Manager, Success Machine Learning Engineers - US (Remote)

February 7

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Developer-first MLOps platform.

deep learning • developer tools • machine learning • MLOps

51 - 200

💰 Corporate Round on 2022-05

Description

• Lead and manage a global team of senior machine learning engineers - including building hiring plans, career growth plans, individual and team-level coaching • Build processes and enablement content for the team so that they can effectively drive customer outcomes, either in the pre-sales specialization (i.e technical demonstration, prospect qualification, and proof of value execution), or post-sales specialization (i.e. customer onboarding, driving adoption and maximizing value for the customer, professional services etc.) • Be the voice of the customer, who are some of the most sophisticated ML engineers in the world, within W&B and influence product/R&D roadmap through aggregated product feedback collected by the team from different prospects and customers • Build a staffing model to support customer-facing requests as well as various cross-functional requests such as presenting in events, webinars, product marketing content generation, partnerships, delivering training etc. • Participate with other customer-facing teams to drive efficient forecasting of revenue indicators

Requirements

• 5+ years of relevant experience in machine learning engineering or a similar role. • 1-3 years of managing a team of machine learning engineers, data scientists or a similar role; Strong plus if the team was customer-facing • 2-3 years of experience in customer-facing roles such as solution engineers, consulting, sales engineering etc. or experience as an ML educator and/or conducting customer training sessions, product demos, and workshops at a SaaS company • Strong proficiency in Python and experience with TensorFlow/Keras, PyTorch Lightning, and other relevant ML packages. • Excellent communication and presentation skills, both written and verbal. • Experience with cloud platforms (AWS, GCP, Azure) and Linux/Unix. Strong Plus: • Proficiency with additional ML packages (HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, Ray). • Experience with MLOps and Cloud tools.

Benefits

• Flexible time off • Medical, Dental, and Vision for employees and Family Coverage • Remote first culture with in-office flexibility in San Francisco • Home office budget with a new high-powered laptop • Truly competitive salary and equity • 12 weeks of Parental leave (U.S. specific) • 401(k) (U.S. specific) Supplemental benefits may be available depending on your location Explore benefits by country