Develop MLOps frameworks and workflows for a variety of domains and applications
Deploy, maintain, and optimize ML models and data processes in a production environment
Develop custom AI/ML algorithms that translate into mission value
Conduct experiments, evaluate model performance, and fine-tune algorithms to improve accuracy and efficiency
Collaborate with cross-functional teams to integrate AI/ML models into products and services

Requirements

Hands-on experience with scripting languages such as Python, Javascript or Rust
Hands-on experience with developing machine learning models at scale from inception to business impact
Hands-on experience with any major deep learning framework and libraries (Tensorflow, PyTorch, HuggingFace)
Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB, Airflow, Kubeflow, Gitlab CI or DVC
Hands-on experience developing and deploying machine learning pipelines in AWS, Azure or GCP
Design and develop custom/novel architectures, define use cases, and develop methodology & benchmarks to evaluate different approaches
Experience deploying, maintaining, testing, and optimizing ML models and data platforms in a production environment
Experience working with and managing processing of large datasets and computational or analytic jobs
Experience monitoring and triaging issues with data processes and tools
Must be a U.S. Citizen (No Dual citizenship)

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonJavascriptRustmachine learning modelsdeep learning frameworksTensorflowPyTorchMLOpsCI/CDmachine learning pipelines

Soft Skills

collaborationcross-functional teamwork