// About Providius
Providius has been at the forefront of innovation in the Media & Entertainment industry for over a decade, delivering solutions to complex challenges in IP media and IT infrastructure within mission-critical environments.
Headquartered in Hamilton, Ontario, Canada, we are a privately held company focused on building practical, reliable systems that solve real-world problems.
// What We’re Looking For
We’re looking for a junior machine learning engineer to join our team and grow into a strong, hands-on ML engineer.
This is a role for someone early in their career who is eager to learn, comfortable getting their hands dirty with real data, and motivated to build a solid foundation in applied machine learning.
You will work under the direction of senior ML and engineering staff, contributing to real models and pipelines while developing your skills and judgment over time.
// Position Overview
Working closely with senior engineers, you will:
- implement, train, and evaluate models under guidance
- prepare and explore real-world data
- help build and maintain data pipelines
- support experiments and document results
- This role is hands-on and engineering-focused.
You will be writing code, working with messy, real-world data, and learning how machine learning systems are built and run in practice.
Over time, as you build experience, you will take on more ownership and tackle increasingly open-ended problems.
// Duties and Responsibilities
- Implement and train models under the guidance of senior engineers
- Prepare, clean, and explore datasets, including feature engineering
- Run experiments, record results, and help interpret findings
- Build and maintain parts of the data pipeline and supporting tooling
- Help integrate models into larger systems alongside the team
- Write clear, testable, and maintainable code
- Ask good questions, seek feedback, and learn from code review
Requirements
// Required Skills / Experience
- 0–2 years of experience in machine learning, or strong academic or project experience
- Programming ability in Python
- Solid grounding in machine learning fundamentals
- Willingness to work with real-world, imperfect data
- Strong problem-solving ability and a desire to learn
- Ability to take direction and incorporate feedback
- Clear communication in a team environment
// What this Role Requires
- Eagerness to learn and grow quickly
- Comfort working with guidance and asking for help when needed
- Pragmatism and a willingness to see tasks through
- Attention to detail and care in the work
- Ownership of your own learning and contributions
// Nice to haves
- Coursework, internships, or projects involving anomaly detection, time-series, or behavioral modeling
- Exposure to streaming or telemetry data
- Familiarity with common ML libraries and tooling
- Experience contributing to a shared codebase
// Why join Providius
- Own a product area with real autonomy and direct impact
- Work on products that operate in real-time, high-stakes environments
- Small team with high ownership and a direct line to leadership
Benefits
Benefits
- Dental care
- Extended health care
- On-site parking
- Paid time off
- Vision care
Providius delivers advanced observability for mission-critical, time-sensitive networks. Our mission is to help organizations in live broadcasting, media & entertainment, and enterprise AV achieve flawless performance across their most demanding workflows. Our expertise is built on three core pillars: Network Visibility – providing instant, real-time insights into multicast routing, synchronization accuracy, and media service health. Traffic Intelligence – enabling deep packet inspection and analytics that uncover patterns, performance bottlenecks, and emerging risks. Operational Defense – equipping teams with the intelligence to detect issues early, resolve them quickly, and safeguard uptime across hybrid and cloud-based environments. With these competencies, Providius empowers industry leaders to optimize their networks, reduce downtime, and innovate with confidence. 👉 Follow us for insights on next-gen observability, media performance, and the future of network intelligence.
Key team members

Bibiana C.

Albert H.

Kiri O'Connor

Spencer Lee
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