Vice President of Engineering, ML and Data

We’re looking for a Vice President of Engineering to lead our machine learning (ML) and data engineering teams. Reporting to the SVP of Technology, you will work closely with our engineering and product leaders to build innovative products, create technical product plans, and bring extensive leadership to help BenchSci scale.

We are welcoming applicants from Canada, the US, and the UK for this position.  

You Will:

– Manage definition, execution, and delivery of all technical goals in the areas of data and ML engineering

– Create alignment across ML and data engineering; prioritize and direct urgency and importance of high-value problems following our roadmap

– Partner with engineering leadership during quarterly and yearly planning meetings, advocating for strategies and objectives required to achieve key ML and data goals

– Be an external thought leader—taking part in customer-facing engagements and internal & external tech due diligence to inform key priorities and goals for the ML and data teams

– Be an internal technology promoter and take an active part in strategic decision-making

– Act as an expert in trends and best practices in ML and data to inspire innovation and adoption of the latest engineering practices

– Lead world-class teams of directors, managers, and engineers to support our growth and deliver key ML and data products

– Guide and foster growth by overseeing the organizational design structure for your teams

– Play an active role in supporting and improving our hiring practices, ensuring that we’re best positioned for our growth objectives

– Commit to advancing diversity, equity, and inclusion (DEI) in the engineering division of BenchSci

You Have:

– 8+ years of experience in a senior engineering management role at a Senior Director or VP level

– 10+ years of total experience leading large engineering teams (50+ members) across different functions and shipping data and/or software products at scale

– Deep knowledge and experience in DataOps, MLOps, modern data architecture, cloud-based data, ML tech stacks, and ML advancements

– Experience with architectural designs, technology exploration, and innovation management

– Proven track record building large-scale data platforms in a data-heavy, B2B environment

– Experience with building ML-based solutions and data pipelines for internal or commercial data products

– Demonstrated experience with managing priorities and implementing effective agile PDLC/SDLC practices at scale

– Ability to establish effective working partnerships across cross-functional teams in both technical and non-technical settings