Senior Manager, Machine Learning and Data Science

3 weeks ago

Old Toronto, Canada Loopio Full time
About Loopio

Loopio is a workplace that unleashes learning & growth opportunities for our Loopers. We provide autonomous, challenging work that allows each employee to master their craft. We attract and retain people who are naturally curious, have grit and are eager to grow and build their careers. At Loopio, we genuinely support each other, because true success comes from working as #oneteam. Loopio’s Data Enablement Team works together on a mission to transform the RFP response process into a rapid and seamless experience. Our team works across all platform portfolio features and delivers innovative solutions where it matters the most for our customers.

We are Hiring: Sr. Manager, Machine Learning and Data Science

We are looking for an experienced Sr. Manager, Machine Learning and Data Science, to lead a dynamic group of Machine Learning Engineers and Data Scientists on our Data Enablement team. Our ideal candidate has deep technical and leadership skills and is comfortable working in an evolving technology infrastructure and dynamic environment. This is a unique opportunity to join a growing team of creative and passionate individuals committed to solving real-world problems. You will empower engineers, product, and data scientists with tools that enable and streamline data-driven decision-making, analysis, and feature development. You will partner closely with other Senior Engineering Leaders, Data Scientists, Machine Learning Engineers, Product Managers and Designers, and other business stakeholders to help us take Loopio’s data value and AI innovation to the next level.

What You'll Be Doing
  1. You will be a valuable member of the Senior Engineering Leadership team and, as such, responsible for fostering a thriving culture, product execution and innovation.
  2. You will be partnering with the rest of the Leaders across the Loopio organization and representing our Data and ML/DS team to provide valuable insights and support.
  3. Promote data-driven decision-making across the organization through data expertise.
  4. Lead the development of advanced automation tooling for data orchestration, evaluation, testing, monitoring, administration, and data operations.
  5. Inspire and lead the Data Enablement team, which includes Machine Learning Engineers, Data Scientists and Data Engineers, by setting clear objectives, promoting innovation, and ensuring alignment with the company’s strategic goals.
  6. Responsible for creating a high-performing team and fostering a culture of technical excellence, continuous improvement, and collaborative problem-solving within the team.
What You'll Bring to the Team

10+ years of experience in software engineering, machine learning, or data science with recent experience in machine learning demonstrating mastery of advanced ML algorithms, frameworks, 3+ years of people management experience, including highly effective conflict resolution, performance management, talent reviews, succession planning, coaching low to high-level performer. Strong understanding of business operational and technical/engineering concepts backed by problem-solving skills to help drive technical decision-making. Experience with distributed systems development using microservices architecture.

Experience in building and maintaining an enterprise data warehouse (EDW) and being well-versed in Data Lake architecture and design. Demonstrated experience designing and developing cloud-based training pipelines. Ability to implement state-of-the-art deep learning algorithms. Knowledge of deep learning frameworks, algorithms and design of various inference systems, including cloud-based servers and hardware accelerators. Experience in Public Cloud (AWS, Azure or GCP), Docker containers, Kubernetes, Infrastructure Automation and API development.

Bonus Qualifications
  • Experience with container orchestration (leveraging tools like Docker, ECS, Kubernetes)
  • Experience working with BI PaaS / SaaS solutions
  • Familiarity with microservice architectures
  • Hands-on experience as ML/DS engineer
  • Experience with Natural Language Processing techniques
  • Experience using deep learning frameworks such as TensorFlow / Pytorch
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