About Highspot
Highspot helps sales teams improve customer conversations and achieve their revenue goals. From content optimization and performance analytics to in-context training, guided selling, and more, the Highspot platform delivers enterprise-ready features in a modern design that sales reps and marketers love. Using Highspot, marketing leaders have deep insights and analytics into the performance and influenced revenue of content, campaigns, and marketing assets. What makes the solution special? It’s loved by sales reps globally, and is the #1 rated sales enablement platform on G2 Crowd.
We are committed to diversity as both a moral and business imperative.
About the Role
We are looking for a 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 a 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
Base salary range: $210,435 - $317,391 annually. Employees may also be eligible for bonuses, stock options, and other forms of compensation.
The above represents total expected compensation for this role. Actual compensation will depend on various job-related factors, including, but not limited to, location, experience, and job qualifications.
Highspot also offers the following employee benefits for this position:
-Comprehensive medical, dental, vision, disability, and life benefits
-Health Savings Account (HSA) with employer contribution
-401(k) Matching with immediate vesting on employer match
-Unlimited PTO
-8 paid holidays and 5 paid days for Annual Holiday Week
-Quarterly Recharge Fridays (paid days off for mental health recharge)
-18 weeks paid parental leave
-Professional development opportunities through BetterUp and LinkedIn Learning
-Discounted ClassPass membership
-Access to Coaches and Therapists through Modern Health
-2 volunteer days per year
-Commuting benefits
Equal Opportunity Statement
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of age, ancestry, citizenship, color, ethnicity, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or invisible disability status, political affiliation, veteran status, race, religion, or sexual orientation.
Did you read the requirements as a checklist and not tick every box? Don't rule yourself out! If this role resonates with you, hit the ‘apply’ button.
