Applied AI/ML Engineer

Atomscale; Boston (MA); On-site; USD 100,000 - 130,000; Full time

Job summary

A tech-focused company based in the US is seeking an Applied AI/ML Engineer to support the development and deployment of machine learning models for advanced materials processing. The ideal candidate will have strong skills in Python and deep learning frameworks, and will work closely with a passionate team to drive data-driven optimizations with atomic-scale precision. This role offers an exciting opportunity to contribute to transformative technology applications in the high-tech industry.

Qualifications

• Experience with Rust is a plus.
• Familiarity with scientific datasets is a plus, but not required.

Responsibilities

• Design, train, validate, and deploy machine learning models.
• Develop and maintain pipelines for model training and validation.
• Implement model validation and performance monitoring systems.
• Optimize models for accuracy and scalability.
• Build data ingestion and preprocessing pipelines.
• Collaborate to integrate features into platforms.
• Evaluate and apply state-of-the-art AI/ML techniques.

Skills

Python proficiency

Deep learning frameworks (PyTorch, JAX)

AI/ML operations frameworks

Containerization and orchestration (Docker)

Excellent communication skills

Education

PhD or MS in materials science, physics, or computer science

Job description

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 forefront 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.

To Apply

Email [e-mail] with "Applied AI/ML Engineer" in the title and following:

• Resume
• Brief overview of why you're a good fit
• LinkedIn profile
• Personal website, projects, GitHub, etc.

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