Machine Learning and Data Science Director

2 days ago

Toronto, Ontario, Canada Loopio Full time
About Loopio

Loopio is a workplace that fosters growth opportunities for our employees. We provide autonomous, challenging work that allows each employee to master their craft. Our team members 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 together as one team. Our Data Enablement Team works together on a mission to transform the RFP response process into a rapid and seamless experience.

Job Summary

We are looking for an experienced Director, Machine Learning and Data Science, to lead a dynamic group of Machine Learning Engineers and Data Scientists on our Data Enablement team. The 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.

Key Responsibilities
  • Foster a thriving culture, product execution, and innovation as a valuable member of the Senior Engineering Leadership team.
  • Lead the development of advanced automation tooling for data orchestration, evaluation, testing, monitoring, administration, and data operations.
  • Inspire and lead the Data Enablement team by setting clear objectives, promoting innovation, and ensuring alignment with company goals.
  • Create a high-performing team and foster a culture of technical excellence, continuous improvement, and collaborative problem-solving within the team.
  • Lead with company values in mind and help create bridges across organizations.
  • Develop scalable data pipelines using Databricks, AWS (Redshift, S3, RDS), and other cloud technologies.
  • Support Loopio's data warehouse (Redshift) and data lake (Databricks delta lake).
  • Orchestrate pipelines using workflow frameworks/tooling.
Requirements
  • A minimum of 10 years in software engineering, with profound knowledge in machine learning or data science.
  • Demonstrable experience with advanced ML algorithms and frameworks as well as NLP/NLU is essential.
  • Strong leadership background with proven ability to manage machine learning or data science teams in fast-paced environments.
  • Rugged understanding of both business operations and technical/engineering principles, equipped with superior problem-solving skills to steer technical decision-making.
  • Proficient in distributed systems development using a microservices architecture.
  • Experienced in constructing and managing an Enterprise Data Warehouse (EDW), with a solid grasp of Data Lake architecture and design.
  • Skilful in designing and implementing cloud-based training pipelines and state-of-the-art deep learning algorithms.
  • Well-versed in deep learning frameworks, algorithms, and inference system designs, including those for cloud-based servers and hardware accelerators.
  • Experience with Public Cloud platforms (AWS, Azure, or GCP), Docker containers, Kubernetes, Infrastructure Automation, and API development.
Benefits
  • Estimated salary: $200,000 - $300,000 per year.
  • A remote-first workplace with Hub Regions spanning Canada, UK, and India.
  • Collaborate with your teams virtually and have established core sync hours and focus time during the workday.
  • Your manager supports your development by providing ongoing feedback and regular 1-on-1s.
  • You have tons of autonomy and responsibility.
  • Learn more than you thought was possible; our team is obsessed with personal and professional growth.
  • Set up to work remotely with a MacBook laptop, a monthly phone and internet allowance, and a work-from-home budget to help get your home office all set up.
  • Join us in regular company socials, AMA (Ask-Me-Anything), and quarterly kick-off to celebrate the big wins and milestones as #oneteam.
  • Part of an award-winning workplace and one of Canada's fastest growing companies with ample opportunity to make a big impact here.

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