Engineering Manager, AI/Machine Learning

Key Skills

Aartificial intelligence, Data science techniques, Docker, Effective communication skills, Kubernetes-K8s, Leadership Skill, Machine learning techniques, MLflow, MLOps tools, Optimization, Python Programming, Teamwork

Job Description

Conviva is the only global streaming analytics platform for big data that collects, standardizes, and puts trillions of cross-screen, streaming data points in context, in real time. The Conviva platform provides comprehensive, continuous, census-level measurement through real-time, server side sessionization at unprecedented scale. If this sounds important, it is! We measure a global footprint of more than 500 million unique viewers in 180 countries watching 220 billion streams per year across 3 billion applications streaming on devices. With Conviva, customers get a unique level of actionability and scale from continuous streaming measurement insights and benchmarking across every stream, every screen, every second.

As an 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.

*Our hybrid work environment combines the benefits of both in-office collaboration and remote flexibility. You'll be based in our Foster City, CA office (or our New York office) and work three days a week alongside your team, with the remaining two days spent working from the location of your choice. 

What You Get to Do: 

• 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.

What You Bring to the Role:

• 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.