MLOps Software Engineer

Key Skills

Aartificial intelligence, AngularJS, Apache Airflow, AWS, Azure, Cloud computing, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, Database, DevOps, Docker, Git, GoLang, Google Cloud Platform (GCP), Keras software library, Kubeflow, Lambda, Leadership, Linux Operating system, Machine learning techniques, MLflow, MLOps tools, NoSQL, Perl Programming, Postgres, Python Programming, PyTorch, R Programming, REDIS, Ruby on Rails, Scikit-learn, Software Development, Spark Core, SQL, TensorFlow

Job Description

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.

Boeing Enterprise Software AI/ML Center (BEAC) is seeking MLOps Software Engineers (Associate Level and Mid-Level).

As a Software Engineer for our MLOps team, you will be responsible for designing, building, and maintaining the foundational infrastructure environments and tool chain that support our Machine Learning Operations (MLOps) services.

You will work closely with our data scientists, software engineers, and DevOps team to ensure that our MLOps services are reliable, scalable, and performant. Your primary goal is to help the team deliver high-quality MLOps services to our consumers by leveraging Kubernetes and other related technologies.

The locations available for this position are listed below:

Huntington Beach, California, El Segundo, Caliornia, Long Beach California, Arlington, Virginia, Fairfax, Virginia, Herndon, Virginia, Berkeley, Missouri, Hazelwood, Missouri, and Charleston, South Carolina.

Position Responsibilities:

• Design, build, and maintain solutions that support our MLOps services on cloud (AWS, Azure, GCP)
• Collaborate with the data science, engineering, and DevOps teams to ensure that our MLOps services are integrated with the infrastructure
• Automate the deployment, scaling, and monitoring of MLOps services using Kubernetes and related technologies such as Helm, Istio, and Prometheus
• Implement security and compliance controls MLOps services
• Optimize the performance and reliability of MLOps services through monitoring, logging, and performance testing
• Develop and maintain documentation, training materials, and best practices for the solution
• Collaborate with other teams and stakeholders to ensure that MLOps services meet their requirements and expectations

This position is hybrid. This means that the selected candidate will be required to perform some work onsite at one of the listed location options. This is at the hiring team’s discretion and could potentially change in the future.

This position must meet export control compliance requirements. To meet export control compliance requirements, a “U.S. Person” as defined by 22 C.F.R. §120.15 is required. “U.S. Person” includes U.S. Citizen, lawful permanent resident, refugee, or asylee.

To be considered for this position you will be required to complete a technical assessment as part of the selection process. Failure to complete the assessment will remove you from consideration.

Basic Qualifications (Required Skills/Experience):

• Bachelor, Master or Doctorate of Science degree from an accredited course of study, in engineering, computer science, mathematics, physics or chemistry
• 1+ years of experience in DevOps
• 1+ years of experience developing software products in a cloud computing environment e.g. Azure/AWS/Google Cloud
• Experience with Docker
• Experience with technologies such as Kubernetes, Istio, Rancher, Git, Helm, Ansible, Chef, Docker, Prometheus, Grafana, and AppDynamics
• Experience working with Java, Python, Go Perl or Ruby
• Experience with Linux
• Experience in Data Science
• Experience with Terraform

Preferred Qualifications (Desired Skills/Experience):

• 3 or more years' related work experience or an equivalent combination of education and experience
• Experience with MLOps Frameworks like ClearML, Kubeflow, MLFlow, Airflow etc
• Experience in using AWS, MS Azure or GCP services.
• Experience in angular
• Experience in Postgres, Redis, GCP, Kafka, Python, R, SQL and NoSQL Databases, Spark, Scikit-Learn, Keras/TensorFlow, PyTorch, AWS Cloud, Lambda & Step functions, Docker, CI/CD Pipelines, Git, and developing APIs
• Experience building and scaling systems both on premise and the cloud
• Experience in developing AI/ML Platforms
• Experience with building ML infrastructure, writing production level code, & deploying Machine Learning models
• Strong technical leadership skill and proven experience architecting, developing and deploying internet-scale, distributed, and critical services
• Experience working on complex problems and systems where scalability and performance

Typical Education/Experience:

Associate Level (Level 2): Education/experience typically acquired through advanced technical education from an accredited course of study in engineering, computer science, mathematics, physics or chemistry (e.g. Bachelor) and typically 2 or more years' related work experience or an equivalent combination of technical education and experience (e.g. Master). In the USA, ABET accreditation is the preferred, although not required, accreditation standard.

Mid-Level (Level 3): Education/experience typically acquired through advanced technical education from an accredited course of study in engineering, computer science, mathematics, physics or chemistry (e.g. Bachelor) and typically 5 or more years' related work experience or an equivalent combination of technical education and experience (e.g. PhD, Master+3 years' related work experience). In the USA, ABET accreditation is the preferred, although not required, accreditation standard.

Relocation: This position offers relocation based on candidate eligibility.

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.

Shift: This position is for 1st shift.

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.

Please note that the salary information shown below is a general guideline only. Pay is based upon candidate experience and qualifications, as well as market and business considerations.

Summary pay range:

Summary pay range for Associate Level:

• California and Virginia: 90,950 – 123,050
• Missouri and South Carolina: 85,000 – 115,000
• Summary pay range for Mid-Level:
• California and Virginia: 112,200 – 151,800
• Missouri and South Carolina: 104,550 – 141,450

Export Control Requirements: U.S. Government Export Control Status: If the successful candidate is not a “U.S. Person“ (as defined by 22 C.F.R. § 120.15 “U.S. Person” includes U.S. citizens, lawful permanent residents, refugees, or asylees) and the position requires access to export-controlled data, an appropriate export authorization by the U.S. Government may be required prior to such access. Employment, and the continuity of employment of non-U.S. persons, is contingent upon the company’s ability to secure and maintain the necessary export control authorization.