Lead ML Engineer - Production-Grade, Remote

Next Step Systems; United States; Remoto; USD 140.000 - 230.000; Tempo pieno

Vantaggi offerti da questo lavoro

Medical insurance

Dental insurance

Vision insurance

Savings plan

PTO

Remote work

Descrizione del lavoro

Next Step Systems is seeking an experienced ML engineer to own and scale the end-to-end ML platforms powering our products, from data ingestion and training to evaluation, inference and deployment. You will build and evolve training and fine-tuning pipelines for large models, and architect high-performance inference systems that optimize latency, GPU utilization, memory and cost.

This fully remote role offers the chance to work on cutting-edge ML infrastructure and production-grade systems

Competenze

• ML experience required, including building and shipping production ML systems.
• Strong understanding of large-model training, fine-tuning, evaluation, and inference.
• Strong software engineering and systems fundamentals, with experience operating GPU-based ML workloads at meaningful scale.
• Fully remote work environment.
• Opportunity to work on cutting-edge ML infrastructure and large models.

Mansioni

• Own end-to-end ML systems powering the company, from data and training to evaluation, inference, and deployment.
• Build and evolve training and fine-tuning pipelines for large models.
• Architect high-performance inference systems, optimizing latency, GPU utilization, memory, cost, and reliability.

Conoscenze

ML experience

Production ML

Software engineering

GPU workloads

Large models

Fine-tuning

Inference

Descrizione del lavoro

Next Step Systems is seeking an experienced ML engineer to own and scale the end-to-end ML platforms powering our products, from data ingestion and training to evaluation, inference and deployment. You will build and evolve training and fine-tuning pipelines for large models, and architect high-performance inference systems that optimize latency, GPU utilization, memory and cost.

This fully remote role offers the chance to work on cutting-edge ML infrastructure and production-grade systems