Deep learning Jobs in Hamilton, ON

Skills and Experience you will bring: 5+ years building and operating production backend or distributed systems (Python preferred; strong candidates from Java, Go, or similar backend languages also considered) Deep, hands-on experience with a major cloud provider’s serverless and compute services (e.g., AWS Lambda, Step Functions, DynamoDB, EventBridge, EC2, or equivalent services on GCP/Azure) Infrastructure-as-code fluency (CloudFormation, Terraform, or similar) and comfort owning deployments end-to-end Solid understanding of event-driven architecture, distributed-systems failure modes, and idempotent/retry-safe design Strong testing discipline and experience writing clean, maintainable, well-covered code Track record of operating what you build - on-call, observability/monitoring, and incident response Strong communication skills and comfort collaborating across multiple repos/services with other engineers Additional skills and experience that will be useful: Video, streaming, or media experience - HLS, SRT, RTMP, transcoding, or live encoders GPU-accelerated encoding (NVENC) or media-server/encoder API integration (e.g., MainConcept Live Encoder or similar) Multi-tenant SaaS and multi-region deployment experience OpenTelemetry or comparable observability stacks (tracing, metrics, logs) Blue-green or canary release strategies for stateful, always-on systems AMI or image build tooling (e.g., Packer) and EC2 fleet lifecycle management Python packaging/tooling such as uv, and schema libraries such as marshmallow or jsonschema Static analysis and code-quality tooling (mypy, bandit, black, isort, pre-commit) in a CI/CD pipeline such as GitHub Actions Location: Burlington, Ontario Hours: Monday - Friday, 40 hours.

Vacancy: This is an existing position. Salary Range: $100,000 to $135,000, based on relevant experience About the Role The evertz.io Engineering Team builds next-generation systems for content management and distribution in the Media and Entertainment industry.

Disney, NBCUniversal, Discovery, BBC, and many other content producers and publishers use our products and services to make the most of their file-based and live content for the least effort.

We work with high quality video in real-time and non-real-time scenarios across a wide range of cutting-edge tech.

Specializations within the group span from low-level video manipulation and analysis, through back-end management and orchestration services, to web delivered UIs.

There may also be opportunities for working as a member of the Scientific Computing Group who work in computer vision, data science and machine learning, taking experiments in Jupyter notebooks through to deployment in production.

This makes for a challenging and rewarding engineering experience of continual learning and plenty of opportunity to explore different parts of the stack.

Prior broadcast or media industry experience is not required; curiosity, strong engineering fundamentals, and willingness to learn the domain are more important.

Our technology stack includes a serverless microservice architecture that capitalizes on the full breadth of AWS services with code written in Python, Rust and Java.

Our UI uses the latest versions of Angular, Typescript and NgRx.

Our CI/CD pipelines leverage AWS, Jenkins, Nexus, and Bazel in addition to our in-house release-management application to build and release 100’s of software components.

• “Work is a thing you do, not a place you go” We work in agile, low-bureaucracy, high-creativity, cross-functional teams spread across the world.

It’s a highly creative work environment where we support your growth with opportunities for career progression, mentoring others and third-party education.

The team is built on trust and is relaxed, open and welcoming to all, and there’s fun to be had with regular social events and sports teams.

As part of this role, you will be expected to: Participating in design discussions with Head of Stream Automation, Product Owners and Solution Architects for adding new or improving existing features Taking a feature from scoping requirement to actual launch in our cloud platform Design & document requirements/features/API Close collaboration with UI & QA team Collaborate with SRE team to improve system observability, incident response, and troubleshooting Develop high-quality, understandable, maintainable software with appropriate automated tests and safe deployment practices Apply practical testing strategies that support reliable delivery and maintainable systems Engage with and involve QA team where an integration/end-to-end test is required Continuous learning to improve yourself and mentoring Junior Engineers Participate in peer review, technical discussions, and shared engineering standards About Evertz Microsystems (TSX: ET) Evertz is a global leader in broadcast technology, delivering cutting-edge hardware and software solutions that deliver content to television sets, on-demand services, WebTV, IPTV, and mobile devices (like phones and tablets) worldwide.

Trusted by major broadcast facilities, telcos, and satellite providers on every continent, we're known for end-to-end innovation that sets the industry standard.

Canadian-headquartered with offices around the world, Evertz has 2,000+ employees and has been recognized as one of Canada's 50 Best Managed Companies — a testament to our commitment to excellence and global impact.

Join a team where your work shapes the future of broadcast and new media industries.

Evertz is committed to equal opportunity employment.

Accommodations are available throughout the recruitment process for applicants with disabilities — please notify HR when scheduling your interview.

Artificial intelligence (AI) technology may be used in our recruitment process to assist with resume screening and interview note-taking.

All hiring decisions are made by our team without AI involvement.

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When you apply to a job on this site, the personal data contained in your application will be collected by Evertz Microsystems Ltd (“Controller”), which is located at 5292 John Lucas Drive, Burlington, Ontario, Canada and can be contacted by emailing privacy@evertz.com.

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