Machine Learning Engineer

Air space Intelligence, 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

Compensation

$170K – $300K ASI is dedicated to maintaining fair and equitable compensation practices. The salary range provided for this role reflects the minimum and maximum cash compensation targets for candidates across all U.S. locations and levels of expertise/experience. Additionally, all employees receive generous equity packages and have access to a comprehensive benefits offering. Actual compensation packages are determined based on relevant skills, experience, education and training. For more information, connect with the recruiting team or Hiring Manager during the process as they can provide more detailed information about the salary range based on the applicant’s position level and location within the overall range.

About

ASI is the frontier AI company that dynamically orchestrates critical infrastructure and defense assets, across air traffic control, energy, logistics, and combat operations. ASI's systems simulate physical operations, hours, days, and weeks ahead, so the people running air traffic control, the electric grid, and military operations can catch problems early and act before they spread. ASI is powering vital infrastructure for customers like United Airlines, National Grid, the Federal Aviation Administration, Delta Air Lines and the Department of War. ASI is headquartered in Boston with offices in Washington, DC, Denver, and Europe, and is backed by leading investors, including Andreessen Horowitz, Citadel Securities, and Spark Capital.

What You Will Do

As part of our Defense engineering team, you will design and deploy production‑grade systems that integrate machine learning models into scalable software pipelines. You’ll develop and ship features that leverage ML to solve real‑world optimization and prediction problems, working with modern infrastructure like Kubernetes, AWS, and MLOps tooling. You’ll approach problems with a software engineer’s mindset—prioritizing robustness, maintainability, and performance at scale.

What We Value

• Proficiency in Python and experience with production ML tooling and frameworks (e.g., TensorFlow, PyTorch, scikit‑learn).
• Experience using LLMs in production environments — covering prompt engineering, fine‑tuning, RAG systems, and frameworks like LangChain
• Strong understanding of data structures, algorithms, and software engineering best practices.
• Familiarity with classical ML, deep learning with emphasis on transformer architectures, and MLOps concepts.
• Experience building and maintaining scalable, reliable production ML systems with robust data pipelines, including expertise with Apache Beam, MLflow, and similar production‑grade tools.
• Commitment to high‑quality ML engineering practices, including data versioning, experiment tracking, model governance, and automated testing pipelines.
• A bias for simplicity and clarity in solving complex problems.
• Intellectual curiosity and willingness to collaborate.
• Clear communication and collaboration across cross‑functional teams.

How We Hire

We look at the interview process not as screening test but rather as an opportunity to simulate what it would look like working together. We build the interview process around you.

Eligibility

ASI works with export controlled technology and restricted U.S. Government data, including on contracts mandating U.S. immigration status and location restrictions for performing personnel. Employment offers are contingent on ability to timely obtain all required authorizations for contemplated job duties.