Machine Learning Engineer

At INflow Federal, we're not just navigating the frontier of digital transformation; we're reshaping it. Our dedication to merging the prowess of humans and machines to solve complex problems has set us apart in designing and engineering solutions for the Department of Defense (DoD) networks. Here, every challenge is an opportunity to advance, and every solution is a step towards a more secure and connected future. We look forward to welcoming you to the INflow team!
ABOUT THIS POSITION:
We are looking for an engineer who enjoys disrupting the "norm" to join our dream team designing and executing experiments for few and low shot approaches for overhead imagery.
Avenues of research include: self-supervised methods, generative adversarial approaches for domain transfer with synthetic imagery, methods for reducing supervision cost through alternative annotation types and networks.
Key Responsibilities: • Design and execute experiments for general detector performance in overhead imagery. Implement and evaluate new network architectures/approaches from literature as necessary to maintain strong baseline performance. • Create custom deep neural network components and new performance metrics as needed. • Occasionally write custom network components, evaluation metrics, etc. in C++ • Maintain containerized execution environments for experiments across compute architectures and domains using Docker and Singularity. • Occasionally work to deploy models created by the team on various partner platforms for evaluation and feedback. • Build and maintain production ready ML pipelines • Build and maintain a production-ready platform to run models in parallel and A/B test • Prepare and preprocess data in collaboration with the data engineering team 

Required Qualifications

• Experience in Machine Learning related field, preferably Computer Vision
• In-depth knowledge of image processing, statistical modeling, advanced mathematics, data integration concepts and tools 
• Strong organizational, analytical, critical thinking and leadership skills 
• Demonstrated leadership on mid-large-scale project impacting strategic partners 
• Background in Machine Learning frameworks such as PyTorch, TensorFlow, SparkML or Keras, Scikit Learn 
• Proficiency in Python or an equivalent language 
• Knowledge of C++ or equivalent object-oriented language
• Experience with at least one cloud provider (AWS, Azure, GCP)
• Experience with CI/CD and containerization tools (e.g. Docker, Singularity, github/GitLab) and best practices 
• Experience with Blender

Required Education & Experience

• MS + 2 years 
• BS + 5 years 
• No Degree + 15 years 

Preferred Qualifications

• Masters Degree Preferred
• PhD Preferred
• Research Experience Preferred

Clearance Requirement

• Must have a minimum of a DoD TS/SCI clearance

About Us Founded in 2013, INflow Federal has distinguished itself through our exceptional services because of our deep-rooted commitment to our people. The ‘INflow difference’ lies in our profound appreciation of employee culture, fueling an obsession with the well-being and professional growth of our team. This employee-centric ethos has been pivotal to our enduring success, directly translating into significant benefits for our customers.Our identity is greatly influenced by the contributions of US Military Veterans. INflow’s Veteran Outreach Program, dedicated to recruiting transitioning military personnel, has been a resounding success. Veterans now represent over 50% of our workforce, bringing invaluable experience and insight that have been crucial in steering our customers’ success.
As a dynamic small business at the forefront of innovation, INflow boasts extensive expertise in Network Modernization, Cybersecurity, and Data Modernization in support of Joint Force Mission Operations. Our reach extends to over 20 states, serving prestigious federal government clients including the United States Navy (USN), United States Marine Corps (USMC), and Joint Forces.
In our quest to simplify the customer experience, we embrace a collaborative approach, guided by our leadership’s transparent communication and unwavering commitment to integrity. Our customers value partnering with INflow for our agility, passion, and integrity.
Fueling INflow’s continuous evolution is our voracious appetite for researching and integrating AI/ML technologies. We are committed to empowering our employees and customers with these emerging tools, enhancing their ability to effectively integrate these technologies into their workflows. This not only improves their operational efficiency but also deepens their understanding of AI/ML’s transformative potential.
As we progress, our focus remains steadfast on developing our people so they can  lead our customers into the future of mission systems and operations, adeptly navigating the ever-evolving landscape of the Department of Defense with innovative solutions and strategic insights.
Citizenship RequirementsINflow Federal is a defense contractor. Due to legal requirements, candidates must be US Citizens to be considered for employment.
Other Notes- Some travel may be required: Must have valid driver’s license and transportation. This is subject to change at the direction of the customer.Other: - Candidate must have the ability to lift up to 50 lbs. Must have willingness to perform duties not listed in the job description as required by INflow and our customer.
Equal Opportunity Employer Diversity and InclusionINflow provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
This commitment applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, leaves of absence, compensation, and training. Job applicants and employees are evaluated solely on job-related qualifications and experience.