Develop high-scale reinforcement learning solutions. Translate vague requirements into actionable models. Optimize machine learning and reinforcement learning solutions for performance and scalability.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Job Title: Senior Machine Learning Engineer (Reinforcement Learning)
Location: Canada (100% Remote working)
Perm/FTE Role
Job Description
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.
- Optimization: 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.
Interested in remote work opportunities in Machine Learning & AI? Discover Machine Learning & AI Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
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.
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
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
Similar Jobs
Explore other opportunities that match your interests
synergyloft
Senior Machine Learning Engineer - Reinforcement Learning
Harvey Nash
