Location: Ashburn VA

Work Schedule: 100% Remote

Clearance: DoD TS or CBP BI

End Client: DHS/CBP

Must have Skills:

  • 2+ years of experience in building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
  • 2+ years of experience designing, developing, operationalizing and maintaining scalable tools and services for our clients to handle machine learning training and inference
  • 2+ years of experience designing the data pipelines and engineering infrastructure to support enterprise machine learning systems at scale
  • 2+ years of experience building scalable workflows for supporting machine learning
  • 2+ years of experience utilizing programming languages, including C++, C or Python
  • 2+ years of experience developing and maintaining scalable data repositories that supply data needed for training Machine Learning models
  • 2+ years of experience creating software for retrieving, parsing and processing structured and unstructured data
  • Experience with wide variety of machine learning programming languages, including Python, R, SQL or JavaScript
  • Experience with the Machine Learning lifecycle, including data import, annotation/labeling training data, CI/CD, automation, etc.
  • Experience with machine learning tools including Pandas, SciKitLearn, TensorFlow, or OpenCV
  • Experience with deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)
  • Experience supporting model development, with an emphasis on auditability, versioning, and data security
  • Experience supporting data scientists develop and build scripts to deploy models to production system
  • Experience with AWS SageMaker
  • Experience with developing scalable ETL/ELT workflows for training Machine Learning models
  • Experience creating solutions within a collaborative, cross-functional team environment
  • Ability to develop scripts and programs for converting various types of data into usable formats and support project team to scale, monitor and operate data platforms
  • Experience creating solutions within a collaborative, cross-functional team environment
  • Ability to develop scripts and programs to support project teams to scale, monitor and operate inference
  • Bachelor’s degree
  • Secret clearance

Nice to Have:

  • Experience developing containers for Kubernetes deployment in cloud computing environments
  • Experience with distributed data/computing tools such as Spark, AWS EMR, or Kafka
  • Experience with machine learning hardware, including AMD, NVIDIA DGX, or small form factor HW, such as Jetson or Xavier
  • Experience with embedded systems programming in C or C++
  • Knowledge of natural language processing, and synthetic data generation
  • Ability to train, optimize, integrate, and reinforce Machine Learning Algorithms across high volume or velocity text and imagery or full-motion video data feeds
  • Ability to translate business needs to technical requirements
  • Understanding of software testing, benchmarking, and continuous integration
  • Experience communicating with clients to build requirements and track progress
  • Experience with Google Cloud
  • Experience in application development utilizing SQL
  • Experience with machine learning hardware, including AMD, NVIDIA DGX, or small form factor HW, such as Jetson or Xavier
  • Knowledge of deep learning, natural language processing, and synthetic data generation
  • Experience with the deployment of proof-of-concept machine learning systems
  • Experience with NoSQL implementations
  • Experience with data warehousing, including AWS Redshift, MySQL, or Oracle
  • Experience with UNIX/Linux, including basic commands and Shell scripting
  • Experience with Agile engineering practices
  • TS/SCI clearance