Senior Engineering Manager, AI/Machine Learning

Posted:
8/13/2024, 5:41:01 AM

Location(s):
Foster City, California, United States ⋅ California, United States

Experience Level(s):
Senior

Field(s):
AI & Machine Learning

If you've used Disney+, Peacock, or other top streaming platforms, you've already benefited from Conviva's technology. We empower the world’s leading B2C companies, including the biggest names in streaming media, to deliver exceptional digital experiences and optimize the “moments that matter” to their customers and their business. As the global leader in experience-centric operational analytics, Conviva has redefined big data analytics with our paradigm-shifting Time-State Analytics model. Our platform does what legacy observability and monitoring tools can’t: we eliminate the gaps between system performance, user experience, and engagement, enabling issue identification, impact assessment, and root cause resolution in seconds. This isn’t just important, its game-changing! Our platform processes over 5 trillion daily events, providing real-time, cost-effective, stateful computation across diverse data sets. This empowers operations teams for the first time to precisely and directly impact real-world business outcomes, including customer satisfaction and revenue.

 

As a Senior Engineering Manager at Conviva, you will lead a team of talented data scientists and machine learning engineers and guide them in developing and implementing machine learning models and MLOps solutions. You will thrive in a fast-paced environment where you'll work closely with cross-functional teams to optimize the streaming experience for our customers and their viewers. Leveraging cutting-edge data science techniques, you will play a pivotal role in driving innovation and delivering impactful solutions in the rapidly evolving streaming media industry.

 

What Success Will Look Like: 

  • Lead and manage a high-performing team of data scientists and machine learning engineers in a fast-paced environment, providing technical guidance, mentorship, and support to drive their professional growth and development.
  • Oversee the rapid development and implementation of machine learning models, leveraging advanced algorithms and techniques to optimize the streaming experience for our customers and their viewers.
  • Drive real-time anomaly detection and root cause analysis initiatives at a swift pace, utilizing statistical and machine learning approaches to quickly identify and resolve issues in the streaming pipeline.
  • Collaborate closely with cross-functional teams, including product managers, software engineers, and data engineers, to deliver data-driven insights and recommendations that enhance the streaming experience in an agile environment.
  • Champion MLOps practices, ensuring the seamless deployment, monitoring, and management of machine learning models at scale within demanding timelines.
  • Stay at the forefront of industry trends, emerging technologies, and best practices in data science, machine learning and MLOps. Apply this knowledge to drive innovation, meet tight deadlines, and maintain a competitive edge.
  • Establish and maintain strong relationships with stakeholders, providing clear and concise communication of technical concepts and findings to both technical and non-technical audiences.

 

Who You Are & What You've Done: 

  • Master's or PhD in a quantitative field such as Data Science, Computer Science, Statistics, or a related discipline.
  • 8+ years of experience in data science, with a focus on machine learning.
  • Proven experience in leading and managing a team of data scientists, driving their professional growth and delivering impactful projects within tight deadlines.
  • Strong expertise in machine learning algorithms, statistical modeling, and data analysis techniques.
  • Solid understanding of real-time anomaly detection and root cause analysis methodologies, with a track record of successfully applying these techniques in a fast-paced environment.
  • Experience implementing MLOps practices, including model deployment, monitoring, and management, utilizing tools such as Kubernetes, Docker, or MLflow in time-sensitive projects.
  • Proficient in programming languages such as Python or R, with hands-on experience using machine learning libraries and frameworks.
  • Strong communication and collaboration skills, with the ability to effectively convey technical concepts to both technical and non-technical stakeholders in a fast-paced context.
  • Knowledge of the streaming media industry and a passion for leveraging data science to optimize the streaming experience in a high-pressure environment.

Preferred:

  • Familiar with common graph algorithms.
  • Experience with time series analysis.
  • Experience with Ad Tech or ID graph.

 

The expected salary range for this full-time position is $200,000 - $300,000 + equity + benefits. Compensation is determined by numerous factors such as your qualifications, experience, relevant education or training, and work location.

 

Underpinning the Conviva platform is a rich history of innovation. More than 60 patents represent award-winning technologies and standards, including first-of-its kind-innovations like Time-State analytics and AI-automated data modeling, that surface actionable insights. By understanding real-world human experiences and having the ability to act within seconds of observation, our customers can solve business-critical issues and focus on growing their business ahead of the competition. Examples of the brands Conviva has helped innovate, adapt, and scale at unprecedented speed include: DAZN, Disney+, HBO, Hulu, NBCUniversal, Paramount+, Peacock, Sky, Sling TV, Univision and Warner Bros Discovery. 

Privately held, Conviva is headquartered in Silicon Valley, California with offices and people around the globe. For more information, visit us at www.conviva.com. Join us to help extend our leadership position in big data streaming analytics to new audiences and markets! 

Conviva

Website: https://www.conviva.com/

Headquarter Location: Foster City, California, United States

Employee Count: 251-500

Year Founded: 2006

IPO Status: Private

Last Funding Type: Venture - Series Unknown

Industries: Advertising ⋅ Analytics ⋅ Information Technology ⋅ Marketing ⋅ Media and Entertainment ⋅ Social Media ⋅ Software ⋅ Video ⋅ Video Streaming