Zendesk is looking for a motivated Machine Learning Science Manager to join our ML organization.

　　Zendesks people have one goal in mind: to make Customer Experience better. Our products help more than 125,000 global brands (AirBnb, Uber, JetBrains, Slack, among others) make their billions of customers happy, every day.

　　Our team is responsible for helping Customer Experience teams to achieve their best, by solving repetitive work, so they can shift their focus to solving more sophisticated problems. We use the latest trends in AI algorithms to help us on that mission, and we're passionate about empowering our customers.

　　As a Machine Learning Science Manager, you will be responsible for expanding and leading a distributed team of ML Scientists, fostering healthy relationships, collaboration and engagement, while supervising the development of AI capabilities. Your role will also involve mentoring and coaching team members, conducting performance evaluations, and finding opportunities for process improvements and innovation. Ultimately, your goal will be to ensure that your team delivers high-quality, scalable, and efficient machine learning solutions that drive business success.

　　What youll be doing

　　Lead the recruitment, health, engagement and development of your teams. You will have regular, open, action-orientated 1:1s with your reports and set goals that will bring them to the next level and further their careers.Manage a team of machine learning scientists to improve, design, develop, and deploy AI-enabled customer support features.Collaborate with other teams and other functional areas, including product management and engineering, to understand business requirements and translate them into technical solutions.Manage and help prioritize the teams work to ensure timely delivery of high-quality solutions that meet business requirements.Contribute to discussions on the technical roadmap by advocating for the quality of the ML solutionsEnsure the team has a deep understanding of the companys data architecture, data governance, and data management processes to ensure accurate and timely data access and availability applications.Develop and maintain in the team best practices for machine learning model exploration, development, testing, deployment and monitoring to ensure high reliability, scalability, and maintainability.Provide a culture of learning and growing while keeping in mind the Zendesk capabilities, by supporting some initiatives to be up to date with the literature and sharing knowledge internally.Support the incorporation in services of innovative machine learning models and algorithms, to continuously improve the effectiveness of AI features.Mentor and coach team members to develop their skills and capabilities in machine learning, data science, and software engineering.

　　What you bring to the role

　　Required experience:

　　Experience in leading machine learning teams to research and deliver technically exciting projectsSolid experience as a scientist researching and developing sound ML solutionsExperience or desire in building a team, managing its morale, developing hiring strategies and the career aspiration of the membersAbility to lead the discovery of solutions, leveraging the expertise of the team members and peers to look for the optimal path.Experience working with the team to distill complex/vague problems into a set of actionable steps.The energy and aim to move discussions/projects forward, exhibiting a balanced appetite for risks and the courage to make decisions.Good communication and interpersonal skills, being able to collaborate effectively with cross-functional teams.Good technical skills appropriate with the level of the role.Track record of coaching/mentoring individual contributors, as well as crafting a culture and team valuing diversity and inclusion.Familiarity with Agile methodologies and development practices.

　　Preferred requirements:

　　Experience with globally distributed teamsExperience working in the customer support or service industry.Experience leading complex ML projects and mentoring colleaguesExperience researching and developing ML methods in both academic and industry environmentsExperience with natural language processing (NLP) and speech recognition technologies.Experience with Machine Learning systems at scale

　　Our stack

　　Our codebase is mainly written in Python and Spark; in some cases we also write in Scala, Ruby, and Java.Our servers live in AWS.Our data is stored in S3, RDS MySQL, Redis, ElasticSearch, and Aurora.Our services are deployed to Kubernetes using Docker, and use Kafka for stream-processing

　　#LI-AK9

　　The intelligent heart of customer experience

　　Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love. We advocate for digital first customer experiences-and we stick with it in our workplace. Over 5,000 employees worldwide are collaborating from kitchen tables, home offices, coworking spaces, and Zendesk workspaces to make one team.

　　Zendesk is an equal opportunity employer, and were proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here.

　　Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to [email protected] with your specific accommodation request.