Machine Learning Engineer, II

Related keywords: remote job francenetwork engineer remote jobdata engineer remote job

This page contains product affiliate links.

Overview of the Position

Spotify is seeking a Machine Learning Engineer II to enhance music and podcast recommendations through effective personalization strategies within the Personalization team. This team plays a crucial role in making choices easier and more enjoyable for users by continuously improving some of Spotify’s most admired features like Blend and Discover Weekly.

About Spotify

Spotify is an industry leader in streaming services, focusing on delivering superior musical experiences through machine learning and recommendations. The company prides itself on innovation and providing tailored content to its users, often leading the industry in the deployment of cutting-edge technologies.

Key Responsibilities

In this role, you will be empowered to:

• Design and Build: Engage in designing, building, evaluating, shipping, and refining Spotify's personalization products with a hands-on approach to machine learning development.
• Collaborate: Work in a cross-functional agile team consisting of user researchers, designers, product managers, and engineers to create new product features aimed at connecting artists with fans.
• Prototype and Productionize: Develop and productionize innovative machine learning solutions at scale, suitable for hundreds of millions of users.
• Promote Best Practices: Act as a role model for ML systems development, involving critical aspects such as testing and evaluation, both within your team and across the organization.
• Collaborative Innovation: Join the larger network of machine learning practitioners throughout Europe and across Spotify to foster collaboration and innovation.

Required Skills

To qualify for this position, candidates should possess several key skills:

• Machine Learning Experience: A strong background in machine learning, particularly in real-world applications and the use of bandit algorithms, large language models (LLMs), and other techniques relevant to recommendation systems.
• Programming Proficiency: Experience in implementing production machine learning systems in programming languages like Java, Scala, or Python. Familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn is considered a strong advantage.
• Data Processing Skills: Some experience with large-scale distributed data processing tools such as Apache Beam, Apache Spark, or related technologies. Knowledge of cloud environments like GCP or AWS is also necessary.
• Agile Processes: A passion for agile software development, data-driven approaches, and a focus on reliability and disciplined experimentation is vital.
• Customer Focus: An enthusiasm for understanding customers’ needs and preferences, placing them at the pinnacle of development considerations.

Job Location

This position is fully remote within the European region, as long as the selected candidate is in a work location compatible with the GMT/CET time zone for collaborative purposes. However, please note that candidates from France are excluded due to specific on-call restrictions.

Why Apply?

Working as a Machine Learning Engineer II at Spotify offers an engaging challenge within a thriving, innovative environment. The role allows for the creation of personalized solutions that have a direct impact on millions of users’ listening experiences. Candidates can expect to be part of a forward-thinking team, dedicated to leveraging advanced technologies for customer satisfaction.

Salary Information

While specific salary figures have not been disclosed in this opportunity, professionals in the field of machine learning engineering typically enjoy competitive compensation, notably at a leading company like Spotify. Candidates should expect to negotiate a salary commensurate with their skills and experience.

Conclusion

Overall, the Machine Learning Engineer II position at Spotify presents a fantastic opportunity for individuals who are passionate about machine learning and personalized user experiences. The combination of an innovative work environment, a focus on cutting-edge technologies, and the chance to collaborate across various functions makes this position truly appealing for motivated candidates.

This job offer was originally published on himalayas.app