Location: Bethesda, MD

Onsite: 100%

Work Authorization: US Citizenship required

Clearance: TS/SCI Full Scope Poly

Type: Full Time

Experience: 3 years to SME

Salary Range: Commencing with experience

Benefits: The standard compensation package consists of a competitive salary, 100% company-paid health/dental/vision care benefits, 100% company-paid LTD/STD/Life Insurance benefits, a 401(k) with company match, and a generous holiday/vacation/sick leave policy.

Introduction:

The Machine Learning Engineer will support the development and deployment of machine learning models for cyber missions and targets. The engineer will implement machine learning methodologies, identify trends within cyber data, work with data science models, integrate machine learning models into software, and collaborate with cross-functional team members.

Work Requirements:

1. Implement machine learning methodologies to triage large commercial cyber datasets.
2. Identify topical, spatial, and time-based trends of interest within large amounts of commercial cyber data.
3. Work with data science models testing, optimization, validation, and test automation.
4. Integrate machine learning models into software through inference engines, machine learning pipelines, and other approaches.
5. Communicate effectively with cross-functional team members, including program managers, data analysts, data scientists, external stakeholders, management, and software solutions integrators.

Mandatory Skills & Experience:

1. Demonstrated experience developing and deploying machine learning models.
2. Demonstrated experience tuning hyper-parameters of existing machine learning models for domain-specific data sets.
3. Demonstrated experience implementing, evaluating, and extending state-of-the-art data science methods, data labeling, ETL, and other data standardization practices.
4. Demonstrated experience integrating user-orientated model evaluation.
5. Demonstrated experience working with data science models testing, optimization, validation, and test automation.
6. Demonstrated experience leveraging model management capabilities to track version control and maintain information about best-performing models, such as MLFLOW or similar.
7. Demonstrated experience programming in Python.
8. Demonstrated experience programming in other scripting languages, such as Bash.
9. Demonstrated experience applying deep learning and machine learning processing libraries, including PyTorch, TensorFlow, Keras, and scikit.
10. Demonstrated experience using Linux and Windows operating systems.
11. Demonstrated experience using CUDA and NVIDIA GPU accelerated libraries for AI, machine learning, and deep learning.
12. Demonstrated experience implementing data science workflows in cloud-based platforms (e.g., AWS, Azure, etc.).
13. Demonstrated experience deploying ML models and creating associated APIs.
14. Demonstrated experience with spark, creating spark clusters in cloud infrastructure and utilizing spark for machine learning.
15. Demonstrated experience creating front-end interfaces to interact with machine learning models.

Optional Desired Skills & Experience:

1. Demonstrated experience/knowledge in cyber security concepts and with Customers’ cyber mission. Demonstrated experience developing and deploying machine learning models based on cybersecurity-related workflows.
2. Demonstrated experience working in Customer’s mission environment.
3. Demonstrated experience developing and working with cyber data (e.g. netflow, pcap, credential, ip scans, etc.).