At Xtract One (TSX: XTRA), our vision is to create a world where great experiences and safety work together. Through a people focused and collaborative approach, we leverage purpose-built AI to create transformative technology solutions that deliver exceptional experiences, safer environments, and informed operational insights for our customers, and their patrons and staff.
Summary:
The Senior Machine Learning Engineer at Xtract One is focused on SaaS and hardware products and is a seasoned professional with a proven track record of delivering complex machine learning solutions in production environments. This role involves leading end-to-end machine learning projects deployed on reliable edge computing systems, and providing technical guidance, evaluating and adopting new tools and frameworks, collaborating with stakeholders to align machine learning solutions and business goals. In this role, you will contribute to driving the technical direction of projects, mentoring team members, and contribute to strategic decision-making. This is an exceptional opportunity for an experienced individual to make a significant impact and lead our team to new heights.
Responsibilities:
Work with development and product teams to design, develop, and maintain microservices-based backend systems that are scalable, fault-tolerant, and high-performance.
Develop edge services and APIs that are optimized for performance and security.
Drive the ML development lifecycle, utilizing expertise to design a reliable data pipeline, code, test, debug, and deploy advanced and scalable machine learning and data solutions.
Write high-quality, reusable, and maintainable code using Python and other relevant programming languages.
Define and enforce machine learning architectures and design standards.
Ensure developer, deployment and user quality stories are first-class citizens in our software.
Take ownership of product-related components and help drive them to production.
Work in agile development methodologies with a multidisciplinary team.
Participate in code reviews and provide constructive feedback to other developers.
Establish and enforce best practices in data reliability, ML development, code quality, and testing.
Requirements:
Bachelor’s degree in Computer Science, Electrical Engineering, Data Science or a related field. Master’s or Ph.D. preferred.
8+ years experience in a software engineering, machine learning engineering or a similar role using Python and other relevant programming languages.
Ability to write clear, well-structured and documented code.
Excellent understanding of software development best practices such as version control, agile, code reviews, and automated testing.
Extensive experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or onnx.
Experience with database systems (SQL or NoSQL).
Experience with edge computing.
Experience with cloud platforms like AWS, Azure, or GCP would be a plus.
Advanced problem-solving and analytical skills.
Exceptional communication and leadership abilities.
Strong mentoring and coaching skills, with a track record of developing team members.
Deep knowledge of version control systems and software design principles.
Track record of successfully delivering complex and scalable machine learning solutions.
Why Xtract One?
Join a dynamic team of talented professionals who are passionate about cutting-edge technologies.
Opportunity to work on challenging projects and make a real impact on the Company's success.
Competitive salary and benefits package, annual bonus and publicly traded stock options.
Ongoing opportunities for professional growth and development.
Collaborative and inclusive work environment that values diversity.
The job location for this hybrid position is in downtown Toronto.
Xtract One is an equal opportunity employer. To learn more about our Diversity and Governance policies, please visit One welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.
#J-18808-Ljbffr