Senior Computer Scientist; AI​/ML

Kegman Inc. is a Women Owned/Service-Disabled Veteran-Owned Small Business headquartered in Melbourne, FL and provides engineering and technical support services to U.S. Government clients. We are seeking a Senior Computer Scientist (AI/ML) to join the team supporting the Air Force Technical Applications Center at Patrick Space Force Base in Melbourne, Florida.

NOTE:
This is not a remote/telework job.

This job requires the selected applicant to have an active U.S. Government‑issued security clearance at time of hire and, therefore, requires U.S. citizenship.

Kegman is seeking a skilled Senior Computer Scientist who will lead the architecture, development, and testing of state‑of‑the‑art Artificial Intelligence/Machine Learning (AI/ML) methodologies supporting the U.S. Government customer’s mission. Specifically, the contractor will direct efforts to design and deploy an advanced suite of deep learning algorithms for processing regional geophysical sensor data, including seismic, acoustic, hydro‑acoustic, and infrasound sensors.

• Lead Advisory and Assistance services for the architectural design and development of generalized phase picker and generalized regional associator algorithms.
• Architect, develop, configure, and evaluate advanced Python code for the detection of regional signal arrivals using deep neural network architectures and AIML Python libraries (PyTorch, Sklearn, Tensorflow/keras…etc).
• Building automated training pipelines, monitoring for model drift, and implementing retraining strategies.
• Serve as the primary technical advisor to executive and senior clients, briefing them on strategic development efforts, emerging technologies, system architecture, risk mitigation, and mission opportunities.
• Mentor and provide technical direction to junior and mid‑level engineers in AI/ML best practices and geophysical data processing.

• Familiarity with Git version control software is required.
• Proficient in signal processing of advanced waveforms to include seismic, acoustic, electromagnetic, or similar signals.
• Expert proficiency with the Python programming language, Anaconda environments, and Jupyter notebooks in a production environment.
• Subject matter expertise in general acoustic theory, particularly regarding local to near‑regional seismic phase arrivals, travel times, and association.
• Mastery of deep neural network architectures for complex time‑series data processing.
• Extensive experience with traditional geophysical signal detection algorithms and the ability to integrate them with modern AI/ML approaches.
• Demonstrated capability to architect solutions leveraging programming, advanced mathematics, data analysis, and data visualization toolkits to drive customer success.
• Proven ability to design and execute advanced statistical analysis on massive, complex datasets.
• Exceptional analytical, problem‑solving, organizational, and written/oral communication skills.
• Detail‑oriented technical leader capable of directing teams, consistently meeting mission‑critical deadlines, and driving projects independently with high autonomy.
• Advanced interpersonal, customer engagement, and technical negotiation skills.
• Demonstrated ability to manage multi‑faced projects and collaborate effectively with a diverse matrix of vendors, executive managers, subcontractors, consultants, and other professionals.
• Highly effective communication skills with company executives, employees, and government stakeholders; must command a room and present complex technical concepts clearly and confidently to both technical and non‑technical audiences.
• Familiarity with agile/scrum techniques.

• Bachelor’s Degree and 8+ years of relevant experience; OR
• Master’s Degree and 6+ years of relevant experience; OR
• Ph.D. and 3+ years of relevant experience.

• U.S. citizenship required.
• Must have a fully adjudicated (not an interim) Government clearance.
• Must pass a drug test.

Kegman Inc. is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other…