Machine Learning Architect - Systems Integrator
Hamilton Barnes Voir toutes les offres
- Canada
- Permanent
- Temps-plein
- Apply deep expertise in machine learning and applied AI to develop practical solutions that address real customer challenges
- Explore emerging technologies and approaches, building early-stage systems that demonstrate clear business value
- Lead technical direction across teams while remaining hands-on in applied research and innovation
- Continuously evaluate the evolving AI landscape, identifying opportunities to leverage new tools and techniques for product advancement
- Translate complex ideas into scalable, high-impact solutions that drive product differentiation
- Guide key technical decisions and contribute to shaping future product capabilities
- Collaborate closely with product and engineering teams to ensure solutions are aligned with real-world requirements and scalable to enterprise-grade systems
- Balance innovation with practicality, maintaining a strong focus on delivering customer value
- Mentor team members and promote a culture of rigorous, outcome-driven innovation
- PhD in Computer Science, Machine Learning, Artificial Intelligence, Operations Research, or a related field.
- Extensive experience applying machine learning to solve complex real-world problems, with a track record of developing novel approaches or adapting emerging techniques in practical settings.
- Strong hands-on experience building prototypes, proof-of-concepts, and early systems that demonstrate the value of new ML and AI methods.
- Deep expertise in modern AI techniques, with strong familiarity in areas such as agentic systems, LLMs, RAG, recommendation, optimization, explainability, and broader language-based AI techniques.
- Strong technical judgment and the ability to assess new technologies critically, separating durable opportunities from short-term hype.
- Ability to influence technical direction across teams through expertise, credibility, and collaboration.
- Strong programming ability in Python and experience working with modern ML and data tooling.
- Experience partnering closely with engineering and product teams to move promising ideas toward scalable product capabilities.
- Excellent communication skills, with the ability to engage technical and non-technical stakeholders and bring clarity to complex problems.
- Practical, product-minded approach to innovation, with an appreciation for enterprise software quality, maintainability, and customer impact.
- Strong mathematical foundation in areas such as probability, statistics, linear algebra, optimization, or stochastic methods.
- Experience with learning from human feedback and designing AI systems that incorporate feedback, oversight, or interaction into how they adapt and improve.
- Track record of developing intellectual property through patents, publications, inventions, or other differentiated technical contributions.
- Experience turning ambiguous customer or product problems into research directions, prototypes, and validated solution concepts.
- Familiarity with enterprise SaaS products and the considerations involved in bringing AI capabilities into production environments at scale.
- Flexible vacation
- Flexible work options
- Physical and mental well-being programs
- Regularly scheduled virtual fitness classes
- Mentorship programs, training, and career development
- Recognition programs and referral rewards
- Hackathons
- Competitive salary based on experience and qualifications.