Machine Learning Engineering Manager

Company DescriptionHyperscience is transforming the future of work to elevate human potential. Our human-centered approach to automation enables a new era of human and machine collaboration that delivers dramatically improved organizational agility, without the legacy cost and burden of change management. By combining data, people, and processes into digital assembly lines, the Hyperscience Platform turns complex processes into simple, configurable workflows. Our industry-leading machine learning technology continuously learns and evolves, to involve humans only when needed. For more information, please visit www.hyperscience.com.
We are looking for a technical manager with a passion for working on business-facing automation products to lead our Application Machine Learning team. The ideal candidate will be able to leverage a strong ML background to bridge the gap between the latest ML technologies and customer needs. 
This is a crucial role in the engineering department, with a significant contribution to the company’s future. You will have a chance to work across the complete machine learning lifecycle, including data collection/generation, annotation, model building, training, testing, and releasing. While partnering with multiple product engineering teams, you will deliver a combination of end-to-end automation solutions and simple, reusable abstractions for complex machine learning tasks to back offices worldwide. 
We are looking for an engineering leader with a blend of technical and people skills. You will be expected to get into the technical details of projects within your team while also understanding how to work cross-functionally to deliver the maximum value to our end users.  

Responsibilities

• Manage and guide a large team of Machine Learning engineers helping to set priorities and tasks
• Plan and manage multiple projects to ensure successful delivery 
• Wrapping ML modules in reusable application components, which can be integrated into different configurations depending on the specific customer’s needs
• Leveraging your systems knowledge to deliver fast and scalable software, starting from the design of the system through development and extension
• Creatively solving problems even when the initial answer is unclear
• Actively participate in discussions and give ideas/guidance 
• Assessing where the optimization efforts should go in order to utilize better the ML components and know-how of the company

Qualifications

• 3+ years of industry experience using data-driven approaches to solve real-world problems through building an ML-related product from end-to-end, including data collection, modeling training, experiment, and release.
• 1+ year(s) leadership experience as an engineering manager or technical lead for a group of engineers or data scientists – coaching, road mapping, and project management.
• Expertise in machine learning for deep learning, and content understanding technologies, especially in NLP or CV-related areas.
• Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams.
• Well-developed software engineering fundamentals and the ability to write production code when needed.
• Good communication skills and the ability to understand and synthesize requirements across multiple project domains.
• Works effectively with cross-functional teams to build a trusted partnership.
• Able to perform applied research projects and bring them to production.
• Strong experience with one or more general-purpose languages (Java, C/C++, Python, etc).

Benefits & Perks:- Top-notch healthcare for you and your family- A pension match for up to 6% of your annual salary– Flexible PTO with the approval of your manager- 12 weeks of parental leave and an additional 4 weeks for birthing parents- Stock options
We are an equal opportunity employer. We welcome people of different backgrounds, experiences, abilities and perspectives. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.
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