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Senior Machine Learning Engineer

datatonic • Canada
Remote
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AI Summary

Shape the future of AI & Data with Datatonic as a Senior Machine Learning Engineer. Develop machine learning solutions, lead projects, and build trusted relationships with clients. Strong ML & Data Science fundamentals and excellent communication skills required.

Key Highlights
Develop machine learning solutions
Lead projects and client discussions
Build trusted relationships with clients
Key Responsibilities
Translating Requirements
Conduct ML experiments
Leverage generative AI
Optimise machine learning solutions
Implement tailored machine learning code
Ensure efficient data flow
Automate ML workflows
Create machine learning architectures
Build and deploy production-grade software
Technical Skills Required
Python Machine Learning Google Cloud Platform
Benefits & Perks
20 days of paid vacation per calendar year
Public Holidays for your Province of Residence
5 Wellness days
Nice to Have
Scale-up experience
Cloud certifications

Job Description


Shape the Future of AI & Data with Us

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.

Your Mission

As a Senior Machine Learning Engineer, you'll know how to engineer beautiful code in Python and take pride in what you produce. You'll be an advocate of high-quality engineering and best-practice in production software as well as rapid prototypes.

Whilst the position is a hands-on technical role, we'd be particularly interested to find candidates with a desire to lead projects and take an active role in leading client discussions. 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 optimisation 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.

What You’ll Do

  • Translating Requirements: Interpret vague requirements and develop models to solve real-world problems.
  • Data Science: Conduct ML experiments using programming languages with machine learning libraries.
  • GenAI: Leverage generative AI to develop innovative solutions.
  • Optimisation: Optimise machine learning solutions for performance and scalability.
  • Custom Code: Implement tailored machine learning code to meet specific needs.
  • Data Engineering: Ensure efficient data flow between databases and backend systems.
  • MLOps: Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage.
  • ML Architecture Design: Create machine learning architectures using Google Cloud tools and services.
  • Engineering Software for Production: Build and deploy production-grade software for machine learning and data-driven solutions.

What You’ll Bring

  • Experience: Multiple years experience as a Machine Learning Engineer, preferably with a consulting background.
  • Programming Skills: Proficiency in Python as a backend language, capable of delivering production-ready code in well-tested CI/CD pipelines.
  • Cloud Expertise: Familiarity with cloud platforms such as Google Cloud, AWS, or Azure.
  • Software Engineering: Hands-on experience with foundational software engineering practices.
  • Database Proficiency: Strong knowledge of SQL for querying and managing data.
  • Scalability: Experience scaling computations using GPUs or distributed computing systems.
  • ML Integration: Familiarity with exposing machine learning components through web services or wrappers (e.g., Flask in Python).
  • Soft Skills: Strong communication and presentation skills to effectively convey technical concepts.

Bonus Points If You Have

  • Scale-up experience.
  • Cloud certifications (Google Cloud Professional Machine Learning Engineer, AWS Solution Architect, etc.).

What’s in It for You?

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
Why Datatonic?

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!

Are you ready to make an impact?

Apply now and take your career to the next level.

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