Sierra Nevada Corporation
Sr AI/ML Engineer
Herndon, Virginia · Senior
No sponsorship$10k-$20kDetected 16 days ago
PythonJavaC++C#AWSDevOpsMachine LearningTensorFlowPyTorchNLPLLMsRAGStatisticsA/B TestingCybersecurityAccountingHRRoboticsSignal ProcessingResearchLeadershipMentoring
About the role
- You will also act as a technical leader, providing strategic guidance on AI/ML initiatives, ensuring compliance with regulatory standards, and collaborating with stakeholders to meet organizational objectives.
- This posting will be open for application for a minimum of 5 days and may be extended based on business needs.
- Estimated Starting Salary Range: $143,487.14 - $197,294.82.
Responsibilities
- Conduct continuous discovery and hypothesis-driven experimentation, rapidly developing prototypes to assess feasibility and potential impact.
- Partner with business stakeholders to translate non-technical requirements into actionable AI/ML exploration paths.
- Develop and prototype RAG-based architectures, including embedding pipelines, retrieval strategies, and transformer-based generative components.
- Explore and validate new approaches for retrieval, indexing, and multimodal document understanding.
- Apply validation, safety, and explainability practices in support of aerospace/defense requirements.
- Develop signal processing, perception, and planning pipelines supporting MPC control loops.
- Use GPU acceleration, simulation environments, and HPC resources to support MPC experimentation.
- Architect, train, and optimize advanced models including transformers, GANs, RL agents, and real-time systems.
- Safety, Validation & Integration Support:
- Develop validation and testing frameworks ensuring compliance with safety and reliability standards.
Requirements
- Support integration teams with prototypes, documentation, and technical insights as required.
- Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
- 10+ years of experience in a related field.
- In the absence of a degree, a minimum of 12 years of related experience is required.
- Higher level relevant degree may substitute for experience.
- Extensive experience architecting, deploying, and optimizing AI/ML systems, including ANNs, CNNs, and RNNs, in large-scale or mission-critical environments.
- Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.
- U.S. Citizenship status is required as this position needs an active U.S. Security Clearance for employment.
Compensation
- $143,487.14 - $197,294.82.
- Compensation varies depending on a wide array of factors, such as candidates' key skills, relevant work experience, and education/training/certifications.
- SNC offers annual incentive pay based upon performance that is commensurate with the level of the position.
Benefits
- Design and prototype MPC-aligned models incorporating predictive modeling, optimization, and reinforcement-learning-based control.
- Relevant experience can be considered as a substitute for the required educational qualifications.
- Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic).
- SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.
Equal opportunity
- SNC is an Equal Opportunity Employer committed to an environment free of discrimination.
- Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law.
Visa & Work Authorization
- Security Clearance
Apply directly at Sierra Nevada Corporation →Create a free account for alerts like thisView Sierra Nevada Corporation immigration profile
This listing is sourced directly from Sierra Nevada Corporation's careers page and normalized into a canonical job model.