Machine Learning Engineer Job at Thrive Career Wellness Inc (Toronto)

Job Description

We are seeking a talented and experienced Machine Learning Engineer to join our growing AI team at Thrive. This role will play a critical part in designing and implementing LLM agents, architectures, and machine learning models that power Thrive’s AI-driven career guidance platform. You will work on applied AI solutions that enable personalized, intelligent career experiences for job seekers, leveraging cutting-edge approaches in agentic frameworks, reinforcement learning, and large language models. If you are passionate about applied AI research, enjoy solving complex problems involving sequential decision-making, and want your work to have real-world social impact, this is the role for you.

Job Responsibility

Design, develop, and evaluate LLM agents and agentic frameworks, including reinforcement learning and sequential decision-making approaches
Research and implement multi-agent architectures to coordinate and deploy AI agents effectively
Train, fine-tune, and optimize machine learning models for production deployment
Build and iterate on MVPs and client-facing AI solutions in collaboration with cross-functional teams
Conduct applied research on large language models, focusing on understanding and addressing model limitations
Stay current with advancements in LLMs, agentic frameworks, and machine learning research
Communicate technical concepts clearly to non-technical stakeholders through presentations, documentation, and client discussions
Write clean, maintainable, production-quality code following best practices for version control and documentation

Requirements

3–7+ years of experience in machine learning engineering or applied AI research
Graduate degree (M.S. or Ph.D.) in Computer Science, Machine Learning, or a related engineering field
Proven ability to translate research concepts into production-ready systems
Strong Python proficiency and experience with ML frameworks such as PyTorch, TensorFlow, LangChain, and Pydantic
Hands-on experience working with large language models and real-world applications
Familiarity with Linux environments, Git, and software engineering best practices
Strong communication skills with the ability to explain complex technical topics to diverse audiences
Must be legally eligible to work in Canada

Nice to have

Publication record in peer-reviewed conferences or journals related to LLMs, agentic frameworks, or reinforcement learning
Hands-on experience with agent frameworks such as LangGraph, Agenta, DSPy, or CrewAI
Knowledge of context engineering techniques and frameworks
Experience designing and deploying multi-agent systems
Background in HR tech, career services, or workforce development
Demonstrated project ownership and leadership experience

What we offer

3 weeks paid vacation
Health insurance & wellness coverage
Yearly Learning & Development Allowance
Yearly Workspace Allowance

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Machine Learning Engineer

Job Description

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