Head of AI and Machine Learning Engineering

gusto; Deutschland; Hybrid; EUR 237.000 - 301.000; Vollzeit

Benefits dieser Stelle

Equity participation

Hybrid work schedule

Zusammenfassung

gusto seeks a senior executive to lead AI and machine learning engineering, shaping a unified strategy across classical ML and generative AI. The role blends deep technical credibility with executive influence to turn AI into a durable business advantage.

You will lead an international team across ML engineering, risk data science, and AI researchers, align AI initiatives with product goals, and drive scalable, safe, production-ready AI systems at scale.

Qualifikationen

• 10+ years leading ML/AI teams and delivering customer-facing software.
• Deep technical expertise across AI/ML systems including classical ML, generative AI and LLMs.
• Strong software engineering and systems background covering data, retrieval, evaluation, deployment, monitoring, and lifecycle management.

Aufgaben

• Lead, manage, and develop a broad AI/ML organization spanning ML Engineering, ML Platform, Risk Data Science, and AI Scientists.
• Define and execute a unified AI/ML systems strategy that unifies classical ML, generative AI, risk modeling, and platform capabilities.
• Partner with senior leaders across Product, Engineering, Design, Data, Risk, Legal, Security, and business teams to identify AI-driven customer value.
• Translate business problems into end-to-end AI/ML systems with clear standards for evaluation, monitoring, observability, reliability, safety, governance, and maintainability.
• Mature AI/ML platform capabilities, tooling, guardrails, and deployment patterns to empower product and engineering teams safely and autonomously.
• Drive disciplined technical and business judgment around AI/ML investments, including build vs. buy decisions.

Kenntnisse

Executive leadership

ML systems

Generative AI

Risk modeling

Production deployment

Ausbildung

Advanced degree in CS or related field

Tools

Python

ML platforms

Data pipelines

Observability tools

Jobbeschreibung

Role overview

A senior executive position leading AI and machine learning engineering for a company whose products touch critical workflows for businesses. The role unifies classical ML and generative AI into a coherent technical strategy while maturing platform capabilities. It calls for someone who combines deep engineering credibility with executive influence to make AI a durable advantage.

Responsibilities

• Lead, manage, and develop a broad AI/ML organization spanning Machine Learning Engineering, ML Platform, Risk Data Science, and AI Scientists, fostering a culture of technical excellence and customer impact.
• Define and execute a unified AI/ML systems strategy that brings together classical ML, generative AI, risk modeling, and platform capabilities in support of broader product and business goals.
• Partner with senior leaders across Product, Engineering, Design, Data, Risk, Legal, Security, and business teams to identify where AI can create meaningful customer value and operational leverage.
• Translate business problems into end-to-end AI/ML systems with clear standards for evaluation, monitoring, observability, reliability, safety, governance, and long-term maintainability.
• Mature AI/ML platform capabilities, tooling, primitives, guardrails, and deployment patterns that make it easier for product and engineering teams to build and operate AI/ML systems safely and with greater autonomy.
• Drive disciplined technical and business judgment around AI/ML investments, including where to build, where to leverage existing capabilities, and where to avoid unnecessary complexity.

Requirements

• 10+ years of experience leading teams in applied machine learning, AI, engineering, or data science roles, with a track record of delivering impactful customer-facing software.
• Deep technical expertise across AI/ML systems, including classical ML, generative AI and LLMs, statistical modeling, risk modeling, and production-scale deployment.
• Strong software engineering and systems background covering data, retrieval, evaluation, deployment, routing, monitoring, observability, feedback loops, and lifecycle management.
• Experience scaling high-performing technical organizations across ML Engineers, AI/ML Platform teams, Risk Data Scientists, and AI Scientists.
• Experience evolving ML teams toward a stronger software engineering and systems orientation with clear ownership for production AI/ML systems.
• Executive-level strategic judgment with the ability to shape company-wide AI/ML priorities and influence senior stakeholders.

Nice to have

• Advanced degree in computer science, machine learning, statistics, or a related field, paired with demonstrated systems leadership and executive-level impact.

Benefits and work setup

• Cash compensation is targeted at roughly $275,000–$305,000 in most remote locations and $320,000–$350,000 in major metropolitan hubs, with final offers determined by experience and expertise.
• Hybrid expectation of approximately 2–3 days per week in a physical office for employees based near an office location.
• Secure, reliable, and consistent internet connection required for remote work days.
• Full-time employees receive competitive base pay, benefits, and equity participation, with offer amounts determined by role, level, and location.