Machine Learning Engineer

Nixtla is seeking a Machine Learning Engineer to improve our products. As an ML Engineer, you will work closely with the CTO to work on the architecture design for our ML products and services. You will work on setting good standards on critical design questions around dataset management, experiment tracking, and distributed training infrastructure. You will also develop and review model and application code and deploy state-of-the-art machine learning systems for time series. You should have a strong background in software engineering and machine learning. We work on research problems on a production timeline. You will succeed in this role if you enjoy setting up scalable training systems and infrastructure from scratch and shipping real-world products.

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Key Responsibilities

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• Contribute to the development and deployment of machine learning models to production environments
• Foster a culture of excellence in architecture, coding, and model development
• Monitor and maintain deployed models and data pipelines
• Continuously learn and stay up to date with the latest advancements in machine learning engineering

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What You Bring To The Team

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• Degree in Computer Science, Machine Learning, Data Science, or a related field.
• 3+ years experience as an ML engineer/researcher working with modern Machine Learning toolkits (Python stack, comfortable with PyTorch).
• 2+ years of experience building, scaling, and optimizing ML systems.
• Experience setting up ML ops workflows and infrastructure from scratch in a startup environment (ideally in Modal or Terraform on AWS and Azure).
• Production programming experience on a data-intensive project in distributed infrastructure.
• Experience writing high-performance, parallelized code.
• Very accustomed to agile software engineering processes, git flow, etc.
• Prior experience setting up GPU clusters (e.g. previously set up SLURM, or built multi-cloud model training pipelines with Infrastructure-as-Code).