AI/ML Ops Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Take ownership of the AI/ML loop from start to finish at scale across all pipelines, encompassing model training, deployment, monitoring, and retirement.

• Create, enhance, and implement ML models.

• Design, construct, and manage the infrastructure for model building and serving.

• Deploy trained scripts as live endpoints capable of handling real-time requests.

• Execute ML workflows as containerized Infrastructure as Code using tools like Terraform, GitHub Actions, Docker, and Kubernetes.

• Develop and automate standardized container pipelines for training, feature engineering, and inference processes.

• Oversee CI/CD practices using GitHub.

• Establish a comprehensive testing strategy throughout the entire ML pipeline, which includes model validation, integration, load, and deployment testing.

• Create visibility and alerting mechanisms for deployed pipelines.

• Design ML governance tools for the oversight and management of deployed infrastructure.

• Apply best practices in data, feature, and model lifecycle management.

• Play a significant role in AI architecture and design decisions, with a primary focus on ML pipeline initiatives.

• Collaborate with Engineering, the Security Operations Center (SOC), and the Adversary Pursuit Group (APG).

• Report directly to the Vice President of AI and Data.

⛳️ Requirements

• A minimum of 5 years of practical ML Engineering experience.

• Experience in personally training and deploying models in a production setting.

• A well-architected approach with an emphasis on efficiency, performance, security, and reliability.

• Comfortable managing deployment pipelines from start to finish.

• Strong analytical and problem-solving skills.

• Proficient in data-driven decision-making.

• Excellent communication and interpersonal abilities.

• Capable of influencing and collaborating with stakeholders at all levels.

• Experience with cloud-based ML infrastructure, particularly AWS.

• Familiarity with SageMaker and Bedrock.

• Experience with Kafka and Spark for managing inference streams and event-driven processing.

• Proficient in MLflow and SageMaker Pipelines.

• Knowledge of Terraform, AI CI/CD, and GitHub Actions.

• Familiarity with ML governance, including data, model, and feature versioning, monitoring, and testing.

• Experience with Docker, Kubernetes, and ECS/EKS.

• Proficient in Python and Bash.

• Proficient in SQL and SparkSQL.

• Knowledge of GitFlow, CI/CD workflows, and DevOps best practices.

• Experience with AI-assisted development lifecycles.

• Proven track record of building high-availability, production-grade systems with visibility and alerting.

• Nice to have: Experience with Transformer Neural Networks.

• Nice to have: Familiarity with Agile Scrum/Kanban methodologies.

• Nice to have: Experience with Anthropic, OpenAI, and LiteLLM APIs and SDKs.

• Nice to have: Background in Cybersecurity, IoT, or NLP.

• Nice to have: Experience with Grafana or CloudWatch.

🏝️ Benefits

• Global equity participation available for employees, with program details varying based on location and employment structure.

• Eligibility for a discretionary bonus.

• Competitive benefits for international employees in alignment with local market standards and applicable country laws.

• Eligible US employees will receive Health Insurance, Vision, Dental, and Life Insurance plans.

• Eligible US employees benefit from a robust 401k plan.

• Eligible US employees are granted Discretionary Time Off.

• Additional minor perks included.