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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior / Principal Machine Learning Scientist, Scientific Reasoning Models, AI for Drug Discovery - **Company:** Sierra Nevada Corporation. - **Location:** Washington, DC, United States - **Experience:** Expert - **Salary:** $124,771.0 - $171,561.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Systems Engineering, Artificial Neural Networks, Computer Vision, C Sharp (Programming Language), C++ (Programming Language), Cluster Analysis, Nvidia CUDA, Data Reduction, DevOps, Python (Programming Language), Machine Learning, Tensorflow, Signal Processing, Software Requirements Analysis, Reinforcement Learning, High Performance Computing, Pytorch, Gpu Programming, Information Technology, Hardware Acceleration, Machine Learning Operations, TensorRT - **Published:** September 22, 2026 - **Apply:** https://nlppeople.com/apply/mmr0 ## About the Role Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline6+ years of experience in a related field.Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 9 years of related experience is required.Higher level relevant degree may substitute for experience.Proficient in machine learning frameworks (e.g., TensorFlow, PyTorch) and skilled in implementing advanced AI/ML techniques, such as supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic), as well as working with generative AI models (e.g., transformers).Proficient in developing, deploying, and optimizing AI/ML models, including ANNs, CNNs, and RNNs, for production applications. Contributed to the design and scaling of systems for larger datasets or environments with moderate complexity.Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.Demonstrated experience leading teams or projects, including mentoring junior staff.Proven track record of deploying AI/ML models in production environments and optimizing them for real-world use cases.Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications Qualifications We Prefer Master's degree in Artificial Intelligence, Machine Learning, or related field.Experience leading teams or projects in aerospace and defense industries.Familiarity with cybersecurity and regulatory requirements.Proficient in Agile or DevOps workflows; active participant in iterative ML software development.Practical experience designing and implementing advanced ML techniques, such as clustering, dimensionality reduction, or generative modeling.Hands-on experience with GPU programming and using high-performance computing systems for ML workloads.Experience with at least one reinforcement learning or generative AI model (e.g., implementing GANs or Transformers).Able to analyze large-scale, heterogeneous datasets and apply advanced statistical and ML methods to real-world problems.Experience translating mission objectives into actionable system requirements, including HMI scenarios.Familiarity with hardware acceleration (e.g., CUDA, TensorRT) and introductory knowledge of edge AI or XAI. Essential Functions Ability to lead and manage complex AI/ML projects.Travel occasionally to testing sites, customer locations, or conferences (up to 10-20%).Work in a hybrid environment, managing cross-functional teams and high-priority deliverables. This posting will be open for application for a minimum of 5 days and may be extended based on business needs., Senior (5+ years of experience) Tagged as: Clustering, Industry, Machine Learning, Neural Networks, NLP, United States ## Description The AI/ML Engineer III is a mid-level technical position that requires advanced expertise in designing, developing, and deploying machine learning systems for aerospace and defense applications. In this role, you will lead the creation of cutting-edge AI solutions for complex problems, such as autonomous navigation, sensor fusion, and real-time decision-making. You will also mentor junior engineers, manage key projects, and contribute to strategic decision-making within AI/ML development efforts. Your work will directly impact mission-critical systems and next-generation technologies. The ISR (Intelligence, Surveillance & Reconnaissance), Aviation, and Security (IAS) business area is a leader in ISR and aviation, it is a leading prime manned and unmanned aircraft systems integrator for innovative, high-performance ISR and aviation systems. Its end-to-end Command, Control, Computers, Communications and Intelligence, Surveillance & Reconnaissance (C4ISR) capabilities encompass design, integration, test, certification, ground/flight training and complete logistics support. IAS tailors solutions to customer cost, performance, and schedule requirements and designs to consistently exceed expectations - with an unrivaled record of on time and on (or under) budget deliveries. Responsibilities Lead the design and development of advanced machine learning models, including deep neural networks, reinforcement learning systems, and generative AI algorithms, to solve complex problems.Architect scalable AI/ML systems that can integrate seamlessly with existing software and hardware platforms. Provide guidance on the selection of tools, frameworks, and infrastructure.Collaborate with systems engineers, hardware teams, and data scientists to align AI/ML solutions with mission-specific requirements and constraints.Manage AI/ML projects, including scoping, resource allocation, and timeline management, ensuring that deliverables meet quality and performance expectations.Develop and oversee robust validation and testing frameworks to ensure that AI/ML models meet performance, safety, and compliance standards in real-world scenarios.Mentor junior engineers, providing technical guidance and fostering a collaborative, innovative team environment.Stay current with emerging AI/ML technologies and propose innovative solutions to address new and existing challenges in the aerospace and defense domain.Communicate technical concepts, project progress, and outcomes to stakeholders, including leadership and external partners, in a clear and concise manner.Independently train, fine-tune, and optimize advanced AI architectures (including transformers) for complex applications.Apply a broad range of AI/ML techniques (supervised, unsupervised, reinforcement, generative) to solve domain-specific challenges.Lead the development and integration of signal processing, computer vision, and planning algorithms to advance autonomous system functionality.Design and execute large-scale simulations and modeling of AI/ML systems, ensuring scalability, performance, and robustness on CPU/GPU platforms.Lead rigorous validation and verification activities, ensuring deliverables meet performance, safety, and reliability requirements. ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)