AI Engineer

Compass Analytics is excited to recruit a talented and driven AI Engineer to join our growing Analytics Delivery team. The ideal candidate will have a passion for designing, developing, and deploying cutting‑edge AI and ML applications, as well as a strong foundation in MLOps and software engineering best practices. About Compass Analytics Compass Analytics specializes in delivering end-to-end data solutions to clients across diverse industries ranging from aviation, healthcare, financial services, retail, and sports.

Our expertise spans data architecture, data engineering, data governance, artificial intelligence & machine learning, process automation, and dashboarding. We pride ourselves on fostering a culture that emphasizes purpose, elegance, rigor, and a fun environment as we get work done. Number of Open Roles: One (1) Location: Montreal, QC (Hybrid) Duration: Permanent Full-Time Key Responsibilities Under the guidance of our Leadership Team & Project Managers, the AI Engineer will be responsible for the following tasks: Collaborate with stakeholders to design, build, and deploy scalable AI and machine learning solutions aligned with business objectives.

Collect, preprocess, and engineer features from structured and unstructured data to feed into ML models. Develop, train, and fine‑tune models using supervised, unsupervised, and deep learning techniques. Integrate AI/GenAI models into production environments, ensuring reliability, performance, and scalability.

Implement MLOps best practices for model versioning, monitoring, retraining, and CI/CD integration. Maintain comprehensive technical documentation covering model architectures, data pipelines, experiments, and deployment processes. Stay informed on advancements in AI/ML research and recommend adoption of emerging tools, frameworks, and techniques.

Support Data Engineering and Analytics projects as well as other projects within the scope of the assigned mandate (e.g., dashboarding or pipeline automation). Technical Capabilities Programming Languages: Proficiency in SQL and Python is essential; experience with PyTorch, Scala, or other languages is a plus. GenAI: Familiarity with leading GenAI frameworks (e.g., LangChain, LangGraph) and hands‑on experience building applications using AI is a plus.

Agentic AI: Hands‑on experience integrating Agentic AI into your software development workflow (e.g., Claude Code or GitHub Copilot) is a plus. Platforms: Knowledge of platforms such as Databricks, Snowflake, AWS, Azure, or Google Cloud. DataOps: Familiarity with CI/CD pipelines and tools such as GitHub for version control and deployment.

Collaboration Tools: Experience with JIRA and Confluence is a plus. Education: Bachelor’s degree in Computer Science, Software Engineering, Math/Physics, or a related field. Preferred Qualifications Problem Solving: Strong analytical and problem‑solving skills with the ability to troubleshoot complex data issues.

Organized & Rigorous Approach: Strong organizational skills and attention to detail, ensuring rigor in development and accuracy in outputs. Communication: Excellent verbal and written communication skills, with the ability to collaborate effectively across teams. #J-18808-Ljbffr