Lead Engineering Manager

This role is for one of the Weekday's clients

JobType: full-time

As a Lead Engineering Manager – Machine Learning, you will lead high-impact engineering teams responsible for building, scaling, and operating production-grade machine learning systems. This role blends deep technical leadership with people management, strategic execution, and cross-functional collaboration. You will work closely with product, data, and business stakeholders to translate complex problems into scalable ML-driven solutions while mentoring engineers and setting high standards for engineering excellence. This is a senior leadership role suited for someone passionate about applied machine learning, system design, and building strong engineering cultures.

Key Responsibilities

• Lead and manage multiple engineering teams delivering machine learning–powered products and platforms
• Own the end-to-end delivery of ML systems, from problem definition and architecture to deployment and monitoring
• Drive technical strategy and architectural decisions for scalable, reliable, and secure ML platforms
• Partner with product managers to define roadmaps, prioritize initiatives, and align engineering outcomes with business goals
• Oversee design and implementation of ML pipelines, including data ingestion, feature engineering, training, inference, and evaluation
• Ensure best practices for MLOps, CI/CD, model versioning, observability, and production reliability
• Review system designs, code, and ML approaches to maintain high quality and engineering rigor
• Guide teams in adopting modern ML frameworks, tools, and infrastructure
• Collaborate with data engineering, DevOps, and platform teams to enable efficient model deployment at scale
• Establish and track engineering KPIs related to delivery, quality, scalability, and system performance
• Proactively identify technical risks, bottlenecks, and scalability challenges, and drive mitigation plans
• Lead hiring, onboarding, and performance management of senior engineers and ML practitioners
• Foster a culture of ownership, innovation, collaboration, and continuous learning
• Mentor engineers and technical leads, supporting career growth and technical depth
• Represent engineering in cross-functional and leadership discussions, clearly communicating trade-offs and decisions

What Makes You a Great Fit

• Extensive experience in engineering leadership roles, managing and scaling high-performing technical teams
• Strong hands-on background in machine learning systems, applied ML, or data-driven product development
• Deep understanding of ML lifecycle concepts including data pipelines, training, evaluation, deployment, and monitoring
• Proven ability to design and scale distributed systems and ML platforms in production environments
• Experience balancing technical depth with people leadership and stakeholder management
• Strong architectural thinking with the ability to simplify complex problems into pragmatic solutions
• Excellent collaboration skills with product, data, and business teams
• Track record of delivering impactful ML-driven products at scale
• Comfortable making high-stakes technical and prioritization decisions in fast-paced environments
• Passion for mentoring engineers and building strong engineering culture
• Clear and confident communicator, able to influence across senior leadership and technical teams
• Results-driven mindset with a focus on long-term platform sustainability and business impact