At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud Platform. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.
As a Lead Machine Learning Engineer, you will be the technical authority for our most ambitious client projects. You will set the technical vision, guide teams of talented engineers, and translate complex business challenges into cutting-edge AI solutions on Google Cloud. You'll be an advocate of high-quality engineering and best-practice in production software as well as rapid prototypes.
This is a hands-on leadership role where you will not only architect solutions but also actively lead client discussions and oversee project delivery from start to finish.Your responsibilities will involve building trusted relationships with prospects, finding creative ways to use machine learning to solve problems, scoping projects, and overseeing the delivery of these engagements.
To be successful, you will need strong ML & Data Science fundamentals and will know the right tools and approach for each ML use case. You'll be comfortable with model optimization and deployment tools and practices. Furthermore, you'll also need excellent communication and consulting skills, with the desire to meet real business needs and deliver innovative solutions using AI & Cloud.
Drive Technical Strategy from Pre-Sales to Delivery: Act as the lead technical authority in high-stakes engagements. You will partner with our commercial team to architect winning solutions, and then lead the delivery of enterprise-grade systems—such as GenAI agents for financial institutions, real-time recommendation engines for global retailers, or predictive maintenance models for the manufacturing sector.
Architect & Implement Production-Grade Solutions: Own the complete technical lifecycle for your projects. You will design end-to-end ML architectures on GCP, implement robust MLOps pipelines using Infrastructure-as-Code (Terraform), and ensure all solutions—from sophisticated multi-agent systems to classical models—are optimized for performance, scalability, and security.
Shape Our Technical Standards: Collaborate directly with the Head of Delivery to define the technical DNA of our ML practice, evolving the best practices, architectural patterns, and standards that ensure excellence across the company.
Lead Strategic Internal Initiatives: Spearhead the development of internal accelerators and reusable frameworks that enhance our delivery capabilities and solidify our position as industry leaders.
Cultivate Engineering Talent: Formally mentor and coach our junior and mid-level engineers, elevating the team's collective skill set through rigorous code reviews, technical guidance, and career development.
Experience: You have 7+ years of professional experience in machine learning and software engineering, with at least 2 years in a formal or informal leadership capacity (e.g., tech lead, project lead, or senior mentor).
Cloud & Systems Architecture Expertise: You possess a proven ability to architect and deploy scalable, production-grade ML solutions on a major cloud platform (GCP is a significant asset). This includes hands-on experience with Infrastructure-as-Code tools (e.g., Terraform) and designing for distributed computing.
Expert-Level Engineering Craftsmanship: You have deep, hands-on expertise in Python for backend ML systems and a mastery of software engineering best practices (e.g., clean architecture, robust testing, CI/CD). You can fluently design and build REST APIs (e.g., using Flask/FastAPI) and are proficient in SQL for complex data manipulation.
Consultative Communication & Mentorship: You have an exceptional ability to communicate complex technical concepts to diverse audiences, from C-level stakeholders to junior engineers. You excel at leading technical discussions, presenting solutions, and mentoring teammates to elevate their skills.
Bonus Points If You Have:
Prior experience in a client-facing or consulting role.
Professional Google Cloud certifications (e.g., Professional Machine Learning Engineer).
Deep experience with the broader MLOps ecosystem (e.g., Kubeflow, Vertex AI Pipelines, MLflow).
Experience building interactive demos for ML models (e.g., using Streamlit, Gradio).
We believe in empowering our team to thrive, with benefits including:
20 days of paid vacation per calendar year
Public Holidays for your Province of Residence
5 Wellness days (sickness, personal time, mental health)
5 Lifestyle days (religious events, volunteer day, sick day)
Matching Group Retirement Savings Plan after 3 months
Competitive Group Insurance plan on Day 1 - individual premium paid 100%!
Virtual Medicine and Family Assistance Program - 100% employer-paid!
Home office budget - We are 100% remote!
CAD $70/month for internet/phone expenses
CAD $1,500 every 3 years for tech accessories and office equipment (monitor, keyboard, mouse, desk, etc.) starting on Day 1
Company-supplied MacBook Pro or Air
CAD $400/year for books, relevant app subscriptions or an e-reader.
Opportunities for paid certifications
Opportunities for professional and personal learning through Udemy Business
Regular company off-sites and meetups
Salary: CAD 175,000 - 200,000.
Datatonic is a UK-based company with an Americas division located in Canada. The Canadian team operates remotely, with members distributed across North and South America. This role is open to candidates located anywhere in Canada.
Join us to work alongside AI enthusiasts and data experts who are shaping tomorrow. At Datatonic, innovation isn’t just encouraged - it’s embedded in everything we do. If you’re ready to inspire change and deliver value at the forefront of data and AI, we’d love to hear from you!
Apply now and take your career to the next level.
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