Machine Learning Engineer - R126

Expedition Technology; Herndon (VA); On-site; USD 100,000 - 130,000; Full time

Job summary

A national security solutions firm in Herndon, Virginia is looking for a Deep Learning-and-Software Engineer to join their innovative team. This role requires expertise in deep learning architectures and Python, along with experience in developing end-to-end deployable systems. Candidates must hold an active Top Secret clearance and be US Citizens. Successful applicants will research recent machine learning theories, develop architectures, and implement solutions in a fast-paced environment.

Qualifications

• Active Top Secret clearance (TS/SCI preferred) required.
• 2+ years of experience with MS or 4+ years with BS in a relevant field.
• Strong understanding of deep neural networks and their applications.

Responsibilities

• Research academic literature for latest theories in machine learning.
• Develop deep learning architectures and pipelines.
• Deliver high-quality tested software in Python.

Skills

Deep Learning architectures

Python

PyTorch

Machine Learning frameworks

Software development

Collaborative code management (Git)

AWS

Computer Vision

Education

MS in a technical field

BS in a technical field

Tools

TensorFlow

Docker

Linux

Job description

At Expedition Technology (EXP), we work on real-world problems whose solutions will make an immediate impact on national security. If you desire an opportunity where you will apply your deep learning and software engineering expertise to challenging problems with no known solutions, EXP is the place to be!

Currently, we are seeking an experienced Deep Learning-and-Software Engineer who will work with a dynamic team that is delivering novel solutions to our Intel Community. We're looking for someone who has in-depth understanding of DL architectures such as YOLO, Faster R-CNN, Mask R-CNN, and other state of the art object detection models. The candidate should feel comfortable developing and testing end-to-end deployable systems; from sourcing and curating data, building, training, and evaluating models, to productizing final deliverables.

If you feel fulfilled by rolling up your sleeves and thinking about hard problems, building and integrating learning-based algorithms and systems, and delivering robust solutions in a fast paced but scientifically rigorous environment, we want to hear from you!

Interested in joining our team? Here's what you'll need to succeed:

Responsibilities

• Researching academic literature to keep abreast of the latest theories, techniques, and tools
• Working in a team to develop deep learning architectures and pipelines for novel applications
• Implementing solutions in Python (PyTorch)
• Delivering high-quality, carefully tested software
• Participate in team brainstorming sessions to shape innovative solutions

Required Skills and Experience

• An active Top Secret clearance (TS/SCI preferred)
• US Citizenship - must be eligible to maintain a US-Government issued security clearance of Top Secret or higher
• MS and 2+ years of experience or BS and 4+ years of experience in a technical field such as Computer Science, Electrical Engineering, Physics, Statistics, or Applied Mathematics
• Proven proficiency in PyTorch, TensorFlow, or other modern machine learning framework
• Solid theoretical understanding of deep neural networks as well as its applications, particularly in computer vision
• Proven experience architecting, training, testing, and deploying machine learning solutions within an AWS environment
• Experience using collaborative source code management tools (Git)
• Strong technical presentation and writing skills
• Strong software development skills to include object-oriented design and implementation in languages like Python
• Strong practical experience developing in both object oriented and procedural languages
• Experience with standard data structures, algorithms, and application organization
• Experience with the full software development lifecycle, CI/CD, agile/scrum methodologies
• Experience with software testing (unit, integration, functional, etc.)
• Exposure to software containerization with Docker, Linux, and cloud development