Senior Machine Learning Engineer, DSP - job 1 of 2

As a Senior Machine Learning Engineer at Nexxen, your responsibilities will include developing high-performance services for programmatic integrations, driving AI innovations for real-time ad optimization, and designing robust algorithms for complex advertising challenges. You will work collaboratively with data scientists and other teams to build inventive solutions and enhance bidding efficiency, ensuring seamless troubleshooting of production issues.

To apply for the Senior Machine Learning Engineer position at Nexxen, candidates should have a Bachelor's degree in Computer Science or a related field, with over 5 years of experience in engineering roles at leading tech companies. Proficiency in AI/ML technologies, programming languages such as Java, Python, and Scala, and experience with large-scale NoSQL databases are essential for success in this position.

Nexxen seeks a Senior Machine Learning Engineer with strong expertise in programming languages, specifically Java, Python, and Scala. Proficiency in these languages is critical for developing effective machine learning models and data-driven applications in our fast-paced environment.

As a Senior Machine Learning Engineer at Nexxen, you can expect to engage in interdisciplinary collaborations with data scientists, engineering teams, product managers, and business stakeholders. This collaborative environment fosters creative problem-solving and innovation, allowing you to work on complex projects while learning from various perspectives.

Absolutely! The Senior Machine Learning Engineer role at Nexxen involves leveraging big data technologies. Candidates will work closely with large NoSQL databases, data processing tech stacks like Spark and MapReduce, and apply machine learning frameworks such as TensorFlow and PyTorch. This exposure enables you to handle and analyze vast amounts of data effectively.

When answering this question, reflect on specific algorithms you've implemented in past projects, especially those that relate to bid optimization or ad ranking. Discuss the results you achieved and how they positively impacted the advertising campaigns.

In your response, choose a project that showcases your problem-solving skills. Highlight the challenges faced, the approaches you took to overcome them, and the final outcome, emphasizing the importance of teamwork and collaboration.

Discuss strategies you employ to maintain model accuracy, such as ongoing training and validation, A/B testing, and the use of feedback loops from production data to iterate and refine models continuously.

Share your experience with data preprocessing, feature selection techniques, and any tools you've used to manage large datasets. Be sure to mention how you ensure data quality and integrity throughout the process.

Illustrate your innovative thinking by describing a situation where you created a novel solution to a problem, highlighting the technical aspects as well as the impact your innovation had on the project or product.

Mention factors such as model scalability, performance monitoring, data pipeline integrity, and the importance of collaboration with other teams to understand business requirements. Discuss deployment best practices you've followed.

Talk about the resources you utilize, such as research papers, online courses, webinars, and conferences in the AI and machine learning landscape. Mention your commitment to continuous learning and how it benefits your work.

Emphasize the importance of communication in bridging the gap between technical and non-technical stakeholders. Discuss how effective communication ensures alignment on project goals and successful implementations.

Address how you would first review model inputs and performance metrics, look into potential data quality issues, and consider revisiting model architecture or retraining approaches, illustrating your analytical mindset.

Share techniques for fostering collaboration, such as regular team meetings, leveraging tools for shared documentation and project tracking, and emphasizing a culture of constructive feedback and knowledge sharing.