Engineering Manager, BenchSci

• 4+ years working as a professional developer
• 2+ years working as an engineering team manager
• Experience hiring and building motivated engineering teams
• Strong experience with Python and programming fundamentals
• Experience working with Data Solutions incorporating online and batch ML inference
• Experience with data engineering and machine learning design patterns and best practices
• Experience shipping machine learning into distributed, data-intensive production systems
• Strong cross-team communication and collaboration skills
• Worked on projects that have gone from proof-of-concept through multiple maintenance stages
• Experience working in a Cloud native environment (Azure, GCP or AWS)

Desirable

• We are looking for an Engineering Manager, Data and ML, to join our growing Data and ML team and report to the Director of Engineering, Data, and Machine Learning
• You will lead a team that works on challenging problems to impact the 41,000+ scientists worldwide who rely on BenchSci for their research
• As an Engineering Manager, you will be responsible for leading a team of talented engineers in the design, development, and deployment of cutting-edge data and machine learning solutions
• Your deep technical expertise and experience with event-driven data pipelines incorporating online inference will be crucial as you guide your team through the entire development lifecycle, from discovery and solution design to implementation and deployment
• You are passionate about mentoring and developing your team, fostering a high-performance culture, and aren't afraid to roll up your sleeves and contribute code when needed
• Ultimately, you will be accountable for the successful delivery of business objectives, ensuring your team's work directly contributes to the advancement of BenchSci's mission and the success of the scientists who rely on us
• Adaptability is key to success in this role, as change happens often, and you will need to navigate ambiguity
• Our ideal candidate is flexible and supportive, knowing when to step in and work hands-on with their team and when to lean out and direct