• Build core ML systems for a proactive AI product • Own work end-to-end: data preparation, training, evaluation, inference, and iteration • Turn research ideas into production systems • Debug model failures using production signals • Collaborate with research, product, and engineering teams • Mentor other ML engineers • Work under production constraints

• Build core ML systems that power a proactive, long-horizon AI product. • Own work end-to-end: data preparation, training, evaluation, inference, and iteration. • Turn research ideas into working systems that run reliably in production. • Debug model failures and system issues using real production signals. • Iterate quickly: ship, measure outcomes, refine, and repeat. • Collaborate closely with research, product, and engineering to deliver real user impact. • Mentor and review work from other ML engineers through example and technical judgment. • Work under real production constraints: latency, cost, reliability, and safety

• Build and improve ML components across data, training, evaluation, and inference. • Fine-tune and adapt models as part of larger production systems. • Implement evaluation and testing to understand model behavior. • Help build and maintain data pipelines for real-world and synthetic data. • Debug model issues, performance problems, and production incidents. • Ship improvements iteratively and learn from real user feedback. • Work closely with senior ML engineers and product teams. • Work under real production constraints: latency, cost, reliability, and safety.

• Build and improve ML components across data, training, evaluation, and inference. • Fine-tune and adapt models as part of larger production systems. • Implement evaluation and testing to understand model behavior. • Help build and maintain data pipelines for real-world and synthetic data. • Debug model issues, performance problems, and production incidents. • Ship improvements iteratively and learn from real user feedback. • Work closely with senior ML engineers and product teams. • Work under real production constraints: latency, cost, reliability, and safety