Senior Director Engineering, Machine Learning

About Highspot
Highspot is pioneering the category that is fundamentally changing the way companies increase sales productivity. On a mission to transform the way millions of people work with sales enablement, Highspot is committed to building breakthrough software with a spark of magic. We believe a great place to work is about more than the work -- it's about what the company stands for, and how it authentically represents its values in the real world. To this end, we have put intentional focus on creating equitable workspaces for each of our employees. Our goal is to create a culture where everyone feels a deep sense of belonging and is empowered to be an agent of change, with the ability to transform themselves, their workplace, and their world.

About the Role
We are looking for a Senior Director of Engineering to join our growing Machine Learning team. You will lead a team that works on challenging problems. As an ML Engineering Director, you will be responsible for building and scaling an ML team, managing the planning and prioritization of upcoming ML-related work, coordinating multiple engineering teams, and coaching team members. You will work with scientists, the leadership team, and product managers to evaluate priorities, spot potential problems before they occur, and support the team's technical roadmap with planned ML engineering investments. You are flexible, and supportive and know when to step in and work hands-on with your team and when to lean out and direct.

What You'll Do

• Coordinate with our data science team and product and engineering leadership to identify both the long-term and short-term needs of the ML learning work, especially in the areas of NLP, NN, and CV.
• Building and scaling the machine learning team
• Lead the team in bringing the ML models built by the data science team to production with high scalability, reliability, availability, performance, and cost efficiency.
• Lead the team in continuously improving existing ML models together with the data science team
• Lead the team in building data pipelines to support ML model training and serving
• Lead the team in building a labeling system for supervised model training
• Contribute to our org-wide product ideation in collaboration with other engineering leaders, engineers, researchers, product managers, and SMEs.
• Communicate complex concepts and the results of analyses in a clear and effective manner to technical and non-technical audiences.
• Collaborate with other team members and cross-functionally to share knowledge and discuss initiatives.

Who You Are

• 8+ years working as a professional software developer
• 4+ years working as an engineering manager
• 2+ years working in ML-related areas with a great understanding of machine learning design patterns and best practices and experience in shipping machine learning models into distributed, data-intensive production systems
• You can draw on substantial depth and breadth of management experience to lead and grow a machine learning team.
• You collaborate well with teams with different backgrounds/expertise/functions.
• You have expertise in full product lifecycle; technical designs, project planning, iterative implementation, and successful product launches.
• You care about data-driven development, reliability, and responsible experimentation.
• You understand the application of intermediate principles of data science (machine learning, statistics, computer science, mathematics) to solve technical problems.
• You have expertise in the ML Operations lifecycle; data acquisition, model training, and model deployment.
• You have experience and passion for mentoring and encouraging collaborative teams.
• You have experience in cultivating a strong engineering culture in an agile environment.

Your Background

• M.S. in Computer Science or related field or equivalent experience
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, documentation, and operations

BONUS POINTS FOR

• 2+ years of experience managing a machine learning team
• Knowledge of security and privacy
• Cloud Infrastructure: AWS, Kubernetes
• Building/maintaining large-scale production services
• Experience developing production ML models
• Background in ML/Stats theory