About the role
The Company
They are a technology-driven organisation that leverages machine learning to solve complex, large-scale commercial challenges. Their teams operate in an environment where experimentation is encouraged, data drives decision-making, and technical expertise is highly valued. They invest heavily in innovation, giving teams the autonomy to explore new approaches while maintaining a strong focus on delivering measurable impact. Collaboration, continuous learning, and technical excellence sit at the heart of their culture.
The Role
You will lead a team of Machine Learning Engineers and Applied Scientists, helping to define priorities, guide experimentation, and ensure successful delivery of machine learning initiatives.
Responsibilities include:
- Lead, mentor, and develop a high-performing machine learning team, supporting both technical and career growth.
- Foster a collaborative and inclusive environment across a distributed organisation.
- Partner with technical leads to evaluate, prioritise, and resource machine learning initiatives.
- Oversee a portfolio of experiments, ensuring decisions are driven by evidence and measurable outcomes.
- Balance short-term delivery objectives with longer-term research and innovation opportunities.
- Establish robust evaluation frameworks to ensure model improvements translate effectively into production environments.
- Work closely with business stakeholders to align machine learning initiatives with strategic objectives.
- Collaborate with engineering and platform teams to support scalable ML infrastructure and tooling.
- Present technical findings, performance improvements, and strategic recommendations to senior leadership.
Your Skills & Experience
- Strong commercial experience in machine learning, data science, or ML-focused software engineering.
- Proven people leadership experience with responsibility for coaching, performance development, and team growth.
- Deep expertise in either machine learning engineering or applied statistics, alongside strong practical knowledge of the other discipline.
- Ability to operate effectively in environments with ambiguity and evolving priorities.
- Strong understanding of experimentation frameworks, model evaluation, and production ML systems.
- Experience making data-driven decisions and adapting strategy based on evidence.
- Excellent written and verbal communication skills, with the ability to engage both technical and non-technical audiences.
- Passion for building high-quality, reproducible, and reliable machine learning solutions.
What They Offer
- Performance-based bonus and comprehensive benefits package.
- Hybrid working environment in New York.
- Significant ownership and autonomy within a highly technical team.
- Clear opportunities for leadership development and career progression.
- Exposure to cutting-edge machine learning challenges at scale.
- Collaborative, learning-focused culture with strong executive support for innovation.
How to Apply
If you're an experienced ML Engineering Manager looking to lead high-impact machine learning initiatives and shape the direction of a growing AI function, apply today to learn more.
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