Engineering Manager, Machine Learning Platform and Infrastructure Full Time

Your Job

DarkVision is seeking a hands-on Engineering Manager to lead our ML Platform and Infrastructure team. You will be responsible for the strategic planning, architecture, and reliability of the compute and data systems that power our advanced acoustic imaging technology.

DarkVision’s ultrasound imaging system creates the largest ultrasound datasets in the world, with single scans approaching petabytes in size. Detecting millimeter-sized defects across hundreds of kilometers of assets requires a platform that is robust, scalable, and efficient. You will lead the team that builds the engine for our AI, bridging the gap between hardware, cloud infrastructure, and statistical data validation.

This role is on-site at our North Vancouver, BC HQ, where employees enjoy a wide array of amenities including a fully equipped gym, squash court, steam room, climbing wall, and more!

Our Team

You will lead the ML Platform and Infrastructure team, a specialized unit within the broader Imaging & AI group. Your direct reports include Cloud Infrastructure Engineers, MLOps Engineers, and Data Scientists. You will work closely with the Applied ML team to ensure their algorithms have the compute resources and clean data required to move from experimentation to production.

What You Will Do

• Team Leadership & Strategy: Manage, mentor, and grow a diverse team of engineers and scientists. You will set the technical roadmap for our ML infrastructure, balancing immediate production needs with long-term scalability goals.
• Platform Architecture: Architect the cloud-based (AWS) and on-premise systems required for massive-scale batch processing. You will make high-level decisions regarding compute orchestration (Kubernetes), storage, and cost optimization.
• Operational Excellence: Oversee the development of CI/CD pipelines and MLOps practices. You will ensure our training and inference workflows are reproducible, monitored, and secure.
• Data Integrity & Validation: Supervise the Data Science function to ensure the statistical validity of our models. You will champion data integrity audits and experimental design frameworks that prove the reliability of our technology to clients.
• Cross-Functional Collaboration: Serve as the bridge between Software Engineering, Applied ML, and Data Analysis teams, ensuring that infrastructure decisions support the company’s product delivery goals.

Who You Are (Basic Qualifications)

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in software, infrastructure, or data engineering.
• 2+ years of experience leading or managing technical teams.
• Deep technical understanding of cloud infrastructure (AWS) and container orchestration (Kubernetes).
• Proficiency in Python and familiarity with the machine learning lifecycle.

What Will Put You Ahead

• Experience managing multidisciplinary teams (combining DevOps/Infra with Data Science).
• Experience managing medium to large teams (10 or more direct reports).
• Hands-on experience with workflow orchestration tools (e.g., Prefect, Dagster, Airflow).
• Experience processing petabyte-scale datasets.
• Familiarity with distributed computing frameworks (e.g., Ray, Dask).
• Experience dealing with data governance, security, and compliance in an industrial context.
• Pragmatic leadership style with the ability to discern when to build custom solutions versus utilizing managed services.
• Exceptional communication skills to articulate complex infrastructure constraints to non-technical stakeholders.

General Salary Range

For this role, we anticipate paying $150,000 to ~$200,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.

At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate’s knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.

Who We Are

DarkVision Technologies Inc. is a Canada-based tech company disrupting the industrial imaging market since 2013. We have created the world’s most advanced acoustic-based imaging platform. We are packaging it into multiple new product lines, revolutionizing how our clients quantify and visualize the integrity of their critical assets.

Backed by Koch Inc., one of the world’s largest privately held companies, DarkVision’s team of Mechanical, Skunkworks, Electrical, Software, and Machine Learning Engineers is rapidly expanding to meet the demand for the company’s current and upcoming products.

We allow employees to work on cutting-edge technologies that blend science with real-world applications. We invite you to join our team for the exciting journey ahead as we become the global leader in industrial imaging.

At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company.

Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results.

How to Apply

If you have the above qualifications, we would like to hear from you. We thank all applicants in advance, but please be advised that only those selected for an interview will be contacted.

We are an equal opportunity employer. If you require accommodation or assistance at any time during the application or selection processes, please submit a request by following the directions located in the FAQ section at the bottom of the kochcareers.com webpage.

Successful candidates will be required to complete a criminal background check.

Keywords: Engineering Manager, MLOps, Cloud Infrastructure, AWS, Kubernetes, Data Science Management, Platform Engineering, Python, Distributed Systems, Team Leadership.

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