Staff Product Software Engineer (ML)

As a Lead Machine Learning Engineer, you will play a leading role in shaping the technical direction of the NewsML platform. You will drive infrastructure for scalable learning, inference, and monitoring, conduct in-depth data exploration and analysis, and collaborate across product, data, and engineering teams to power exceptional, personalized guest experiences. Your work will directly support strategic initiatives to help shape the roadmap for algorithmic innovation while ensuring that solutions are scalable, impactful, and aligned with stakeholder needs.

The core responsibilities for the job include the following:

80% of Time:

• Own complex technical initiatives end-to-end, from technical design through production deployment and operational excellence.
• Design and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries.
• Drive data and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, auto-generated tagging solutions, and RAGs.
• Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions.
• Strategically prioritize initiatives and technical workstreams to deliver the highest-impact and most time-sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution.

20% of Time:

• Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response.
• Mentor and coach engineers, fostering a culture of ownership, collaboration, and continuous improvement.
• Contribute to technical documentation and promote knowledge sharing across teams.

Requirements:

• Bachelor's degree in computer science, information systems, statistics, math, or a comparable field of study, and/or equivalent work experience.
• 8+ years of experience building and operating ML engineering systems in production environments.
• Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems.
• Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training, and low-latency online serving.
• Experience designing and developing backend microservices for large-scale distributed systems using REST.
• Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize).
• Familiarity with developing and deploying Spark and ML pipelines.
• Hands-on experience with big data technologies such as Databricks, Kinesis, and Kafka.
• Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals.
• Experience with observability tools for metrics, logging, and monitoring such as Datadog.
• Experience working in Agile/Scrum development environments.
• Excellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment.