At Leidos, we use Typescript, Python, Java 9, Rust, and the Unity stack to build actual software that people both pay for and willingly use. Our engineers are housed in a safe and welcoming habitat with infinite espresso, fancy ramen, and Atlassian tools. Data scientists in our Applied Systems team can expect to make heavy use of Python, Tensorflow, and Spark as they munch on their ramen thoughtfully.
This job has two major focus areas. The first centers on transitioning image classification and recognition systems to massively scalable applications using internal micro-service frameworks built on Kafka and Docker. The second focus area is accelerating and parallelizing photogrammetric processes to be suitable for near-real-time applications.
Bachelor's in Computer Science, Computer Engineering, Electrical Engineering, or related field
Two or more years of professional experience in software engineering or data science
Two or more years of experience in applied modeling or geospatial systems
Fluency in Python, Scala, Rust, Java or Typescript
Professional experience with Kafka and at least one Big-Table-alike, preferably Accumulo
Experience in low-latency domains such as video processing or trading arbitrage
Priors with Azure Functions or AWS Lambdas for serverless systems
Experience with Geomesa, GeoTrellis, GeoWave, or comparable
Priors with Tensorflow, PyTorch, or XGBoost