Production ML Engineer - Scale AI Pipelines for Defense

Automatic Systems, Inc.; Boston (MA); On-site; USD 170,000 - 300,000; Full time

Benefits offered by this job

Equity packages

Comprehensive benefits

Job summary

Automatic Systems, Inc. is a frontier AI company shaping critical infrastructure and defense assets. The role focuses on integrating machine learning models into scalable software pipelines and delivering production-ready systems for real-world optimization problems.

You will develop features using Python and ML tooling, leveraging Kubernetes, AWS, and MLOps practices. Collaboration across cross-functional teams and a commitment to robust, high-quality ML engineering are essential.

Qualifications

• Proficiency in Python and ML tooling (TensorFlow, PyTorch, scikit-learn)
• Experience deploying ML models in production
• Knowledge of data structures and algorithms
• Familiarity with ML systems and MLOps concepts

Responsibilities

• Design and deploy production-grade systems that integrate ML models into scalable pipelines.
• Develop and ship ML-powered features for optimization and prediction problems.
• Work with Kubernetes, AWS, and MLOps tooling to ensure robustness and performance at scale

Skills

Python

ML tooling

TensorFlow

PyTorch

scikit-learn

LangChain

Algorithms

Data structures

Tools

Kubernetes

AWS

Apache Beam

MLflow

Job description

Automatic Systems, Inc. is a frontier AI company shaping critical infrastructure and defense assets. The role focuses on integrating machine learning models into scalable software pipelines and delivering production-ready systems for real-world optimization problems.

You will develop features using Python and ML tooling, leveraging Kubernetes, AWS, and MLOps practices. Collaboration across cross-functional teams and a commitment to robust, high-quality ML engineering are essential.