Senior Software Developer, ML Ops

Accountabilities:
As a Senior Software Developer focused on ML Operations, you will help build and evolve a self-service machine learning platform that enables teams to develop, deploy, and operate ML and AI solutions efficiently. You will work closely with engineers, data scientists, and infrastructure teams to design scalable systems, define technical direction, and deliver reliable platform capabilities. Design, build, and maintain framework-agnostic services supporting machine learning model training, inference, evaluation, and monitoring. Develop scalable ML infrastructure that enables data scientists to move models from experimentation into production reliably. Establish technical roadmaps and architecture decisions for machine learning platform capabilities. Build high-performance systems and contribute to ML infrastructure running on technologies such as Kubernetes and Ray. Collaborate with product, engineering, infrastructure, and data teams to solve complex technical challenges. Take ownership of projects from concept through implementation, deployment, and long-term maintenance. Improve platform reliability through strong engineering practices, observability, performance optimization, and operational excellence. Contribute to the evolution of ML tooling, workflows, and internal developer experiences. Support the adoption of modern AI and machine learning technologies across the organization. Requirements: The ideal candidate is an experienced software engineer with a strong background in machine learning infrastructure, scalable systems, and production-grade software development. You should be comfortable owning complex technical projects, collaborating across teams, and building systems designed for long-term impact. 5+ years of experience developing and implementing production-ready software services. 5+ years of software engineering experience focused on ML infrastructure, ML tooling, or machine learning engineering. 3+ years of professional experience with Python. Proven experience designing and building highly scalable, performant, and observable systems. Strong understanding of software architecture, distributed systems, and production engineering practices. Experience owning projects end-to-end and maintaining complex systems over time. Ability to work independently, make technical decisions, and define solutions for ambiguous challenges. Strong collaboration and communication skills with both technical and non-technical stakeholders. Experience with machine learning ecosystems and tools such as PyTorch, Transformers, Ray, feature stores, vector databases, Triton, CUDA, DVC, or vLLM is a plus. Experience with Kubernetes, FastAPI, MLflow, cloud-based ML infrastructure, or data platforms is an advantage. Benefits: Competitive base salary range of approximately CA$152,900 – CA$189,000 depending on experience, skills, and location. Equity compensation opportunities as part of total compensation. Comprehensive health benefits and life insurance coverage. Employer-matched group savings program. 20 vacation days, wellness days, and flexible sick and mental health days. Ability to work outside Canada for up to 90 days per year. Remote-friendly work environment with opportunities for collaboration across North America. Access to employee resource groups supporting inclusion and community. Opportunity to work with talented teams building innovative technology products. Supportive culture focused on curiosity, learning, and continuous improvement.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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