At a Glance
- Tasks: Design and manage AI infrastructure for large-scale workloads in cloud environments.
- Company: Join a cutting-edge AI infrastructure company focused on optimizing model serving.
- Benefits: Remote-first role with equity, competitive salary, and access to advanced tech resources.
- Other info: Collaborative environment with opportunities for experimentation and career growth.
- Why this job: Be a founding engineer and shape the future of AI infrastructure while making a real impact.
- Qualifications: 5+ years in AI infrastructure, proficiency in Python, and experience with Kubernetes.
The predicted salary is between 123750 - 151250 $ per year.
Employment type: Full-time position, 40 hours per week, with direct employment by the client.
Location: Remote-first role for candidates based in Canada.
Travel requirement: Candidates must be available to visit the client’s office in Montreal approximately two to three times per quarter.
About the client: An AI infrastructure company specializing in inference optimization for large-scale models. The platform enhances token throughput and reduces latency by optimizing hardware utilization and decoding processes within a customer's cloud environment. The technology focuses on improving the efficiency of model serving without requiring changes to existing infrastructure or code, ensuring data privacy while reducing operational costs for organizations deploying open-source models.
About the Role: As a founding Senior AI Infrastructure Engineer, you will report to the Chief Technology Officer to design and operate large-scale infrastructure for AI workloads on public cloud and on-premises environments. You will be an individual contributor with significant influence, combining software engineering with deep systems expertise to build secure and reliable platforms. Your work will focus on enabling efficient model serving at scale, ensuring the infrastructure can support a massive number of concurrent users while maintaining high service quality and performance.
What You'll Do:
- Design and manage multi-cloud and on-premises infrastructure for internal and external workloads.
- Orchestrate large-scale deployments using infrastructure-as-code and container orchestration to support high user concurrency.
- Benchmark AI inference workloads to identify performance bottlenecks and optimize hardware utilization.
- Develop and maintain comprehensive monitoring systems to ensure high service quality and reliability.
- Collaborate with customers to deploy and integrate optimization solutions within their existing infrastructure.
- Build and maintain an internal laboratory for infrastructure testing and experimentation.
What You Bring:
- 5+ years of experience in AI infrastructure or systems engineering.
- Proficiency in Python and experience building and operating scalable APIs.
- Extensive experience with Kubernetes, Helm, Ansible, and Terraform.
- Proven track record of shipping large language model (LLM) serving systems in production environments.
- Experience with distributed computing frameworks such as Ray, RayClusters, or KubeRay.
- Demonstrated experience with agentic workflows.
- Bachelor’s degree in Computer Science or a related technical field.
- Founding-engineer equity and direct ownership.
- Remote-friendly work environment. Visit the office 2-3x a quarter in Montreal.
- Access to extensive compute resources and specialized hardware for experimentation.
AI Infrastructure Engineer in Montréal employer: Mission.dev
Mission.dev is an exceptional employer that fosters a collaborative and supportive work culture, allowing Senior Full Stack Developers to take ownership of impactful projects within a high-growth risk intelligence platform. With flexible hybrid work options in Montreal and a strong emphasis on professional growth, employees benefit from engaging with cutting-edge AI technologies while being part of a tight-knit community of talented peers. The company prioritizes meaningful work-life balance, ensuring that team members can thrive both personally and professionally.
