Director – Machine Learning Engineering

Director – Machine Learning Engineering

Requirements

• M.S or B.S.in a Computer Science/Statistics/Data Science or related field
• 10+ years of building ML products with for both consumer and enterprise applications, preferably within identity resolution and/or AdTech
• 4+ years of managing high-performing teams
• Proven leadership skills, such as aligning complex technical decisions across teams, mentoring, coordinating cross-functional relationships with non-technical stakeholders, managing expectations, and navigating competing priorities
• Excellent written and verbal communication skills, with the ability to effectively advocate technical solutions to business audiences
• Self-motivated, growth-oriented, and driven to pursue excellence across teams
• Technical knowledge of Data Clean Rooms, AdTech, and data licensing vendors, such as Experian, TransUnion, LiveRamp, Merkle
• Deep understanding of statistics and ML and AI fundamentals
• Deep knowledge in multiple ML methodologies, such as XGBoost, Probabilistic Graphical Models, Foundation Models, Multi-Armed Bandits, Reinforcement Learning
• Expert proficiency with ML-frameworks such as TensorFlow, PyTorch, JAX, Scikit-learn etc.
• Production experience implementing, maintaining, and improving machine learning pipelines and models at scale in Python, Java, Scala, or similar languages

Responsibilities

• Develop and communicate a robust technical vision and strategy for identity resolution, matching & linking, and lookalike modeling for ad sales, marketing, and product
• Define and track key performance indicators to measure product and technical success for Identity Resolution and Customer 360
• Work cross-functionally with product management, engineering, and business stakeholders
• Research and build high-impact end-to-end machine learning systems
• Coordinate the work of data scientists and machine learning engineers providing research guidance and mentorship
• Promote and role-model best practices of data science, engineering, and communication throughout the organization
• Mentor engineers and data scientists across the org
• Navigate existing ML and AI research on Identity and apply it to solve business problems
• Contribute back to research community by writing/publishing blogs, articles or papers in conferences

Preferred Qualifications

No preferred qualifications provided.