling, clinical decision support, and more on one platform that allows clinicians to look at their patients instead of their keyboards. Thousands of clinicians across Canada and the US already use Tali, across dozens of specialties, integrated deeply with the fragmented landscape of North American health-record systems. The traction is real: multiple commercial product lines, 15M+ patient visits documented on the platform, 70+ years worth of time saved for clinicians in under three years. We move fast in a market that rewards speed, in a domain where breaking clinician trust is not recoverable.

The role You own AI systems end to end. The models, the prompts, the retrieval, the data, the evals, and the debugging when a clinician says the output was wrong. The ambient scribe listens to a visit and writes the clinical note. A recommender suggests the billing codes a clinician can claim for that visit. Medical search answers a clinical question from real sources. And a growing number of agents run inside the company and in the product. You work across all of it. Evaluation carries the same weight here as any product feature. It is what makes the rest of it trustworthy.

What you'll work on:

• Build the evaluation pipelines that decide whether the AI is good enough to ship. Automated judges, regression suites, human review, and the datasets underneath them.
• Diagnose failure modes and fix them. The lever might be the prompt, the retrieval, the routing, the model, the audio capture, or a fine-tune.
• Build production agents. Tool use, orchestration, guardrails, and recovery when a step fails.
• Debug one visit end to end, then find every case like it. You trace a single interaction from audio to delivered note and work out what broke.
• Decide which model serves which request, and change that safely.
• Own these systems in production. You get the alert when quality slips, you find the cause, and you decide what ships to fix it.
• Turn a vague clinical complaint into a problem statement, a metric, and a plan the team can act on.
• Set the bar for how Tali does applied AI. Your evals become the evals everyone else runs.

What we're looking for:

• 5+ years in production ML, applied AI, or research engineering.
• Deep evaluation experience.
• Agentic systems.
• Strong systems engineering.
• Data-centric instincts.
• Python, plus modern ML tooling.
• Candour.
• You raise the people around you.

This is a senior or staff role depending on your track record. The levelling conversation happens at the end of the interview process.

Bonus points:

• Speech recognition or real-time audio.
• A regulated domain, such as healthcare or finance.
• Clinical experience of any kind.

What you'll work with:

• Python and TypeScript.
• GCP and Cloud Run.
• Vertex AI, Claude, and other frontier LLM and ASR providers.

Is this you? You're passionate about the application of technology in our users' lives. You default to the simplest way to deliver value to users. And you know when the simple answer stops being good enough. Then you make the technical case and the business case for the harder one, and you ship it. Both halves matter.

If you don't have ground truth data, you mine production for weak labels and generate what you can. When you hit a real ceiling, you cost out annotators, write the case for the investment, build the quality checks, and run the program.

If audio quality is a deep issue for some users, you squeeze what you can from the signal, and you know when and how to make the case for shipping microphones to users. Then you drive the execution.

You build our eval tooling even when it's unglamorous. You debug traces, you talk to clinicians about what went wrong, and you know when to invest in better infrastructure to slash toil.

What success looks like:

• 3 months: You own a real AI problem and you're driving it with minimal oversight.
• 6 months: Evaluation and rollout are a system you helped build.
• 1 year: Tali's AI systems have taken a step change in capability.

Working at Tali Benefits:

• Flexible work hours
• Comprehensive health and wellness coverage from day one, including unmetered wellness days
• Competitive PTO, including winter shutdown Dec 25 - Jan 1, birthdays and Taliversaries, and 'extra long' long weekends
• $2000 annually in "Knowledge Dollars" to learn, grow, and level up
• Quarterly socials & company outings that bring our team together beyond the day-to-day

Our Core Values:

• Bold: we embrace ambitious goals, make courageous decisions, and take calculated risks to drive impactful innovation and growth
• Resourceful: we're self-directed problem solvers; navigating obstacles, learning and acquiring new skills and making sound judgement calls.
• Candid: Being honest, transparent, and open in all interactions, fostering a culture of trust and authenticity
• Caring: Actively supporting and empathizing with our people - customers, patients, and colleagues to help them thrive and achieve their goals

Tali is one of Linkedin's Top Startups of 2025. Tali is part of the renowned Digital Supercluster Project.