Applied AI/ML Engineer

Atomscale; Boston (MA); On-site; USD 140,000 - 230,000; Full time

Job summary

Atomscale seeks an Applied AI/ML Engineer to develop, deploy, and scale models for materials processing and characterization, bridging research and production with atomic-scale precision. You will build real-time predictive systems and data-processing pipelines to optimize manufacturing processes.

You will collaborate with materials scientists and process engineers to integrate features into the platform, driving innovation and maintaining production-grade reliability in a fast-paced

Qualifications

• Proficient in Python and deep learning frameworks (PyTorch, JAX, vLLM, Ray). Rust is a plus.
• Strong proficiency with AI/ML operations frameworks (Weights & Biases, MLflow, or similar).
• Familiar with modern containerization, orchestration, and version control tools (Docker, CI/CD, git).
• Excellent communication skills and ability to present technical information clearly.
• Understanding of scientific and industrial datasets (spectroscopy, microscopy, metrology, sensor data) is a plus.
• Advanced degree (PhD, MS) in materials science, physics, computer science, or related fields is a plus.

Responsibilities

• Model Development: Design, train, validate, and deploy ML models to extract real-time insights from materials data.
• Model Infrastructure: Build, deploy, and maintain pipelines for training, testing, validation, and versioning.
• Model Evaluation: Implement validation, drift detection, and performance monitoring in production.
• Model Optimization: Improve accuracy, scalability, interpretability, and low-latency inference for production.
• Data Engineering: Create robust ingestion and preprocessing pipelines for multimodal datasets.
• Collaboration: Work with scientists, process engineers, and product teams to integrate features.
• Research & Innovation: Apply state-of-the-art AI/ML techniques to materials science and automation.

Skills

Python

PyTorch

JAX

vLLM

Ray

Rust

Education

Advanced degree in relevant field

Tools

Docker

Git

CI/CD

Job description

Develop, deploy, and scale machine learning for materials processing and characterization, bridging research and production at atomic-scale precision.

About the Role

Atomscale builds intelligent systems for advanced materials synthesis enabling dynamic process control and breakthroughs in new materials.

We are seeking an Applied AI/ML Engineer to support the development, deployment, and scaling of models for materials processing and characterization data. Your work will bridge research and production, enabling real-time, data-driven optimization of manufacturing processes with atomic-scale precision, impacting some of the most important technology applications in the world.

Responsibilities

• Model Development. Design, train, validate, and deploy machine learning models to extract real-time insights from advanced materials characterization and process data.
• Model Infrastructure. Develop, deploy, and maintain pipelines for model training, testing, validation, and versioning.
• Model Evaluation. Implement systems for model validation, drift detection, and performance monitoring in production.
• Model Optimization. Optimize models for accuracy, scalability, interpretability, and low-latency inference in real-world production environments.
• Data Engineering. Build and optimize robust data ingestion and preprocessing pipelines for high-resolution multimodal datasets.
• Collaboration. Partner with materials scientists, process engineers, and product teams to integrate features into our platform and workflows.
• Research & Innovation. Identify, evaluate, and apply state-of-the-art AI/ML techniques relevant to materials science and process automation.

Qualifications

• Strong proficiency with Python and accompanying deep learning frameworks (e.g., PyTorch, JAX, vLLM, Ray). Experience with Rust is a plus.
• Strong proficiency with AI/ML operations frameworks (e.g., Weights & Biases, MLflow, or similar).
• Familiarity with modern containerization, orchestration, and version control tools (e.g., Docker, CI/CD, git).
• Excellent communication skills and ability to effectively present technical information.
• Understanding of scientific and industrial datasets (e.g., spectroscopy, microscopy, metrology, or sensor data) is a plus, but not required.
• Advanced degree (PhD, MS) in materials science, physics, computer science, or related technical fields is a plus, but not required.

You’ll Succeed If...

• You enjoy solving challenging problems and continuously improving models based on feedback and new data.
• You are excited to apply techniques at the frontier of high performance computing to foundational technical problems and complex engineering datasets.
• You're ready to get in at the ground floor with an efficient, focused, and highly technical team building for live production deployments today.

Bonus Points

• A track record of applying AI and ML to domains including semiconductor research or materials science.
• Prior experience in a startup or founding environment where you helped shape the direction of AI-powered products.
• Hands‑on experience working with thin‑film fabrication and process tools.

Why Join Atomscale?

• Help bring next-generation tools to the semiconductor and nanotechnology industries, redefining how innovation happens.
• Work on a mission‑critical product that will shape the future of high‑tech R&D and manufacturing.
• Collaborate closely with a small, passionate team, and make a direct impact from day one.

This position requires ongoing work authorization in the United States without employer sponsorship.