Position: Lead Software Engineer (ML Systems & Deployment)
Location: Waterloo, Ontario (Hybrid, 3+ days weekly in office)

About Us

PolyML is a fast-growing AI and data analytics company building next-generation machine learning tools that unlock insight from complex, high-dimensional datasets. Our technology is proven in manufacturing, and we’re expanding into financial services and other data-intensive, highly regulated sectors. We work at the intersection of advanced mathematics, computer science, and real-world problem-solving—delivering tools that help organizations make better, faster, and more explainable decisions.

We’re a smart, energetic start-up team. We’re building something that matters and doing it right.

About the Role

PolyML is evolving from advanced ML innovation into scalable commercial products for manufacturing and regulated industries (including financial services). We’re hiring a hands-on engineering leader, reporting to the CEO, who can take PolyML’s core technology from prototype to production at massive compute scale (cloud or on-prem), while helping build the foundation of an engineering organization.

What You’ll Own (core outcomes)

• Production-scale deployments of our proprietary solution with cost/performance discipline and 24/7 reliability in compute-intensive environments.

• Propose and oversee end-to-end architecture and technology across ML, infrastructure, systems, and customer integrations (cloud and/or on-prem).

• Regulated-customer readiness (finance and similar): secure SDLC, auditability, and compliance alignment (e.g., SOC 2).

• Hiring judgment: knowing who to hire next (and when to outsource or simplify) as PolyML scales. 

Responsibilities

1. Scale the PolyML platform at serious compute levels

• Design and ship distributed compute pipelines and model execution at scale (cloud or customer-managed infrastructure).

• Benchmark, profile, and optimize throughput/latency, stability, and resource usage; own unit economics per run.

• Build production repeatability: testing strategy, CI/CD workflows, observability, incident response, and runbooks.

2. Guide architecture and technology decisions

• Guide architectural direction, with the Chief Scientist, across ML systems, platform, data flow, APIs, and integration patterns.

• Drive build-vs-buy decisions and define a scalable platform roadmap.

• Ensure interoperability with industry-standard tools and deployment patterns (e.g. Kubernetes, Terraform, AWS/GCP/Azure, Python).

3. Ship in highly regulated environments (e.g., finance)

• Lead security-by-design: access control, encryption, secrets management, audit logging, and environment isolation.

• Support compliance and governance expectations: reproducibility, artifact/version management, change control, and evidence collection.

• Partner with customer security/IT teams to pass reviews and deliver integrations.

4. Productize

• Turn one-off deployments into repeatable product capabilities: platform tooling, APIs, deployment templates, and documentation.

• Work with customers to translate requirements into measurable outcomes, trusted deployments, and ongoing operational success.

5. Build the team

• Establish priorities and execution cadence; mentor engineers and set a culture of technical rigor and accountability.

• Design the organization and hiring plan; decide when to hire vs. outsource vs. simplify with strong judgment.

Tech Stack/Playground

 At PolyML you’ll get a chance to play, learn and build with both open source and in-house developed tools and technologies, and as part of an experienced team:

• Languages: Darwin, Python
• Web Stack: Flask, Gunicorn, Nginx, FastAPI
• In-house ML tools: PolyML Fiins AI and Clara group of algorithms
• LLMs: ChatGPT, Claude, Gemini
• Infrastructure: AWS/Azure/GCP, Terraform, MongoDB, Airflow, Kubernetes
• Health/Monitoring: Prometheus, Grafana

You’ll collaborate directly with our Chief Scientist, Gaston Gonnet — co-founder of OpenText and a pioneer in computational mathematics whose work contributed to the development of systems like Maple. This is a rare opportunity to build alongside a world-class computer scientist and help translate deep mathematical innovation into production-grade systems.

What We’re Looking For (must-haves)

• 6+ years of software engineering experience, including 1–2+ years in a senior or lead capacity.

• Hands-on builder mindset: able to code, debug, and personally unblock critical engineering bottlenecks.

• Experience shipping into regulated environments with real security/compliance rigor (finance preferred).

• Early-stage mindset: balances speed with long-term scalability under constraints.

Nice-to-haves

• Experience with hybrid/on-prem enterprise deployments and restricted-network integration patterns.

• Familiarity with model governance and audit requirements in financial services.

• Domain experience in manufacturing or similarly regulated, data-intensive industries.

• Proven track record taking ML-driven products from concept → production → scale in compute-intensive settings.

• Strong architecture experience across ML systems, infrastructure, APIs, data pipelines, and integrations.

Why Join PolyML

Build next-generation sovereign Canadian AI/ML technology with real-world impact. At PolyML, you’ll have high ownership, influence core platform architecture, and work closely with experienced leadership to solve challenging technical problems at scale, across multiple industries. We offer competitive compensation, equity, hybrid work, and strong growth opportunities as we scale.

Compensation

PolyML offers a competitive total compensation package. In addition to base salary, the role includes group benefits, eligibility for performance-based bonus and equity participation. Final compensation will be determined based on qualifications, experience, and overall fit for the role.

How to Apply

Here is a link to apply: PolyML Jobs_Lead Software Engineer