EVONA · 1 hour ago
Sensor Fusion & Machine Learning Engineer
United States
Full-time
Remote
Entry, Mid Level
2+ years expEVONA is partnering with a cutting-edge organization working at the intersection of space, defense, and advanced data systems. They are seeking a Sensor Fusion & Machine Learning Engineer to help turn complex, multi-modal sensor data into actionable insights that support mission-critical applications.
Staffing & Recruiting
Responsibilities
Designing and deploying machine learning models to interpret physics-driven data across domains such as space systems, missile defense, PNT, and advanced communications
Building numerical models to simulate physical systems and integrating these with ML approaches to improve predictive accuracy
Developing algorithms for spatio-temporal registration and data association across heterogeneous sensor networks
Designing and implementing multi-sensor fusion architectures that deliver a unified, real-time common operating picture
Applying digital signal processing techniques to extract weak signals from high-noise environments prior to ML ingestion
Owning data pipelines including preprocessing, feature engineering, and data augmentation
Optimizing model performance and scalability for cloud-based deployment, primarily on AWS
Monitoring models in production and iterating continuously to improve performance and reliability
Collaborating closely with cross-functional teams to translate complex physical processes into scalable ML solutions
Qualification
Required
2+ years of experience in machine learning engineering or a closely related role within aerospace or defense environments
Hands-on experience building and deploying ML models using modern frameworks such as TensorFlow, PyTorch, Keras, or JAX
Strong experience working with time-series data, sensor data, and imaging data
Background in numerical modeling and physics-based systems, ideally at scale or within distributed environments
Experience with Kalman filtering and Bayesian methods
Solid foundation in signal processing, data science, and model evaluation
Proven experience taking ML models into production, with working knowledge of MLOps practices including CI/CD, model versioning, and monitoring
Strong problem-solving skills and the ability to communicate clearly within multidisciplinary teams
Preferred
Master's degree in electrical engineering, aerospace engineering, or a related field
Experience deploying and scaling ML workloads on AWS, including services such as SageMaker
Exposure to physics-informed machine learning approaches such as PINNs or neural operators
Familiarity with Docker and containerized deployments
Experience working with real-time data processing frameworks such as Spark, Flink, Kafka, or similar
Experience supporting or maintaining live systems running on Kubernetes
Relevant cloud or machine learning certifications
Company
EVONA
We believe in the evolution of knowledge and the progression of people - it is so core to our business, it's the meaning of our name: EVO - to evolve, ONA - people.
51-200 employees
Funding
Current Stage
Growth StageLeadership Team
Jack Madley
Co-Founder
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