Graph Machine Learning Postdoc Jobs (NOW HIRING)

Information Systems and Cyber Division (ISCD)staff couple the latest in information system technologies, such as elastic compute clouds, containerization, microservices, real-time operating systems, and visualization frameworks, with expertise in cyber security, software architecture, software engineering,data science, Artificial Intelligence,process improvement, and software development to deliver responsive, resilient, high-performance software intensive systems to ourIntelligence Community, DoD,and civilian customers.

The Data Science and Artificial Intelligence Department (DSAID)seeksa creative and enthusiastic Machine Learning Engineerto join a diverse team of engineers, data scientists, and programmers with a passion for researching, prototyping, understanding, and building AI and data enabled tools across the space enterprise.We are a growing, innovative,andcollaborative department that makes meaningful contributions toNationalSecuritySpace(AF, NRO, etc.),andCivil andCommercial customers(NASA, MDA, DHS,etc.).

This position is for theData Science Applications section,where wefocus on solving customer problems with digital applications that involvedata scienceand machine learning techniques.DSA is looking for machine learning engineer with reinforcement learning and graph theory experienceto support customers in the missile warning/missile tracking domain.

This is afull-timeposition based inColorado Springs, Coloradowhichrequires100% onsite work.

WhatYou'llBe Doing

DSAID's customers range from NationalSecuritySpace(AF, NRO, etc.) to civil (NASA, NOAA, etc.) andcommercial (commercial space, autonomous vehicles, etc.)

• DSAID applies data science and AI knowledge across the space enterprise, to Aerospace enterprise capabilities, and towards corporate workforce development and strategic focus areas

• Machine Learning Engineers learn and develop their skills by working on teams spanning disciplines, experience levels, and organizational boundaries.

• Primary functions include:

• Evaluation of technologies for use in scalable and resilient mission-critical applications in a production environment

• Coordinated development and execution ofAI/MLexperiments

• Coordinated development of proof-of-concept infrastructure configuration and software prototypes

• Collaboration with small, innovative teams to deliver features and products

• Written and verbal presentation of results to team members and stakeholders

• Reinforcing an environment of learning and progress with team members and others

• Focus on accountability and innovation in leadership competency development

• Duties,responsibilitiesand activities may change, or new ones may be assigned as needed

• Machine learning engineers mustmaintaina commitment to ongoing learningin order tostay current with government missions and the ever-changing climate of data science and AI. This requires both ongoing education in relevant domains, such as physics, math, and/or computer science, as well as an understanding of the existing systems and futureobjectivesof government missions.

What You Need to be Successful

MinimumRequirements for the Machine Learning Engineer- Senior Member of Technical Staff

• Bachelors degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering orrelated technicalfield(s)

• 5 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain

• Strongproficiencyin at least two different programming languages (e.g.Python, R, C/C++),and MLframeworksand familiarity with common libraries used for Data Science and Machine Learning, such as pandas,pytorchor JAX.

• Experience with on and off-policy reinforcement learning algorithms such as Deep Q Learning, A3C, and PPO.

• Working knowledge of fundamental graph theory and graph neural networks.

• Hands on experience with containerorchestrationtooling(Docker, Kubernetes, etc.)

• Experience with and understanding of software engineering concepts with an AI focus (MLOps/DevOps, ML Development Lifecycle, data structures, etc.)

• Working knowledge of Unix/Linux operating systems

• This position requires ability to obtain andmaintaina security clearance, which is issued by the US government. U.S citizenship isrequiredto obtain a security clearance.

In addition to the above, theminimumrequirements for theMachine Learning Engineer- EngineeringSpecialist:

• 8 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain

• Demonstrated experience architecting, designing, or implementing enterprise-scale AI/ML solutions with multiple tenants and cloud integration

• Experienceleading technical teamsand in mentoring junior staff.

• Familiarity with data pipelining and streaming technologies (Apache Kafka, temporal, etc.)

How You Can Stand Out

It would be impressive if you have one or more of these:

• Advanced degreein Computer Science, Computer Information Systems, Electrical or Computer Engineering, or related field(s)

• Publications in reinforcement learning, graph theory, or a relevant AI/ML domain.

• Experience in designing or managing enterprise-level ML platforms and production-grade ML models at scale

• Familiarity with High Performance Computing hardwarefor ML(GPUs, TPUs), CUDA programming, and advanced ML optimization techniques and architectures

• Demonstrated ability to exercise judgement and critical thinking in a scientific discipline

• Experience implementing and guiding teams toward software development best practices

• Experience in SQL, NoSQL,Cypherand other big data querying languages

• Demonstrated contributions to open-source software repositories (github,kaggle, etc.)

• Experience deploying ML models on cloud platforms (AWS, Azure, etc.)

• Domainexpertiserelevant to one or more customer organization mission areas (USSF, NRO, etc.)

• Active security clearance