Senior Machine Learning​/AI Software Engineer

Job Description

At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.

The Boeing Company is currently seeking a Senior Machine Learning / AI Software Engineer to join the Special Projects Dallas (SPD) P‑8A Advanced Airborne Sensor (AAS) Software Engineering team located in Richardson, TX
. This position will focus on supporting the Boeing Defense, Space & Security (BDS) business organization.

The Boeing Company in Richardson, TX is looking for a Senior Machine Learning / Artificial Intelligence Software Engineer to design, develop, document, and deploy robust, ethical, and scalable AI/ML solutions for aerospace systems. The role requires hands‑on ownership across the ML lifecycle: data collection and preprocessing, model design and training, verification and validation, safety risk management, production integration, and ongoing monitoring and improvement.

The successful candidate will collaborate closely with cross‑functional teams and domain experts, apply best‑practice engineering and testing methodologies, and stay current with emerging tools, frameworks, and regulatory/ethical considerations in support for the P‑8A Advanced Airborne Sensor (AAS) Mission Systems contracts.

• Design and implement appropriate AI/ML algorithms and models using standard methods and tools, with attention to ethical implications and potential biases.
• Oversee the collection, cleaning, preprocessing and analysis of large datasets to ensure data quality, reliability and identification of patterns, trends, and insights.
• Train, evaluate, and optimize model performance, generalization, and computational efficiency.
• Test, document, debug, and validate AI/ML models and associated software systems following engineering standards.
• Consult on training, evaluation and optimization of performance and capabilities of Artificial Intelligence models.
• Oversee Safety Risk Management processes for Artificial Intelligence models in accordance with organizational standards.
• Provide subject matter expertise on integration and deployment of standard efficient and scalable Artificial Intelligence models into production environments.
• Oversee monitoring, validation and improvement of standard in production Artificial Intelligence models.
• Consult and collaborates with cross functional teams and domain experts to understand business requirements, gather feedback, and iterate Artificial Intelligence models and algorithms.
• Influence current and emerging technologies, tools, frameworks, and regulations in the Artificial Intelligence environment and contributes to Artificial Design Practice(s).
• Research, prototype, and adopt current and emerging technologies, tools, frameworks, and regulatory guidance relevant to AI/ML and aerospace applications.

• Masters degree or higher in Engineering and/or a Technical discipline.
• Proficiency with ML frameworks and libraries such as Tensor Flow, PyTorch, scikit‑learn, and common data tooling (e.g., pandas, Num Py).
• Experience with data engineering tasks: data collection, cleaning, preprocessing, feature engineering, and working with large‑scale datasets.
• Solid understanding of ML fundamentals: supervised and unsupervised learning, deep learning, model evaluation metrics, regularization, and hyperparameter tuning.
• Hands‑on experience building end‑to‑end ML solutions from data ingestion through production deployment and maintenance.

• PhD degree in Computer Science, Electrical Engineering, Data Science, or related field (or equivalent experience).
• Significant experience designing and deploying ML systems in production, preferably in regulated domains.
• Strong knowledge of ML algorithms (supervised, unsupervised, deep learning), model evaluation, and optimization techniques.
• Proficiency with data engineering: cleaning, feature engineering, and working with large‑scale datasets.
• Experience with ML frameworks and…