Senior Machine Learning Engineer

Location: Remote

Job Type: Full-time contractor

About Us:

At Archetype AI, we’re building the world’s first physical AI platform to bring artificial intelligence into the real world. Our foundation model, Newton, understands the physical world through objective sensor data and generates real-time insights into complex physical behaviors — from industrial machinery and systems to wearable devices and smart environments.

Formed by a high-caliber team from Google and backed by one of Silicon Valley’s most renowned venture funds, Archetype AI is in a pre-Series A phase and rapidly advancing its technology for the next big leap. This is a unique opportunity to join an exciting, fast-growing AI team based in the heart of Silicon Valley.

As a Senior Machine Learning Engineer, you’ll play a pivotal role in building and productizing the AI model and solutions at the heart of our platform — empowering developers to deploy next-gen sensor intelligence at scale.

Key Responsibilities

• Develop and optimize advanced ML models for time-series and multi-modal sensor data, applying state-of-the-art techniques in deep learning and foundation models.
• Develop scalable ML pipelines to apply our core foundation model across a range of real-world use cases and sensor modalities.
• Productize research models, transforming experimental prototypes into efficient, reliable, and maintainable deployment-ready code.
• Build robust evaluation pipelines to benchmark and monitor model performance across diverse datasets and applications.
• Deliver custom AI solutions using our platform, adapting and fine-tuning ML pipelines to meet specific customer requirements.
• Contribute to core platform and product specifications, helping define the tools, features, and requirements for stable, scalable AI deployment.

Qualifications

• 5+ years of experience in machine learning or applied AI, with a strong track record of delivering real-world solutions — particularly with time series or sensor data.
• Deep understanding of modern ML architectures, including foundation models, transformers, self-supervised learning, and multi-modal approaches.
• Proficient in Python and ML frameworks such as PyTorch or TensorFlow.
• Strong software engineering skills; able to write clean, modular, production-quality code.
• Passion for building and refining AI products that deliver tangible value to developers and end users.
• Comfortable working in a remote, asynchronous environment with a fast-paced, multidisciplinary team.
• Strong written and verbal communication skills.

Preferred Qualifications

• Experience with distributed or cloud-scale AI infrastructure (e.g. AWS, GCP, Azure, or Kubernetes clusters).
• Familiarity with AI/ML workflows for large-scale datasets, including data versioning, model lifecycle management, and MLOps best practices.