Engineering Technical Lead/Chef d’équipe technique
August 20
🏢 In-office - Montreal
AWS
Azure
Cloud
Docker
Google Cloud Platform
Java
Kubernetes
Microservices
Python
PyTorch
Scala
Scikit-Learn
Tensorflow
Go
Description
• This team member will work with us to formulate engineering timelines, organize work, make workflow decisions (e.g. coding style), identify technical challenges, communicate across the organization, and help lead the day to day activities of the team. • The ideal candidate has worked at the intersection of machine learning and engineering, understands the key technical challenges in working with ML systems, and has led teams of engineers to deliver successful software solutions. • We are looking for someone who can be hands-on on the short term and establish themselves as both an engineering expert and leader, and then progressively take on a larger amount of responsibility.
Requirements
• Bachelor's or master's degree in computer science, engineering, or a related field. A Ph.D. in a relevant field is preferred. • Extensive Architectural Experience: 10+ years of experience in machine learning, data engineering, or related roles, with a focus on architecting and delivering machine learning solutions at scale. • Experience with cloud-based platforms (e.g., AWS, Google Cloud Platform, Azure) is required. • Architecture and Design Skills: Strong architectural skills with experience in designing and implementing scalable, distributed, and fault-tolerant systems. Familiarity with microservices architecture, containerization (e.g., Docker), and orchestration frameworks (e.g., Kubernetes) is a plus. • Programming and Tooling: Expertise in programming languages like Python, Java, or Scala, and knowledge of ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). • Data Engineering and Preprocessing: Strong understanding of data engineering principles, data preprocessing techniques, data governance, and data integration. • Strong Communication and Leadership: Excellent communication skills with the ability to communicate complex technical concepts to both technical and non-technical stakeholders. Proven leadership abilities with experience in guiding and mentoring engineering teams. Strong team player with the ability to collaborate effectively in cross-functional teams. • Problem-Solving and Analytical Skills: Strong analytical thinking, problem-solving, and troubleshooting skills to address complex architectural challenges. • Adaptability and Innovation: Ability to adapt to evolving technologies and business needs. Strong drive for innovation and continuous learning. • Software Engineering Skills: Familiarity with software engineering best practices, version control systems, and agile development methodologies. • Experience developing machine learning applications and deploying in a business setting, especially generative AI applications, is highly desirable.
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