AI Machine Learning Engineer Staff

Lockheed Martin•Orlando, CT

2d•Remote

About The Position

The Lockheed Martin Global Sustainment Information Systems and Innovation organization is seeking a high energy professional with a strong background in software engineering, artificial intelligence and machine learning to support the AI team and product portfolio, focusing on a broad range of projects across the corporation. The team is focused on exploiting small, innovative and agile teams to rapidly iterate and mature solutions from prototypes to deployment for utilization across the Lockheed Martin enterprise and in the field for our customers. The selected candidate will focus on the development of technologies and products that leverage Artificial Intelligence to provide discriminating capability to our internal teams, organizations, business areas, and overall customers. This will require engagement in every phase of the system development lifecycle including requirements generation, system and software design, development, implementation, integration, and deployment. Activities will range from low TRL research, proof of concepts, development of prototypes, building demonstrators, and transition to production. The selected candidate can expect to utilize current AI paradigms including computer vision, deep learning, and reinforcement learning. These techniques would be applied to solve complex problems and field innovative solutions. The selected candidate will also be expected to assume technical lead responsibilities, take ownership of critical tasks and mentor junior engineers. Must exhibit self-motivation, a strong work ethic, time management and interpersonal skills. The selected candidate can work at any major Lockheed Martin facility or remotely.

Requirements

Bachelor’s Degree in Engineering, Computer Science, or other related discipline
10+ years of professional experience in the related discipline
Proficiency in Python and multiple libraries (NumPy, OpenCV, Scikit, Pandas, LangChain, etc.)
Experience using machine learning frameworks (Pytorch, Tensorflow, Hugging Face, MxNet, Caffe, etc.)
Experience with network/messaging (UDP, ZeroMQ, RESTful API, etc.)
Experience with C++, Java, JavaScript, TypeScript, Web-based languages (HTML5, CSS, etc.), GO, and other compiled languages
Experience with Natural Language Processing (NLP) and Large Language Models (LLM)
Experience interfacing with databases (SQL Server, MySQL, PostgreSQL, MongoDB, etc.)
Experience with modern Computer Vision (CV)
Experience with image processing and data analysis techniques
Experience in high-performance computing, embedded systems, edge computing, or AI deployment
Experience with neural network architectures and their computational requirements
Experience deploying neural networks on embedded/edge devices
Experience with large-scale software architecture and design
Experience with transitioning prototype software to production
Experience leading large technical teams
Creative and resourceful when it comes to problem-solving
Must be a US citizen

Nice To Haves

Master’s Degree in Engineering, Computer Science, or other related discipline
Experience with DevOps tools: Docker, Git [GitLab, GitHub], Continuous Integration [CI], Continuous Deployment [CD]
Experience working cross-functionally with product/platform teams
Experience with application of current research in the AI/ML domain
Problem-solving mindset with attention to real-world deployment challenges
Self-motivated with ability to work independently and collaboratively
The ability to thrive in a fast-paced environment in an industry that constantly changes
Strong oral and written communication skills, and ability to collaborate with cross-functional partners
Strong presentation skills to present to teams, stakeholders, leadership, and customers
Experience of collaborating with virtual teams

Responsibilities

Assume technical lead responsibilities
Take ownership of critical tasks
Mentor junior engineers
Develop technologies and products that leverage Artificial Intelligence
Engage in every phase of the system development lifecycle including requirements generation, system and software design, development, implementation, integration, and deployment
Conduct low TRL research, proof of concepts, development of prototypes, building demonstrators, and transition to production
Apply current AI paradigms including computer vision, deep learning, and reinforcement learning to solve complex problems and field innovative solutions
Build AI Agents and/or train and deploy ML models
Develop applications on Windows and Linux