Machine Learning Engineer
Thrive Career Wellness Platform
- 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.
- 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.
- 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.
- Fast-paced, mission-driven startup environment with high ownership and autonomy.
- Collaborative, transparent culture where everyone’s voice matters.
- Opportunity to work on cutting-edge AI technologies with meaningful social impact.
- Cross-functional collaboration with Product, Engineering, and Customer Success teams.
- Strong career progression and mentorship opportunities as our AI team scales.
- 3 weeks paid vacation
- Health insurance & wellness coverage
- Yearly Learning & Development Allowance
- Yearly Workspace Allowance
