A/AI Machine Learning Engineering

About the Role

Responsible for developing, integrating, and deploying autonomy and artificial intelligence algorithms for mission systems. Supports the technology development life cycle from requirements generation through development, integration, and testing.

Key Responsibilities

• Develops, integrates, and implements algorithms for perception, motion/mission planning, and controls in LM products and platforms.
• Translates requirements and applies them to development code, integrating autonomy, AI, or machine learning algorithms.
• Determines software methods to best acquire and execute knowledge.
• Implements algorithms into software to train systems to recognize patterns and perform specific functions.
• Manages various phases of developing and maintaining autonomy software: requirements generation, software design and development, integration, testing, troubleshooting, debugging, and implementation.
• Reviews test outcomes, conducts troubleshooting, and debugs issues.
• Develops human-machine interface scenarios and breaks missions into tasks.
• Documents interface requirements and implements human-machine interfaces.

Requirements & Tech Stack

• Python
• AI Frameworks
• Project Management experience with software development
• Git workflow experience (branching, pull-requests, code reviews)
• Familiarity with CI/CD pipelines for automated testing and deployment of automation assets.

Desired Skills

• Experience designing, developing, testing, and deploying agentic automations.
• RPA Platforms: Proven experience with Blue Prism or an equivalent RPA tool such as UiPath (designing, debugging, and deploying bots in a production environment).
• Python Automation Stack:
• Proficiency with agentic frameworks: LangChain, LangGraph.
• Ability to orchestrate LLM-driven workflows.
• Hands-on with open-source RPA libraries: Playwright (web automation) and pywinauto (desktop UI automation).
• Hands-on experience with graph database libraries: Neo4J, Ontop, OrientDB, or similar.
• OpenCode / Clinerule Automation: Ability to leverage OpenCode (or Clinerule) to rapidly prototype and build agentic automations, including writing custom skills, prompt engineering, and integrating LLM outputs into process flows.
• Business Process Expertise: Skilled at process mapping (e.g., BPMN, flowcharts), analyzing end-to-end workflows, and translating business requirements into repeatable, scalable automation solutions.
• Communication & Relationship Building: Excellent written and verbal communication; capable of documenting technical solutions clearly and building rapport with business stakeholders and customers.
• Project Management: Experience managing automation projects end-to-end: scoping, estimating effort, tracking milestones, risk mitigation, and delivering on schedule.
• Ontology Engineering: Experience with ontology design, development, and management using tools like Protege for ontology modeling and Ontop for ontology-based data access (OBDA).

Qualifications

• Bachelor’s degree in Engineering, Computer Science, Information Systems, or a related field or equivalent professional experience.
• Excellent written and verbal skills.