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Links Technology Solutions, Inc. is seeking an AI/ML Engineer III to serve as the primary technical lead for rapid R&D prototyping of autonomous technologies in a fast-paced team. The role focuses on architecting proof-of-concept AI/ML builds and mentoring growing engineers.
The ideal candidate will bridge leadership vision and technical execution, deliver end-to-end AI/ML prototypes, and collaborate across software, hardware, and data science teams to advance autonomous platform functionality.
Title: AI/ML ENGINEER III
Location: Englewood, CO (Onsite)
Pay Rate: $68.00 per hour
Hours:40 hours per week
Duration: Contract (5 months+)
Summary:
Serve as the primary technical lead and expert for AI/ML development on a fast-paced team prototyping new autonomous technologies for an innovative Joint Task Force. This highly autonomous position focuses on rapidly architecting proof-of-concept builds for autonomy, perception systems, and advanced analytics. Ideal candidates will bridge the gap between high-level leadership vision and technical execution while mentoring growing engineers.
Serve as the primary day-to-day AI/ML expert, performer, and technical lead for a rapid R&D prototyping team.
Rapidly define architecture, technical direction, and requirements for new AI/ML initiatives and prototypes without regular technical oversight.
Architect and build end-to-end AI/ML prototypes quickly, managing data ingestion, feature engineering, training pipelines, model deployment, and evaluation.
Lead the design and development of advanced machine learning models, including deep neural networks, reinforcement learning systems, and generative AI algorithms.
Translate high-level conceptual guidance from leadership into actionable requirements, designs, roadmaps, and technical approaches.
Collaborate with software, systems, hardware, and data science teams to integrate AI/ML prototype components into larger autonomous platforms.
Help Program Managers identify staffing, tooling, and data requirements while identifying and managing technical risks during execution.
Develop and oversee robust validation and testing frameworks to ensure models meet performance, safety, and compliance standards.
Lead the development and integration of signal processing, computer vision, and planning algorithms to advance autonomous system functionality.
Design and execute large-scale simulations and modeling of AI/ML systems on CPU/GPU platforms.
Prepare and execute demonstration plans, technical briefings, and trade studies for leadership and program stakeholders.
Bachelor’s degree in Computer Science, Mathematics, Applied Statistics, or a related STEM discipline with 6+ years of related experience (or 9+ years of related experience in lieu of a degree); a Master’s degree in Artificial Intelligence or Machine Learning is preferred.
Proficient in machine learning frameworks (e.g., TensorFlow, PyTorch) and implementing advanced techniques such as supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic).
Proficient in developing, deploying, and optimizing AI/ML models (including ANNs, CNNs, RNNs, and transformers) for production applications.
Strong proficiency in programming languages such as Python, C++, C#, or Java.
Proven track record of delivering rapid prototypes or research models under tight schedule pressure and evolving requirements.
Experience leading teams or projects, including a strong ability to coach, mentor, and "upskill" engineers with developing AI/ML backgrounds.
Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications.
Preferred experience establishing ML engineering practices (MLOps, data versioning, validation frameworks) and working with hardware acceleration (e.g., CUDA, TensorRT).
Preferred familiarity with early-stage autonomy R&D, multimodal sensor fusion research, or integrating ML models into embedded/real-time platforms.
Pay Rate: $68.00 per hour
Available health, life, vision, and dental insurance
401K Matching
Opportunity to work on cutting-edge, high-impact autonomous technologies in a collaborative environment
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