Date Posted:
2026-08-21
Country:
United States of America
Location:
US-CA-REMOTE
Position Role Type:
Remote
U.S. Citizen, U.S. Person, or Immigration Status Requirements:
Must be authorized to work in the U.S. without the company's immigration sponsorship now or in the future. The company will not offer immigration sponsorship for this position. The company will not seek an export authorization for this role.
Security Clearance Type:
None/Not Required
Security Clearance Status:
Not Required

As a Machine Learning Engineer on the Aviation Intelligence team, you will be building our next generation of Machine Learning models that will become new Foresight products, improving our existing models, and through this work, improving the operational efficiency of the world's largest airlines and airports..

We're a small team inside a large org, and this role is meant to grow into someone who brings ideas to the table, not just executes on them.

Within Aviation Intelligence, FlightAware's Predict crew builds state-of-the-art machine learning systems that leverage years of historical data and hundreds of millions of examples in order to build models for computing runway landing times, gate arrival times, taxi durations, and more. The results of these models power the FlightAware Foresight product suite, which streams live predictive aviation data to major customers in industry.

Here's why you might like it: the datasets are genuinely very large, so you get to leverage niche technologies for large datasets and get to flex your math/stats skills from time to time. Performance and efficiency aren't nice-to-haves here, they're fun problems. Much of what we work on is open-ended - and "can this even be solved," is a question that one must enjoy trying to answer. Improvements in our products directly improve the status quo for aviation around the world: airlines and airports run on our predictions, so real people catch flights they'd otherwise miss and skip delays they'd otherwise sit through - without ever knowing your work is why. You don't get many shots at impacting an entire mode of transportation. This is one of them.

Qualifications You Must Have:

• Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and minimum 8 years prior relevant experience or an Advanced Degree in a related field and minimum 5 years of experience
• Must be authorized to work in the U.S. without sponsorship now or in the future. RTX will not offer sponsorship for this position.
• Strong knowledge of Python
• Experience with deep learning frameworks: Tensorflow/Keras or PyTorch
• Experience with complex data types: time series, image, video, etc.
• Ability to work within an agile development style

Qualifications We Prefer:

• Experience with Kubernetes, AWS, and GPU acceleration.
• Experience with graph neural networks
• Experience with weather, or other geospatial, datasets
• Experience with observability stacks (Prometheus, Grafana, Thanos, etc.).
• Familiarity with Dagster, Airflow or other modern ETL orchestration tools.
• Familiarity with Iceberg, Spark, Elasticsearch and other large-scale data processing systems.
• Experience working in hybrid infrastructure environments (cloud + on-prem Kubernetes).

What We Offer:

Some of our competitive benefits package includes:

• Medical, dental, and vision insurance
• Three weeks of vacation for newly hired employees
• Generous 401(k) plan that includes employer matching funds and separate employer retirement contribution, including a Lifetime Income Strategy option
• Tuition reimbursement program
• Student Loan Repayment Program
• Life insurance and disability coverage
• Optional coverages you can buy pet insurance, home and auto insurance, additional life and accident insurance, critical illness insurance, group legal, ID theft protection
• Birth, adoption, parental leave benefits
• Ovia Health, fertility, and family planning
• Adoption Assistance
• Autism Benefit
• Employee Assistance Plan, including up to 10 free counseling sessions
• Healthy You Incentives, wellness rewards program
• Doctor on Demand, virtual doctor visits
• Bright Horizons, child and elder care services
• Teladoc Medical Experts, second opinion program
• And more!

Please ensure the role type (defined below) is appropriate for your needs before applying to this role.

Remote: Employees who are working in Remote roles will work primarily offsite (from home). An employee may be expected to travel to the site location as needed.

As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.

The salary range for this role is 132,400 USD - 251,600 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.