[Hiring] Senior Machine Learning Engineer @Indeed.com

Role Description

At Indeed, our mission is to help people get jobs. Every search and homepage visit runs a real-time auction that ranks sponsored and organic jobs for millions of jobseekers. A common ranking utility decides that order across Indeed and its partner surfaces.

As a Senior Machine Learning Engineer on the Utility team in Marketplace Efficiency, you will:

• Build the models and tools behind that utility.
• Work on dynamic filters that adapt to each request.
• Develop models for Multi-Armed Bandit or Utility algorithms.
• Build scalable, high-performance components that rank millions of jobs for millions of jobseekers in real time.
• Build and maintain request-level simulation tooling to replay production traffic and test ranking, utility, and filter changes offline before a live experiment.

On a daily basis, you will:

• Explore data to define problem statements.
• Build and tune models and algorithms.
• Write production code.
• Scale model, algorithms, and filter improvements to production.
• Run A/B experiments to measure their impact.
• Monitor performance.
• Conduct science research and run experiments to optimize outcomes for Employers, Job Seekers, and Marketplace.
• Collaborate with engineers, scientists, and product managers.
• Stay current with advances in the field.

Qualifications

• Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience.
• Prior success in deploying impactful Machine Learning solutions to large-scale production systems.
• Solid knowledge of data structures and algorithms.
• Exceptional sense of ownership.
• Excellent written and verbal communication in English, effective with technical audiences.
• Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.).
• Experience building simulation, offline evaluation, or counterfactual estimation tooling for ranking, recommendation, or advertising systems.
• Proficiency in Python and SQL for model development and large-scale data analysis.

Requirements

• Build highly scalable and performant recommendation systems and technologies that can identify optimum matches between millions of jobs and millions of job seekers in real-time.
• Experiment with Proof-Of-Concept Machine Learning (POC ML) model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology.
• Mentor other software engineers, data scientists, and Machine Learning Engineers in the team.
• Break down larger Machine Learning initiatives into pieces that deliver incremental business value and implement them.
• Represent Indeed at major Machine Learning conferences like Neural Information Processing Systems (NeurIPS), International Conference on Machine Learning (ICML), and International Conference on Learning Representations (ICLR).

Benefits

• Quarterly bonuses.
• Restricted Stock Units (RSUs).
• Paid Time Off policy.
• Region-specific benefits.