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Scribd is the world's largest digital library, headquartered in San Francisco, California. With over 1 million titles, including books, audiobooks, and documents, Scribd serves millions of subscribers globally. The company has raised over $150 million in funding from investors like Y Combinator and ...
Scribd offers competitive salaries, equity options, flexible PTO, and a remote work policy that allows employees to work from anywhere....
Scribd fosters a culture of reading and learning, encouraging employees to explore new ideas and share their insights. The company values innovation a...
Scribd • San Francisco
Scribd is seeking an Engineering Manager for their ML/Data Engineering team to lead initiatives in content trust. You'll oversee engineering projects and collaborate with cross-functional teams. This role requires strong leadership skills and experience in data engineering.
You have a proven track record of leading engineering teams, with a focus on machine learning and data engineering. Your experience includes managing projects from conception to execution, ensuring that your team delivers high-quality results while fostering a collaborative environment. You understand the importance of data integrity and have a passion for building systems that enhance content trust. You are adept at navigating complex technical challenges and can communicate effectively with both technical and non-technical stakeholders.
You thrive in a culture that values GRIT — demonstrating passion and perseverance towards long-term goals. You believe in empowering your team members, encouraging them to take ownership of their work while providing guidance and support. You are committed to fostering diversity and inclusion within your team, recognizing that varied perspectives lead to innovative solutions.
Experience with machine learning frameworks and data engineering tools is a plus. Familiarity with agile methodologies and a strong understanding of software development best practices will help you excel in this role. You are open to continuous learning and are eager to stay updated with the latest industry trends and technologies.
As the Engineering Manager for ML/Data Engineering at Scribd, you will lead a team focused on enhancing content trust through innovative engineering solutions. You will be responsible for setting the technical direction of projects, ensuring alignment with the company's mission to democratize knowledge and empower collective expertise. You will collaborate closely with product managers, data scientists, and other engineering teams to define project scopes and deliverables.
You will oversee the development of data pipelines and machine learning models, ensuring they meet the highest standards of quality and performance. Your role will involve mentoring team members, conducting performance reviews, and facilitating professional development opportunities. You will also be responsible for fostering a culture of collaboration and continuous improvement within your team.
In addition to technical leadership, you will play a key role in strategic planning, helping to shape the future of Scribd's data initiatives. You will engage with stakeholders across the organization to understand their needs and translate them into actionable engineering projects. Your ability to balance technical expertise with strong interpersonal skills will be crucial in driving the success of your team.
Scribd offers a flexible work environment that prioritizes both individual needs and community connections. You will have the opportunity to work in a culture that values boldness and authenticity, where you can be yourself and contribute to meaningful projects. We encourage you to apply even if your experience doesn't match every requirement, as we believe in the potential of diverse backgrounds and perspectives.
Join us in building a world of stories and knowledge, where your contributions will have a direct impact on how people access and share information. We are committed to supporting your growth and development as a leader in the tech industry.
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