Senior Machine Learning Architect

Senior Machine Learning Architect

Company : The Boeing Company

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!

Position 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

Basic Qualifications (Required Skills / Experience) :

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++)

Preferred Qualifications (Desired Skills / Experience) :

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

Drug Free Workplace :

Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies.

Pay & Benefits :

At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities.

The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work.

The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements.

Pay is based upon candidate experience and qualifications, as well as market and business considerations.

Summary pay range for Level 5 : $148,750 – $251,250

Summary pay range for Level 6 : $174,250 – $293,750

Language Requirements :

Not Applicable

Education :

Bachelor's Degree or Equivalent

Relocation :

This position offers relocation based on candidate eligibility.

Export Control Requirement :

This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a “U.S. Person” as defined by 22 C.F.R. §120.62 is required. “U.S. Person” includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee.

Safety Sensitive :

This is not a Safety Sensitive Position.

Security Clearance :

This position does not require a Security Clearance.

Visa Sponsorship :

Employer will not sponsor applicants for employment visa status.

Contingent Upon Award Program

This position is not contingent upon program award

Shift :

Shift 1 (United States of America)

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