Engineer Manager – AI

5 days ago

Burnaby, British Columbia, Canada Autodesk Full time

Job Requisition ID #

25WD85267

25WD85267 Engineer Manager – AI & ML Platform

Position Overview

We are seeking a hands-on Engineering Manager to lead our skilled team of software and ML engineers in the design, development, and maintenance of AMP, our next generation machine learning platform. Your management role extends beyond providing technical leadership; you will be a pivotal figure in fostering collaboration with partners and driving platform adoption. Collaborating closely with cross-functional teams including product management, data science, and infrastructure, you will define and execute the AI/ML platform roadmap. Your responsibilities encompass driving the technical strategy, execution, and delivery of scalable AI/ML platforms, ensuring alignment with organizational goals and priorities. This role requires a blend of technical expertise in AI/ML technologies, strong leadership skills, and a proven track record of delivering complex projects on time and within budget.

Responsibilities

  • Lead and mentor a team of engineers in the development and deployment of AI/ML solutions
  • Collaborate with cross-functional teams including product management, data science, data and cloud infrastructure to define and execute the AI/ML platform roadmap
  • Provide sound technical guidance and drive crucial technology decisions
  • Actively participate in coding review processes, and problem-solving alongside your team
  • Stay updated with the latest advancements in AI/ML technologies
  • Provide guidance of the design and architecture of scalable, reliable, and efficient AI/ML systems
  • Ensure adherence to best practices in software development, code quality, and security standards
  • Manage project timelines and resource allocation to drive deliverables
  • Foster a culture of innovation, agility, collaboration, and continuous improvement within the engineering team
  • Actively participate in the hiring process to attract and onboard top-tier engineering talent, ensuring the team possesses the necessary skills and expertise to execute on the AI/ML platform vision

Minimum Qualifications

  • BS/MS in Computer Science, Engineering, or a related field. (MS preferred)
  • Minimum of 3 years of experience of software engineering, with at least 3 years in a leadership or management role
  • Proven experience leading and mentoring software and ML engineering teams. Ability to inspire, motivate, and guide team members towards achieving project goals
  • Ability to align technical objectives with business goals. Skilled at roadmap development, setting clear objectives, and prioritizing tasks
  • Ability to plan, execute, and deliver projects timely and efficiently allocate resources and managing workload distribution among team members
  • Skilled in identifying potential project risks and developing mitigation strategies
  • Strong background in AI/ML with experience in deep learning, statistical modeling, and neural networks
  • Ability to design and build scalable, high-performance systems with understanding of cloud services (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes)
  • Solid understanding of agile software development methodologies and management practices
  • Working knowledge of CI/CD pipelines, automation tools, and practices for machine learning lifecycle management
  • Excellent communication skills to effectively liaise with various stakeholders, including product managers, data scientists, and upper management
  • Ability to foster a collaborative team environment
  • Managers of Professional roles – and/or managers of people that manage Support roles
  • Manages work for medium size team, or multiple small teams and achieves results by directing work through supervisors/team leads and professional employees
  • Typically focused on areas of subject matter expertise within one discipline
  • Keep their teams organized, efficient, effective, productive, and motivated through professional leadership techniques
  • Responsible for managing deliverables against expected results with a timeline that is typically longer than a quarter
  • Focus is more operational, and decisions are typically made within established policies, procedures and objectives

Preferred Qualifications

  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform, specifically AWS SageMaker or Azure Machine Learning
  • Prior experience in building AI/ML platforms
  • Understanding of MLOps principles and practices for effectively managing and automating machine learning workflows, including model versioning, monitoring, and deployment
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