Engineering Manager, Affinity

• If you’re excited about this role, but your past experience doesn’t perfectly align with the qualifications above, we encourage you to apply anyways. You may be just the right candidate for this or other roles
• 8+ years in software engineering and machine learning roles, building and delivering scalable applications with large data volumes in cloud environments (AWS, Azure, or GCP), with focus on NLP and/or Computer Vision
• 3+ years in engineering management, providing formal mentorship and coaching
• Proven experience as an engineer bringing ML products to production or as an Applied Machine Learning Engineer
• Experience working with distributed systems at scale, consuming high volumes of data in batch or real-time for the purpose of building AI data sets
• Experience working with complex SaaS platforms
• Track record of managing technical roadmaps to improve platform performance, reliability, and drive toward a technical vision
• Demonstrated success mentoring junior engineers and advancing their careers
• Excellent communication skills with the ability to influence across functions
• Strong examples of collaborating with UX engineers, application developers, and product managers to influence roadmaps, UX decisions, and feature prioritization
• Passion for contributing ideas to continuously improve our product and company

Desirable

• As Engineering Manager for AI Platform, you'll lead and scale a team responsible for developing the foundations of AI features and services within Affinity
• This is a technical leadership role where you'll shape the technical roadmap, drive implementation end-to-end, and guide technology and architectural decisions alongside the team
• Your charter is to leverage data and AI techniques to derive actionable insights and enable delightful customer experiences
• You'll work with cutting-edge technologies, ship rapidly, and see direct impact on company revenue and growth. We're looking for an experienced Engineering Manager who excels at career development, mentorship, and scaling high-performing ML engineering teams
• Define the technical roadmap for AI feature delivery through cross-team collaboration, from ideation to production
• Own the full ML lifecycle: understanding the current landscape, feature engineering, model construction, deployment, observability, and evaluation
• Advance our approach to distributed systems and services architecture to improve agility, reduce complexity, and isolate logic across different languages
• Drive complex technical, architecture, design, and product discussions
• Lead, coach, and inspire a team that is building capabilities that are critical to customer and business success
• Run Agile processes including daily standups, sprint planning, demos, and retrospectives
• Scale the team by hiring talented engineers to deliver at high velocity and level up the technology
• Mentor engineers and accelerate their career growth
• Identify gaps and create processes that enables the team to be more efficient and drive their success
• Be an active contributor - you will have opportunities to be hands-on in the platform in order to support your team
• Own delivery of delightful, scalable and reliable capabilities through rapid development cycles
• Monitor quality and performance, answer customer questions, and identify patterns to propose root cause solutions
• Identify and measure the impact of the team’s work on customer outcomes