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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.
Job Responsibility:
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
Requirements:
Masters degree or higher in Engineering and/or a Technical discipline
Proficiency with ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, and common data tooling (e.g., pandas, NumPy)
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
Active U.S. Top Secret Security Clearance (U.S. Citizenship Required)
Must meet U.S. export control compliance requirements (U.S. Person as defined by 22 C.F.R. §120.62)
Will be required to complete a technical assessment (CodeVue Coding Challenge)
Nice to have:
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 tooling (e.g., TensorFlow, PyTorch, scikit-learn), containerization, CI/CD, and cloud or on-prem deployment pipelines
Experience with GPU utilization
Experience with real-time requirements regarding computational efficiency
Familiarity with safety engineering processes, risk assessment, and methods to assess and mitigate model bias and ethical risk
Excellent coding skills in relevant languages (e.g., Python, C++/Java as applicable), and software engineering best practices (testing, documentation, version control)
Strong communication and collaboration skills
ability to work across cross-functional teams and present technical results to stakeholders
What we offer:
Competitive base pay and variable compensation opportunities
Health insurance
Flexible spending accounts
Health savings accounts
Retirement savings plans
Life and disability insurance programs
Programs that provide for both paid and unpaid time away from work
Generous company match to your 401(k)
Industry-leading tuition assistance program
Fertility, adoption, and surrogacy benefits
Up to $10,000 gift match when you support your favorite nonprofit organizations