Lead Engineering Manager

Weekday AI•Washington, PA

About The Position

This role is for one of the Weekday's clients As a Lead Engineering Manager , you will play a critical role in shaping and scaling machine learning–driven products while leading high-performing engineering teams. This role blends deep technical expertise with strong people leadership, requiring you to set engineering vision, guide architectural decisions, and ensure the successful delivery of complex ML-powered systems. You will work closely with product, data, and business stakeholders to translate strategic goals into reliable, scalable, and impactful solutions. This is a full-time role based in the USA , offering the opportunity to influence technology direction at scale while mentoring and growing world-class engineering talent.

Requirements

10+ years of overall engineering experience, with significant time in engineering leadership roles
Proven experience managing and scaling teams working on machine learning or data-driven systems
Strong understanding of ML concepts such as model training, evaluation, deployment, and monitoring
Hands-on experience collaborating with data scientists on productionizing ML models
Solid background in system design, distributed systems, and cloud-native architectures
Experience with MLOps practices, including model versioning, pipelines, and automated retraining
Ability to balance technical depth with strategic thinking and people leadership
Strong communication skills, capable of engaging both technical and non-technical stakeholders
Track record of delivering complex projects in fast-paced, evolving environments
Experience driving engineering excellence through processes, standards, and continuous improvement
Comfortable making data-driven decisions while navigating ambiguity
Passion for building inclusive, high-trust engineering cultures that foster learning and ownership

Responsibilities

Lead and manage multiple engineering teams focused on machine learning platforms, services, and applications
Define technical vision, architecture, and best practices for ML systems in production
Partner with Product Managers to align engineering execution with business and customer needs
Oversee end-to-end delivery of ML solutions, from experimentation to deployment and monitoring
Drive adoption of modern engineering practices, including CI/CD, MLOps, testing, and observability
Review system designs and code to ensure scalability, reliability, performance, and security
Enable cross-functional collaboration between engineering, data science, infrastructure, and operations
Establish and track engineering metrics related to delivery, quality, and system health
Mentor senior engineers and managers, supporting career growth and technical excellence
Support hiring, onboarding, and team scaling initiatives to meet business growth
Identify and mitigate technical risks, ensuring long-term maintainability of systems
Champion innovation by evaluating and integrating new ML frameworks, tools, and methodologies