Job Title: Senior Machine Learning Engineer
(Reinforcement Learning)
Location: Canada (100% Remote working)
Perm/FTE Role
Citizens and Permanent Residents and those authorized to work in the Canada are encouraged to apply. We are unable to sponsor Visa or any work authorizations at this time
Job
Description
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.).
A reasonable, good faith estimate of the minimum and maximum base salary for this position is $150 K CAD to $170 K CAD per year
* The pay range listed above reflects the expected
starting salary /Pay rate for this role. This range may be adjusted based on
market conditions, location, and other relevant factors. The Company will
determine the final starting salary/Pay rate in consultation with the selected
candidate(s), in full compliance with applicable laws
