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Toronto Startup Design Jobs (NOW HIRING)

Adaptive ML

Customer Success Engineer

New York, NY · On-site

ABOUT THE TEAM Adaptive ML is a frontier AI startup building a Reinforcement Learning Operations ... Design and deliver compelling technical demos and proof-of-concept implementations that map ...

Lithium Americas

Mechanical Engineer

Winnemucca, NV · On-site

The Company's shares are listed on the Toronto Stock Exchange (TSX) and New York Stock Exchange ... Experience with CAD and updating drawings with use of Hexagon SmartPlant P&ID preferred

Beacon Software

Software Engineer

New York, NY · On-site

We are growing our team in Toronto, San Francisco, and New York. Apply below. Software Engineer We ... You'll collaborate closely with product, design, and leadership teams within our portfolio ...

Beacon Software

Software Engineer

San Francisco, CA · On-site

We are growing our team in Toronto, San Francisco, and New York. Apply below. Software Engineer We ... You'll collaborate closely with product, design, and leadership teams within our portfolio ...

Pear

Founding Applied AI Lead

New York, NY · On-site

$110K - $175K/yr

It is the written and structured system design layer around our AI: precise agent instructions ... startup environment where processes are still being built. * Based near New York City or Toronto ...

Giga AI Inc

Founding Engineering Manager

New York, NY · On-site

$210K - $400K/yr

Voice AI startup Giga raises $61M Series A * DoorDash and Giga Partnership Giga builds AI agents ... What You'll Work On You'll hire an elite team and lead the Toronto site! You will drive technical ...

Sokin

Campaign Lead

New York, NY · On-site

... design offers that drive conversion. Working closely with Sales and regional marketers globally ... Locations New York, Toronto Remote status Hybrid Yearly salary 120,000 - 140,000

Highbeam, Inc

AI Implementation Associate

New York, NY · On-site

$130K - $180K/yr

Break down messy customer situations, reason through them, and design workflows that scale beyond a ... Our Toronto office is downtown near St. Andrew Station. * Generous PTO * Comprehensive health ...

Highbeam, Inc

AI Implementation Associate

Manhattan, NY · On-site

Break down messy customer situations, reason through them, and design workflows that scale beyond a ... Our Toronto office is downtown near St. Andrew Station. * Generous PTO * Comprehensive health ...

Rillet

Business Operations Associate

New York, NY · On-site

They internalize a mission, design a strategy, and bring back results that are better, faster, and ... startup. We're looking for teammates who value in-person collaboration and are within commutable ...

Rillet

Senior Software Engineer

San Francisco, CA · On-site

$144K - $190K/yr

They internalize a mission, design a strategy, and bring back results that are better, faster, and ... Prior experience working in a high growth startup * Experience with modern web frameworks and ...

Adaptive ML

RevOps Manager

Boston, NY · On-site

$107K - $110K/yr

RevOps Manager About the team Adaptive ML is a frontier AI startup building a Reinforcement ... Design and maintain dashboards, reports, and analytics that give sales leadership clear visibility ...

Rillet

Business Operations Associate

Manhattan, NY · On-site

They internalize a mission, design a strategy, and bring back results that are better, faster, and ... startup. We're looking for teammates who value in-person collaboration and are within commutable ...

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As of Jun 5, 2026, the average hourly pay for toronto startup design in the United States is $50.69, according to ZipRecruiter salary data. Most workers in this role earn between $39.18 and $61.78 per hour, depending on experience, location, and employer.
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Customer Success Engineer

Adaptive ML

New York, NY • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago

Job description

ABOUT THE TEAM
Adaptive ML is a frontier AI startup building a Reinforcement Learning Operations (RLOps) platform that enables enterprises to specialise and deploy LLMs into production with measurable impact. We provide the core infrastructure to tune, evaluate, and serve specialised models at scale - pioneering task-specific LLM development and running production-ready workflows that serve millions of requests while optimising for both cost and performance across distributed systems.
Our tightly-knit team was previously involved in the creation of state-of-the-art open-access large language models. We raised a $20M seed led by Index Ventures and ICONIQ in early 2024, and we're already live in production with customers including Manulife, AT&T, and Deloitte, across travel and financial services - with much more to be announced soon.
ABOUT THE ROLE
We're looking for a Customer Success Engineer to be the technical backbone of our customer relationships - from the first technical conversation through to long-term production success. Based in New York City, you'll operate across the full customer lifecycle: deep enough technically to win enterprise deals in pre-sales, and commercially minded enough to grow and retain the accounts you help land.
The best people in this kind of role run rigorous discovery, design architectures that solve real business problems, and earn the kind of trust that makes customers come back for every major decision. You won't just hand off after a deal closes. You'll stay embedded: owning deployment success, driving adoption, and becoming the trusted technical advisor your customers rely on in production.
The role suits someone who has operated at the intersection of Solutions Engineering and Customer Success before, or a strong Solutions Architect ready to own the full arc of customer value.
WHAT YOU'LL DO
Pre-Sales
  • Lead customer-facing workload planning - understanding model usage patterns, expected throughput, and infrastructure constraints to scope solutions accurately from day one.
  • Own solution architecture in the sales cycle: infra selection, TCO calculation, and performance benchmarking tailored to each prospect's environment and LLM workloads.
  • Design and deliver compelling technical demos and proof-of-concept implementations that map Adaptive ML's capabilities directly to customer pain points and existing infrastructure.
  • Respond to technical evaluations, RFPs, and security reviews; go deep with engineering and data science counterparts on architecture decisions and integration requirements.
  • Partner with Account Executives to shape deal strategy, accelerate procurement timelines, and remove technical blockers standing between a prospect and a signed contract.

