Senior Machine Learning Engineer (Reinforcement Learning)

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 an Reinforcement Learning focused 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 with a focus on using and implementing Reinforcement learning on real‑world applications .You will know the right tools and approach for an RL or 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.

What You’ll Do

Develop Solutions with Reinforcement Learning at a large scale.

Design and deploy RL solutions from data selection, model training, to productionization.

Translate Requirements : Interpret vague requirements and develop models to solve real‑world problems.

Data Science : Conduct ML experiments using programming languages with machine learning libraries.

Optimisation : Optimise ML / RL solutions for performance and scalability.

Custom Code : Implement tailored ML / RL code to meet specific needs.

RL Architecture Design : Create reinforcement learning architectures using Google Cloud tools and services.

(Bonus!) Data Engineering : Ensure efficient data flow between databases and backend systems.

(Bonus!) MLOps : Automate ML workflows, focusing on testing, reproducibility, and feature / metadata storage.

(Bonus!) Engineering Software for Production : Build and deploy production‑grade software for machine learning and data‑driven solutions.

What You’ll Bring

Multiple years experience as a Machine Learning Engineer specifically using Reinforcement Learning.

Prior work on designing and implementing RL algorithms on real world projects (using non‑dummy data).

Experience with data requirements for RL algorithms (quantity, type and schemas)

A strong understanding of the training procedure and timelines for RL

Experience with selecting and adapting existing RL models for novel solutions (e.g., SAC, DQN, PPO etc.)

Familiarity with developing RL algorithms using open source ML libraries (preferably python‑based e.g. pytorch or tensorflow)

Ideally, experience with distributed RL libraries (e.g., Ray RLLib)

Experience with RL in conjunction with a Computer Vision application or using Computer Vision Data

Proficiency in Python as a backend language, capable of delivering production‑ready code in well‑tested CI / CD pipelines.

Bonus Points If You Have :

Cloud Expertise : Familiarity with cloud platforms such as Google Cloud, AWS, or Azure.

Software Engineering : Hands‑on experience with foundational software engineering practices.

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.

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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