Associate Artificial Intelligence and Machine Learning Developer

at  Boeing

At Boeing, we innovate and collaborate to make the world a better place. From the seabed to outer space, you can contribute to work that matters with a company where diversity, equity and inclusion are shared values. 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 an Associate Artificial Intelligence and Machine Learning Developer to join the team in either Seattle, WA; Mesa, AZ; or North Charleston, SC.
Boeing’s Enterprise Artificial Intelligence (AI) & Data team builds the singular AI & analytical data platform that serves as the foundation for Boeing’s AI capabilities. The platform’s cloud-based infrastructure and developer self-service design enable the democratization of AI and data at Boeing – allowing for development teams to perform data science and AI/Machine Learning (ML) workloads across the enterprise on accelerated timelines and at an enterprise-scale.
We are looking for a passionate and talented AI & ML Developer to join us in our mission to deliver a world-class AI platform experience to development teams throughout all of Boeing and to assist AI & data development teams towards accelerating their path to production and realizing business value. Our team works alongside data science and AI application development teams to assist in the operationalization of their AI/ML workloads, builds and maintains large cloud infrastructures and integrated technology stacks, and we also set architecture standards and guidance around Generative AI (GenAI) & Machine Learning Operations (MLOps) for the enterprise. As an AI & ML Developer for Enterprise AI & Data, you’ll have the opportunity to work with cutting-edge technologies on a wide variety of exciting use cases dealing with supply chain, smart manufacturing, and real-time aircraft operations!

BASIC QUALIFICATIONS (REQUIRED SKILLS/EXPERIENCE):

• 1+ years of experience with Go, Java, C/C++, Rust, or Python
• 1+ years of experience with database content management and database querying languages
• 1+ years of experience using SQL
• 1+ years of experience in Git
• Experience training machine learning models in a cloud computing environment such as AWS, Google Cloud Platform, Microsoft Azure, etc. and fundamental knowledge in MLOps

PREFERRED QUALIFICATIONS (DESIRED SKILLS/EXPERIENCE):

• 1+ years of experience in Data Science and building Artificial Intelligence (AI) & Machine Learning (ML) models
• 1+ years of experience developing ML training and serving pipelines using cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML) and/or commercial platforms (Dataiku, Databricks, MLFlow, ClearML, or alternative)
• 1+ years of experience in building AI models/solutions and 1 year(s) experience with one or more ML frameworks (Tensorflow, PyTorch, Scikit Learn, etc)
• 1+ years of experience in building RAG or prompt engineering solutions for use with large language models (LLMs) (such as GPT, Llama, Mistral, Gemini, etc) and/or models from repos such as Hugging Face
• 1+ years of experience developing both batch and streaming data pipelines with cloud provider tools (such as AWS Glue, GCP DataFlow, AWS Kinesis, GCP PubSub, etc) and/or commercial or open-source data processing tools (such as Informatica, Dataiku, Databricks, Airflow, Kafka, etc)
• 1+ years of experience building container applications (Docker, Kubernetes) and using CI/CD tools (GitLab CI, Jenkins, Circle CI, etc) to deploy in production cloud environments (AWS, GCP, Azure)

TYPICAL EDUCATION & EXPERIENCE:

Education/experience typically acquired through advanced technical education (e.g. Bachelor) and typically 2 or more years’ related work experience or an equivalent combination of technical education and experience (e.g. Master, 6 year’s related work experience, etc.).

• Develop, integrate, and support a single cloud platform architecture for AI & analytics products that simplifies and drives the productivity of data scientists, data analysts, machine learning developers, and analytics solutions developers throughout the company
• Develop the enterprise AI & ML platform, enabling compliant management of AI/ML models while accelerating deployment of ML models into production environments
• Consult AI development teams across the enterprise to assist in designing the appropriate cloud solution architecture for their proposed solution and subsequently get hands-on in order to develop the solution and make it a reality
• Provide on-going guidance and support to all AI & data development teams as they navigate their AI & analytics journey on the platform