Applied Machine Learning Engineer

About the CompanyOur client is a fast-growing, venture-backed maritime technology company building advanced sensing and intelligence systems for both commercial and defense applications. They are developing edge-intelligent platforms that operate in real-world, high-stakes environments, combining AI, sensor fusion, and distributed systems to deliver actionable insights at scale.About the RoleThis is a chance to work on real-world AI systems deployed in the field. You will build and deploy machine learning systems that operate on edge hardware, integrate across multiple sensor types, and deliver mission-critical insights in real time.ResponsibilitiesDesign, train, and evaluate models across object detection, classification, anomaly detection, and sensor-based inferenceOptimize models and inference pipelines for edge and embedded environments with compute and bandwidth constraintsBuild and maintain real-time data processing pipelines across edge and cloud systemsContribute to dataset development and labeling strategyPartner closely with hardware, software, and product teams from concept through production deploymentInvestigate and resolve failure modes in field-deployed systemsQualificationsStrong background in machine learning, computer vision, or sensor fusionOwnership of post-academic, production scale model deploymentsExperience deploying models to edge or embedded hardware (sensors, cameras, etc)Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar)Comfort working across the full ML lifecycle: data → training → deployment → monitoringExperience with real-time inference pipelines is a strong plusMust be eligible for a U.S. security clearancePay range and compensation package$240K–$270K base + equity (targeting $300K+ total)Equal Opportunity StatementService to Success is an equal opportunity employer and recruiting partner. We are committed to creating an inclusive process and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.