Senior Machine Learning Engineer – Reinforcement Learning

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November 10

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Datatonic

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Artificial Intelligence • eCommerce • Telecommunications

Datatonic is your go-to AI partner that addresses complex business challenges through advanced cloud data and AI consultancy. They offer a range of services including generative AI applications for various industries such as Retail, Telecommunications, Gaming, and Financial Services. With a focus on data-driven decision-making and analytics, Datatonic empowers businesses to optimize their operations and enhance customer engagement across multiple sectors.

51 - 200 employees

Founded 2013

🤖 Artificial Intelligence

🛍️ eCommerce

📡 Telecommunications

💰 Pre Seed Round on 2013-01

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• 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