Responsibilities
- Establish and uphold technical hiring standards for machine learning positions, lead technical evaluations, and make confident hiring decisions to elevate team capability.
- Conduct regular one-on-one meetings, deliver honest feedback at key points, and support professional development across all experience levels.
- Identify high performers and address performance issues promptly and directly, collaborating with HR and leadership when needed, and champion team members when appropriate.
- Maintain awareness of team member assignments, communicate evolving skills and preferences to staffing leads, and ensure placements offer meaningful growth opportunities.
- Assess client environments comprehensively, including infrastructure, data workflows, model lifecycle, and organizational maturity, to inform executive decisions and future engagements.
- Act as the lead technical decision-maker on projects, define architectural strategy, uphold quality standards, and resolve complex technical tradeoffs.
- Guide clients in building maintainable machine learning systems by simplifying MLOps, LLMOps, and monitoring practices into executable standards for engineering and leadership teams.
- Collaborate with sales and solutions teams during pre-sales to provide technical insight, accurately scope work, and build client confidence in delivery capabilities.
- Oversee technical execution from project start to finish, including solution design, problem resolution, and adherence to quality benchmarks.
- Serve as the primary technical point of contact for clients, responsible for architect-level outcomes, or act as the senior technical advisor overseeing team delivery.
- Coach engineers and architects through hands-on project work, support technical hiring efforts, and develop reusable architectures and tools to strengthen the broader practice.
Work Arrangement
Remote (Worldwide) — Canada, United States, Latin America
Team
Leads a team of ML engineers and architects; part of the AI/ML practice; reports to the Director of AI/ML
Other
- Up to 25% travel may be required based on business needs.
- Equipment and office stipend provided.
- Reimbursement for exams and certifications.
- Annual learning and development stipend.
- Individual professional development planning supported.
