Senior Machine Learning Architect

Boeing•Seattle, WA

4d•$148,750 - $293,750

About The Position

The Boeing Company is currently seeking a Senior Machine Learning Architect to join the team in Seattle, WA; Arlington, VA; Auburn, WA; Berkeley, MO; Chicago, IL; Colorado Springs, CO; El Segundo, CA; Englewood, CO; Everett, WA; Hazelwood, MO; Houston, TX; Huntington Beach, CA; Huntsville, AL; Kent, WA; Long Beach, CA; Mesa, AZ; Miami, FL; North Charleston, SC; Plano, TX; Portland, OR; Renton, WA; Ridley Park, PA; Saint Charles, MO; San Antonio, TX; Seal Beach, CA; Titusville, FL; or Tukwila, WA. We are looking for a talented and experienced Senior Machine Learning Architecture leader to join our dynamic team. The ideal candidate will play a pivotal role in leading, designing and implementing scalable machine learning systems and architectures that empower our organization to make informed, data-driven decisions. As a Machine Learning Architecture leader, you will collaborate closely with cross-functional teams to thoroughly understand business requirements and translate them into high reliable solution designs. You will then lead highly scalable, secure, and cost-effective solutions tailored to address specific business challenges. This role demands a deep understanding of cloud, data and machine learning technologies, along with a proven track record in developing repeatable and reusable architecture frameworks. Join us in shaping the future of our cloud and data strategy!

Requirements

Bachelor’s degree or higher
5+ years of experience with AI/ML technologies, frameworks, models and ensembles
5+ years of experience with Pytorch, SciKit Learn, Tensorflow, or similar backend frameworks
5+ years of experience with Kubernetes, Docker containers, and Ansible
5+ years of experience with data engineering and data pipelines for On-Prem cloud, hybrid data models and data warehouses
5+ years of experience with DevOps software including Gitlab, Ansible, Terraform, Jira, Azure DevOps Pipelines, GitHub, AWS CodeBuild, AWS CodePipelines, AWS CodeGuru
5+ years of experience with software programming/scripting (such as Python, Unix/Linux type batch scripting, FORTRAN, C / C++)

Nice To Haves

10 or more years' related work experience or an equivalent combination of education and experience
5+ years of experience in the manufacturing or aviation domain
5+ years of experience with big data technologies and data engineering practices
Experience in multi-cloud and hybrid AI architecture
Experience with generative AI, NLP, computer vision, or reinforcement learning
Experience with CI/CD pipelines, DevOps practices and containerized deployments
Experience with fine-tuning and optimization approaches (LoRA / QLoRA, PEFT, parameter-efficient training), and cost/performance tradeoffs across CPU/GPU/accelerators
Experience with open-source ML projects or publications in relevant fields

Responsibilities

Define the strategy to build highly reliable and scalable ML and AI solutions that align with the organization’s business goals and objectives
Lead the creation and implementation of scalable, robust, and high-performance ML architectures including MLOps, AIOps leveraging cloud native services (AWS, Azure, GCP) and open-source frameworks
Design, build, and optimize machine learning models, ensuring accuracy, efficiency, and scalability
Collaborate with data engineers, data scientists, software developers, and DevOps teams to integrate ML models into production systems
Assess and recommend ML tools, frameworks, and platforms to deliver business value and foster innovation
Monitor and optimize ML models and systems for latency, throughput, and cost-efficiency in production
Provide technical guidance to ML engineers and data scientists including documenting standards and best practices
Ensure ML systems adhere to ethical guidelines, data privacy regulations, and industry standards
Design and development of Generative AI and AI use cases (LLMs, RAG, Agentic, multi model AI, fine tuning. Vector databases and prompt engineering)
Lead organizational change for the adoption of new platforms, machine learning tools and analytics workflows
Own all communication and collaboration channels pertaining to strategy and assigned projects, including regular stakeholder, senior leadership and cross-team updates
Establish working relationships with vendors (Technology and Consulting), partners and cross teams and holding them accountable