Lead ML Developer & Operations Engineer

As the lead Two Six Technologies Developer for an open source machine learning (ML) test and evaluation (T&E) system, you will lead the team to develop new features and work with a team of professional ML researchers, developers, and operators that spans government and industry partners. You will also drive the operational deployment and integration of the program to multiple government partners. You will scale-up our well-established ML red team T&E system that models adversarial scenarios and evaluates cutting-edge ML defenses. You will also play a key role in our overall ML defense and security strategy.

Duties:

• Lead the iterated development, release, and maintenance of Armory, our open source adversarial ML framework
• Drive the operationalization and transition of the program to government and industry users
• Develop new features per emerging user needs
• Collaborate in the creation and integration of new adversarial testing methods and real-world scenarios 
• Collaboratively build back-end capabilities to scale Armory-based capabilities
• Collaborate in the evaluation of cutting-edge ML defenses via the system
• Work with other developers on cloudification, containerization, and productization of their applications
• Engage with peers to review solutions and help ensure our team delivers maintainable and extensible solutions

Requirements (ordered by priority):

• Advanced degree with 10+ years of experience or Bachelor’s degree with 12+ years of experience
• 5+ years experience leading a software development team, including task decomposition, feature prioritization, issue delegation, code review, and system architecture design
• 3+ years experience operationalizing ML systems or transitioning ML systems to government customers, especially while managing a product intended for a diverse set of customers with competing needs
• Python fluency including packaging, testing, and requirements management

• 3+ years experience working with ML libraries and systems, such as PyTorch, TensorFlow, TFDS, Numpy, or HuggingFace

• Experience with Jupyterlab or Streamlit

Additional Nice-to-haves:

• Compute cluster provisioning and management experience
• Knowledge of distributed computing concepts
• Open source project development experience
• Training or evaluation of ML models
• Development of datasets for ML training
• Experience with Linux, git, GPUs, and NVIDIA-Docker
• Docker and container registry experience
• AWS S3 or EC2 familiarity

Clearance Requirements:

Eligible for security clearances required