Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Turning machine learning research into production-ready software for AI-enabled radar and sensing systems, with an accent on real-time, maintainable ML implementations and scalable ML infrastructure. Focus on deploying and maintaining AI workloads across edge, near-edge, and cloud environments, including building AI agents and LLM-powered applications.

Location: Hybrid in Burlington, MA

Salary: $165,000 - $200,000

Company

hirify.global develops AI-enabled radar and sensing systems for real-world situational awareness.

What you will do

• Partner with Data Scientists to convert research algorithms into robust, production-quality software.
• Implement machine learning algorithms in high-performance C++ and Python with a focus on maintainability, scalability, and real-time performance.
• Build and improve ML infrastructure, tooling, and training pipelines to accelerate experimentation and model development.
• Design and implement AI agents, agentic workflows, and LLM-powered applications.
• Deploy and maintain AI workloads across edge, near-edge, and cloud environments.
• Collaborate across engineering and research teams to transition prototypes into production systems.

Requirements

• Work authorization: legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance.
• BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI, Robotics, or a related field.
• Strong hands-on programming experience in C++ and Python.
• 3-5 years of experience developing and deploying machine learning systems in production environments.
• Experience building AI agents, LLM-based applications, or intelligent automation systems.
• Excellent written and verbal communication and collaboration skills.

Culture & Benefits

• Hybrid work in Burlington, MA (not fully remote).
• Engineering-heavy ML role focused on productionizing algorithms and building ML infrastructure.
• Close collaboration with Data Scientists to bridge research and deployment.
• Compensation range of $165,000 - $200,000 based on experience level.