AI Systems Engineer

Key Skills

Aartificial intelligence, AIOps, Analytical and Problem solving, C++, Continuous Integration & Continuous Delivery - CI/CD, DevOps, Effective communication skills, Java Programming, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Python Programming, PyTorch, Scikit-learn, TensorFlow

Job Description

The AI Systems Engineering team researches and develops solutions using model-based systems engineering, formal methods, planning, decision making, controls, machine learning, anomaly detection, computer vision, and failure analysis techniques for a variety of high impact real world problems in the aerospace, manufacturing, and defense industries.

We are looking for an AI Systems Engineer to help develop, deploy, monitor, and maintain ML/AI-based platforms and tools relevant to safety-critical AI-enabled systems.

You will get to develop state-of-art AI Systems tools and apply them to real world datasets at scale. Interact and learn from leading researchers on a variety of topics working at RTRC. Support for publishing results in top conferences. You will work with a small and focused team on implementing AI-based systems engineering tools for deployment of AI in safety-critical AI-enabled systems. You will get to work on challenging problems within the broad areas of AI/ML applications in aerospace and defense.

Role Overview

The AI Systems Engineer will be responsible for one or more of the following activities:

• Leverage your strong software engineering expertise and experience to develop robust solutions for real-world problems

• Collaborate with researchers on projects related to machine learning and artificial intelligence

• Algorithm development, software implementation, performance profiling and optimization for various kinds of AI/ML workloads

• AI Platform Development: Assist in design and development of AI/machine learning-based platforms for various safety-critical technical problems

• AI/ML Model Deployment: Assist in deploying AI/machine learning models into production environments

• AI/ML pipeline and model monitoring: Contribute to code development and tool rollout for monitoring and maintenance of model performance and infrastructure health

• Automation: Participate in the development and maintenance of automated AI systems pipelines

• Collaboration: Under guidance from project leads, collaborate with the domain experts to integrate machine learning models into production systems

• Documentation: Maintain documentation of AI platform processes and procedures

• Problem Solving: Assist in troubleshooting and resolving AI platform-related issues

• Research and stay updated on the latest trends and technologies in DevOps, MLOps, and AIOps

Required Qualifications

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field

• 5+ years of experience in software engineering, data engineering, or machine learning engineering

• Proficient in one or more programming languages, such as Python, Java, C++

• Proficient in working with AI frameworks and tools, such as TensorFlow, PyTorch, Scikit-learn

• Experience developing, training, and debugging ML pipelines for computer vision, natural language processing (NLP)

• Experience in working with cloud platforms, especially AWS and Azure

• Experience in working with CI/CD frameworks such as GitLab, Jenkins

• Experience in working with container and workload management frameworks such as Docker, Kubernetes, Airflow

• Experience in infrastructure as code technologies such as CloudFormation, Terraform, and Open Tofu

• Strong analytical and problem-solving skills

• Excellent communication and collaboration skills

• Ability to work independently and in a team environment

Preferred Qualifications:

• Deep expertise across a variety of DevOps, MLOPs, and AIOps tools and technologies

• Demonstrated experience in prototyping and shipping AI-based tools

• Experience in working with big data technologies, such as Hadoop, Spark, Kafka

• Experience in working with platforms such as DataBricks, Amazon Sagemaker, W&B (Weights and Biases), Kubeflow, SnorkelFlow, Labelbox, DVC, Doit, GreatExpectations

• Experience in working with DevOps tools such as Puppet, Ansible, Packer, Vagrant

• Experience with security-focused programming languages such as Rust, WebAssembly

• Experience developing, training, debugging, and maintaining ML pipelines for Large Language Models (LLMs), foundational models, time-series forecasting, anomaly detection

• Experience working with DOD and other govt. agencies

• Experience in open-source software development

• S. Person (U.S. citizen, permanent resident, refugee or asylee) or eligible to obtain necessary export authorizations required.

Education:

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.

Location

Hybrid: Berkeley, CA.

Requires advanced knowledge of work area typically obtained through advanced education combined with experience. May have practical knowledge of project

management. Practical to substantial knowledge of RTX projects, programs or systems with the ability to make enhancements and leverage in daily work.

Typically requires:

A University Degree or equivalent experience and minimum 5 years prior relevant experience, or An Advanced Degree in a related field and minimum 3 years experience

Engineering/Other Technical Positions:

Typically requires a degree in Science,Technology, Engineering or Mathematics (STEM) and a minimum of 5 years of prior relevant experience unless prohibited by local laws/regulations.

The salary range for this role is 77,000 USD - 163,000 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and key skills.

Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.

Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance.

This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.

RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.