Senior Machine Learning Engineer Job Listing at SAIC in San Antonio, TX (Job ID 2509585)

Description

Description

Role Overview:
As a Machine Learning Engineer Senior at SAIC, you will play a crucial role in designing, implementing, and testing proof of concepts for improving flight training platforms. You will collaborate closely with a multidisciplinary team of engineers, pilots, instructional designers, and data specialists to create an immersive and interactive training experience that leverages both cutting-edge software and data-driven insights. Your work will support not only the development of advanced training features but also the collection, management, and analysis of training performance data to enhance effectiveness, enable predictive analytics, and support AI/ML-driven improvements in student learning outcomes.

This is an onsite position based out of San Antonio, TX.  (There is no option for remote work)
 

Key Responsibilities:

• Work closely with cross-functional teams to understand requirements and design solutions for remote instruction capabilities within our flight simulation training platform.
• Develop software modules and features to enable real-time communication, data streaming, and interaction between instructors and trainees during remote training sessions.
• Implement advanced visualization techniques and user interfaces to enhance the remote instruction experience and provide intuitive controls for instructors and trainees.
• Integrate external APIs, protocols, and hardware interfaces to support interoperability with flight simulation hardware and software components.
• Design, manage, and optimize databases to support the collection, storage, and retrieval of training performance and system telemetry data.
• Build data pipelines and processing logic to enable trend analysis, predictive analytics, and the generation of actionable insights from training sessions.
• Apply machine learning techniques to analyze student performance data, support early detection of training issues, and improve predictive models of student learning outcomes.
• Collaborate with QA engineers to ensure the reliability, performance, and scalability of both software and data systems through comprehensive testing and validation.
• Provide technical support and assistance to pilots, instructors, and customers during the testing and evaluation phases of the proof of concept.
• Leverage AI/ML models and data analytics to inform continuous improvements in training design, student performance tracking, and adaptive instruction methods.
• Stay updated on emerging technologies, industry trends, and best practices in flight simulation, remote instruction, data engineering, and AI/ML to drive continuous innovation and improvement.

Qualifications

Qualifications

• Bachelor's degree and 5 years of experience, or equivalent relevant years of experience in lieu of degree.
• Security+ or another DoD 8140 compliant certification.
• Solid understanding of software development principles, algorithms, and data structures.
• Proficiency in TypeScript, NodeJS, Python, with experience in developing software applications or simulations.
• Experience with application development for macOS and iOS platforms using Xcode and Swift.
• Experience in designing and working with relational and/or NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB), including data modeling, query optimization, and performance tuning.
• Familiarity with data pipelines, ETL processes, real-time data streaming frameworks, and machine learning workflows.
• Familiarity with real-time communication protocols (e.g., WebRTC, RTP/RTCP) and network programming concepts.
• Experience with 3D graphics programming (Unreal Engine) and virtual reality (VR) technologies is a plus.
• Strong problem-solving skills and the ability to work independently as well as part of a collaborative team.
• Excellent communication skills and the ability to effectively convey complex technical, data, and AI/ML concepts to non-technical stakeholders.
• Passion for aviation and a keen interest in flight simulation training, AI/ML-driven instruction, and data-informed training methodologies.