Head of Machine Learning in Haciendas del Canada, Nuevo León at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Head of Machine Learning based in Canada.

This is a senior engineering leadership role responsible for shaping and advancing machine learning initiatives across a high-growth technology environment. You will lead the development of ML-powered products that help businesses make smarter, more personalized customer engagement decisions. The role combines technical leadership, product strategy, team building, and hands-on influence over engineering standards. You will tackle complex challenges spanning personalization, recommendation systems, identity resolution, generative AI, and large-scale ML infrastructure. Working closely with engineering and product stakeholders, you will establish a strong technical vision while maintaining a pragmatic focus on business impact. This is an opportunity to build and scale an emerging ML function with significant ownership and long-term influence.

• Lead the technical vision, roadmap, and execution of machine learning products and initiatives, balancing ambitious innovation with pragmatic engineering decisions.

• Guide the development of ML-powered capabilities such as personalization, product recommendations, probabilistic identity resolution, and generative AI.

• Oversee the design and evolution of scalable machine learning infrastructure supporting model training and inference for large enterprise customers.

• Improve the team's pace of execution through strong technical leadership, effective prioritization, and removal of organizational or engineering obstacles.

• Establish and maintain high standards for reliability, operational excellence, incident management, and production readiness.

• Build and grow the machine learning organization by identifying hiring needs, designing effective evaluation processes, and attracting high-impact talent.

• Mentor engineers and managers, support career development, and foster a highly engaged, collaborative, and intellectually curious team culture.

• Partner with product and engineering leadership to identify high-value opportunities where machine learning can create meaningful customer and business impact.

• Significant experience leading engineering or machine learning teams, with a strong track record of delivering technically complex products or platforms.

• Deep expertise in machine learning and familiarity with areas such as recommendation systems, personalization, identity resolution, generative AI, or large-scale model infrastructure.

• Strong software engineering foundations and the ability to engage credibly in technical architecture, system design, and engineering trade-offs.

• Experience building and scaling reliable ML systems for production environments, including model training and inference infrastructure.

• Demonstrated ability to translate ambiguous or complex problems into clear technical strategies, product roadmaps, and measurable outcomes.

• Strong people leadership skills, including hiring, mentoring, performance management, and developing high-performing engineering teams.

• Excellent communication and collaboration skills, with the ability to work effectively across engineering, product, and other business functions.

• A pragmatic, impact-oriented mindset with the judgment to balance technical excellence, execution speed, reliability, and business priorities.

• Intellectual curiosity and enthusiasm for exploring emerging technologies, particularly advances in machine learning and large language models.

• Competitive annual salary range of $230,000–$400,000 USD, with compensation designed to be location-independent under a remote-first model.

• Meaningful equity compensation.

• Fully remote work environment across North America.

• Significant ownership and influence over the direction of machine learning initiatives and products.

• Opportunity to solve complex ML challenges involving personalization, recommendations, identity resolution, generative AI, and scalable infrastructure.

• Strong emphasis on professional growth, technical impact, and leadership development.

• Opportunity to build and scale a high-impact machine learning organization within a rapidly growing technology environment.