Senior Machine Learning Engineer

Candidate should live within driving distance of the following areas: Waldorf, MD; Wichita, KS; Lawton, OK; or Round Rock, TX. Job Purpose/Summary The Machine Learning Engineer will build and integrate machine learning solutions into our next-generation space and critical infrastructure defense capabilities. They will leverage a variety of machine learning approaches to process very large streams of unstructured data in real time in scalable and secure cloud‑native environments. As the first dedicated internal Machine Learning Engineer for this product, they will play a critical role in requirements generation, team leadership, and influencing the future of our products. This is a demanding product development role, not a research position. Success on year one involves the design, training, optimization, validation, and implementation of high‑performance inference pipelines at scale. The role will play a key part in building and delivering initial machine learning capabilities for our MVP offering and may evolve over time to include involvement in hiring and mentorship as the team grows. Duties and Responsibilities Lead the development and implementation of real‑time feature detection and anomaly detection models. Generate data characteristic requirements for real‑time data processing pipelines. Prepare technical documentation, reports, and specifications. Collaborate with cross‑functional teams including project managers, technicians, and other engineers. Perform testing, troubleshooting, and quality assurance on systems or products. Ensure compliance with safety regulations, industry standards, and company policies. Qualifications 7-10 years of experience as a SWE or ML engineer building applied research and/or production technologies. Expertise on building production training and inference pipelines in Python. A strong familiarity and personal preference for one or more deep learning libraries (e.g., PyTorch). A comprehensive understanding of systems programming (a strong proficiency in C would imply this). An understanding of how ETL processing works and familiarity with some of the common tools (Kafka, Spark, etc.). Experience building machine learning models for unstructured data types (text, imagery, RF, telemetry, etc.). Experience with hardware acceleration (GPUs, CUDA) for training and inference workloads. Experience packaging and deploying trained inference models for use in production environments. Minimum education requirement: High school diploma. Eligible to obtain a U.S. Security Clearance – U.S. Citizenship required. Bonus Qualifications Experience integrating trained inference pipelines into scalable cloud‑native infrastructure. Experience building backend services and implementing API endpoints for scalable infrastructure. Experience building technology for air‑gapped production deployment environments. Knowledge and experience with OCI technologies (Docker, Kubernetes, Helm, etc.). B.S. or M.S. in an area relevant to this role. Working Conditions Employees may be called upon to participate in in‑person meetings, training, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position. Estimated Travel: 0-10%. Physical Requirements May include sitting or standing for extended periods, working with computers and technical equipment, and occasionally lifting or moving materials or tools. Direct Reports None #J-18808-Ljbffr