Post-Sales
  • Own technical onboarding end-to-end - designing integration architectures, working directly with customer engineering teams, and driving time-to-first-value.
  • Support and continuously optimise live deployments: cost optimisation, performance tuning, and workload expansion across multi-geo and multi-team customer environments.
  • Be the escalation point for production issues - investigating and debugging problems spanning k8s deployments, Helm configurations, model serving infrastructure, and distributed systems.
  • Drive workload expansion proactively: surface new use cases, additional model workflows, and untapped product capabilities that create value across your account portfolio.
  • Conduct regular technical and business reviews with customer stakeholders, translating infrastructure metrics into business impact and building the case for renewal and growth.

Internal & Cross-Functional
  • Build reusable technical assets - reference architectures, integration guides, runbooks, and demo environments - that scale knowledge and accelerate future deals.
  • Act as the voice of the customer internally: channel field insights directly to Product and Engineering to shape the roadmap and prioritisation.
  • Contribute to infra sizing and workload planning discussions alongside Solutions and DevOps colleagues, with particular focus on the NA region (NYC/Toronto coverage).

YOUR (IDEAL) BACKGROUND
We encourage candidates to apply even if their experience doesn't match every point below.
Experience
  • 3-6+ years in a customer-facing technical role - Solutions Engineer, Solutions Architect, Customer Success Engineer, or Technical Account Manager - ideally in B2B SaaS, cloud, or infrastructure.
  • Proven ability to operate across both pre-sales and post-sales: you're as comfortable running a technical architecture review for a VP of Engineering as you are debugging a production incident with a DevOps team.
  • Track record with enterprise customers in complex technical environments - multi-stakeholder deals, long sales cycles, and durable post-sale technical relationships.
  • Demonstrable outcomes: successful deployments, adoption growth, expansion revenue, or strong renewal rates. You own the result, not just the activity.
  • Experience at a fast-growth or early-stage company is a strong plus - you know what it takes to build things from scratch under pressure.

Technical Skills
  • Strong infrastructure instincts: you can confidently size GPU and storage requirements, reason about TCO trade-offs, and produce architecture diagrams that a CTO would trust.
  • Skilled at architecture design - you can whiteboard a solution live, document it clearly, and defend design decisions with technical rigour.
  • Hands-on with Kubernetes (k8s): you can investigate deployment issues, read and edit Helm charts, and navigate distributed systems problems in production environments.
  • Python proficiency - enough to build proof-of-concepts, write integration scripts, and benchmark model performance against real customer workloads.
  • Familiarity with ML infrastructure concepts: model serving, LLM fine-tuning, inference optimisation, and the operational realities of running models at scale is a strong plus.
  • Comfortable working alongside DevOps and SRE teams; you understand their tooling, constraints, and language.

The Right Profile
  • You ask sharp discovery questions, design clean solutions, and earn trust through genuine expertise rather than commercial polish.
  • Strong communicator across audiences - you can simplify a complex distributed architecture for a CFO and go deep on inference latency with a staff ML engineer in the same afternoon.
  • You own outcomes. In fast-moving, ambiguous environments you figure out what matters and act - you don't wait for a brief.
  • Genuine curiosity about generative AI and LLMs. The technology you're selling and supporting moves fast; intellectual interest in the space makes a real difference.
  • Based in New York City, comfortable in the NA time zone for customer-facing coverage.

BENEFITS
  • Comprehensive medical (health, dental, and vision) insurance.
  • 401(k) plan with 4% matching.
  • Unlimited PTO - we strongly encourage at least 5 weeks each year.
  • Mental health, wellness, and personal development stipends.
  • Visa sponsorship available if required.

Apply