Senior Machine Learning Engineer, Artificial Intelligence; AI Work From Home

Senior Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home

As the Senior Machine Learning Engineer, you are an independent owner of critical Machine Learning (ML) subsystems in production. You take ambiguous problems, design practical solutions, and ship systems that operate reliably s is a hands-on, high-impact role focused on depth. This position is 100% Remote.

• – Build core Machine Learning (ML) systems that power a proactive, long-horizon Artificial Intelligence (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 Machine Learning (ML) engineers through example and technical judgment.
• – Work under real production constraints: latency, cost, reliability, and safety

• – Machine Learning (ML) models and systems in production consistently meet accuracy, latency, reliability, and efficiency targets.
• – Complex production issues are monitored, debugged, and resolved with minimal disruption.
• – Training, inference, and data pipelines are robust, scalable, and maintainable over time.
• – Drive measurable improvements in Machine Learning (ML) systems based on real-world signals and user feedback.
• – Provide mentorship and technical guidance to peers, raising the overall ML engineering standard.
• – Collaborate cross-functionally to ensure Machine Learning (ML) features integrate seamlessly into products and meet business goals.

• – Experience building and shipping Machine Learning (ML) systems used by real users.
• – Artificial Intelligence (AI) experience required.
• – Experience understanding how modern Machine Learning (ML) models behave and misbehave in production.
• – Experience writing strong, production-quality code and think in systems, not scripts.
• – Experience taking ownership, work independently, and push work across the finish line.
• – You learn fast, communicate clearly, and improve through iteration.
• – Tech Stack: GPU-based training and inference systems, JAX, Python, and PyTorch.

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.

Compensation: USD 170000 – USD 190000 – yearly