ML Infrastructure Engineer

Overview

Develop and maintain cloud ML infrastructure, CI/CD, and MLOps for research and production.

Key Responsibilities

• ci/cd
• release management
• model optimization
• cloud infrastructure
• ml ops
• automation

Tasks

-Build automation, CI/CD, and release management -Collaborate with software engineers for continuous improvement of end-to-end products from hardware tool to customer -Optimize ML models and classical algorithms to run efficiently and robustly -Develop and maintain cloud infrastructure to support research and production batch processing workloads -Introduce and promote ML Ops best practices to accelerate research using modern tooling such as DVC, WandB, etc.

Requirements

• aws
• python
• kubernetes
• linux
• devops
• bachelor's

What You Bring

-At least 3 years of experience developing and managing Cloud Infrastructure on AWS services (VPC, EC2, S3, RDS, etc.) -Knowledge of databases, SQL vs NoSQL, data pipelines, and data governance -Outstanding technical communication, analysis and problem-solving abilities -Familiarity with Linux and Shell Scripting -Having shipped at least one complex software product and supported it in production for real customers -At least 3 years of professional experience in a DevOps, ML Ops, or Software Engineering role -Bachelor's degree in Science, Engineering, or Mathematics -Background in ML, especially in Computer Vision for engineering applications -Educational background or work experience in ultrasound, signal processing, or similar -Experience managing hybrid or on-prem infrastructure -Proficiency in Python programming -Experience administering Kubernetes and related tools (e.g. Helm, Karpenter, Traefik) to support production workloads -Data Science skills (Prefect, NumPy, Pandas/Polars, SciPy, Matplotlib) -Knowledge of System Design, common architectural patterns and trade-offs. Particularly cloud-native development in the context of data-intensive, large-scale ML workloads

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About Darkvision

-Founded in 2013 in North Vancouver, the company pioneered industrial acoustic imaging to peer inside critical assets. -Secured Series A funding and earned a Deloitte Fast 50 award. -Acquired majority stake by Koch Industries to expand and fuel R&D. -Their HADES™ downhole tool captures sub-mm 3D ultrasound data from wells thousands of feet deep at high pressure. -Projects span oil & gas well integrity, pipeline inspection, public infrastructure, and aerospace component analysis. -The in-house stack blends sensor arrays, cloud-based AI, signal processing, and photorealistic defect visualizations. -Known for delivering insights in extreme environments.

Sector Specialisms

Security Clearance

-criminal background check required.