ML Software Developer

DNEG•Montreal, QC

46d

About The Position

The ML Technology department at Brahma DNEG-Dedicated Unit (Brahma DDU) explores, tests, and deploys machine-learning and automation solutions to support the technology and infrastructure that powers DNEG’s multi-site, global VFX and Feature Animation studio. With thousands of artists producing tens of thousands of shots across film, TV, and immersive experiences, we face complex scaling and workflow challenges. As a Senior Software Developer, you will act as an architect building Python applications, high-quality tools, services, and web front-end UIs that enable award-winning VFX and feature animation work.

Requirements

Experience as an architect for Python applications
Strong programming and shell-scripting skills (Python; Bash).
Experience building and troubleshooting non-trivial packages (C++11–17, CMake, autotools, setuptools/pip/poetry, RPM).
Linux expertise and command-line proficiency.
Solid grasp of systems architecture and software engineering fundamentals.
Ability to articulate complex technology to non-experts and collaborate openly.
Confidence in navigating ambiguity and providing pragmatic solutions.
Proactive mindset and comfort with multiple priorities.
Logical, methodical approach to problem solving.

Nice To Haves

Experience as Lead on at least one project
Significant experience with a major package/ports system.
Experience monitoring, collecting, and analyzing diagnostics to drive resilience.
Practical experience with Git and issue tracking systems (Jira).
Familiarity with ops/CI/CD tooling (Elastic Stack, Graphite/Grafana/StatsD, Sensu, Jenkins/GitHub Actions).
Understanding of sysadmin responsibilities (networking, filesystems, environment management).
Relevant qualifications (CS/CE degree; RHCSA/RHCE, etc.).
Demonstrable open-source contributions.

Responsibilities

Deploy ML solutions and integrate AI tooling within the VFX pipeline with minimal burden on artists and production.
Design and build web front-end UIs (dashboards, curation tools, job control, review) that make ML/automation workflows intuitive and accessible.
Collaborate with global stakeholders and architects to implement cost-effective data and MLOps pipelines; document methodologies.
Build, package, and configure complex software systems across Linux.
Improve efficiency, stability, and observability through profiling, metrics, and tracing.
Validate work with methodical testing (unit/integration/e2e).
Write clear technical documentation and workflow guides for artists and developers.
Manage escalated troubleshooting and debugging for ML-driven tools and services.
Work collaboratively under tight deadlines; mentor developers, assign tasks where appropriate, and report to the Head of ML Technology.
Enforce standards via CI: formatting (e.g., black/clang-format), linting (ruff/eslint, clang-tidy), typing (Python type hints, TypeScript), and test coverage gates.
Require code reviews for all merges; maintain modular, testable designs with clear separation of concerns and DCC-agnostic cores where applicable.
Documented APIs (OpenAPI/Protobuf), versioned schemas, and backward-compatible changes.
Secure-by-default practices (authn/z, secrets management), performance budgets, and telemetry by design.