Staff Machine Learning Engineer, Home Surfaces

The Staff Machine Learning Engineer will shape personalized content discovery by developing advanced recommendation systems that help millions of listeners find relevant podcasts and episodes. This role sits at the intersection of machine learning, large language models, personalization, and large-scale production infrastructure. You will lead the development and optimization of models powering prominent digital experiences, including personalized home feeds and AI-driven discovery features. Working closely with product managers, engineers, data scientists, and designers, you will translate research into reliable, scalable solutions. You will influence technical strategy, drive experimentation, and improve recommendation quality, system performance, and cost efficiency. This is an opportunity to solve complex machine learning challenges while mentoring engineers and shaping the future of personalized user experiences.

• Extensive experience developing, deploying, and operating machine learning systems in production environments.

• Deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms.

• Strong proficiency in Python and hands-on experience building machine learning solutions using PyTorch.

• Practical experience training, fine-tuning, evaluating, and optimizing large language models, including techniques such as SFT, distillation, and LoRA.

• Understanding of large-scale model inference, including latency management, reliability, scalability, and cost optimization.

• Experience designing, implementing, and interpreting online experiments and A/B tests to measure impact and improve user experiences.

• Experience operating distributed machine learning workloads using frameworks such as Ray, FSDP, HSDP, or comparable technologies.

• Experience building and maintaining data pipelines and workflow orchestration systems using tools such as Flyte, Airflow, BigQuery, and cloud-based storage platforms.

• Strong technical judgment and the ability to influence architecture and engineering decisions beyond your immediate team.

• Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.

• A user-focused mindset and a commitment to applying machine learning thoughtfully to improve content discovery and engagement.

• Location and collaboration: Must be based in a North American region where the employer has an established work location, with availability to collaborate within Eastern Time working hours.