Senior Machine Learning Engineer II — Remote Aviation AI

Collins Aerospace; City of Albany (NY); Remote; USD 132,000 - 252,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Three weeks vacation

401(k) match

Tuition reimbursement

Student loan repayment

Life insurance

Disability coverage

Pet insurance

Home and auto insurance

Critical illness insurance

Group legal

ID theft protection

Parental leave

Wellness rewards

Teladoc visits

Childcare services

Job summary

Collins Aerospace in the United States is seeking a Machine Learning Engineer on the Aviation Intelligence team to build models powering the FlightAware Foresight product suite. This role offers a chance to work on large datasets and open-ended problems in a small team within a large organization.

You will contribute to model development, experimentation, and deployment, with opportunities to influence product direction and collaborate across disciplines while maintaining a focus on performance

Qualifications

• STEM degree with 5+ years of related experience or advanced degree with 3+ years.
• Authorized to work in the U.S. without sponsorship now or in the future.
• Strong knowledge of Python.
• Experience with TensorFlow/Keras or PyTorch.
• Experience with time-series, image, or video data.
• Ability to work within an agile development style.

Responsibilities

• Build next-generation ML models powering Foresight products.
• Improve existing models and aviation-related efficiency.
• Collaborate in a small team and contribute ideas for direction.

Skills

Python

Deep learning

Time series

Images / video data

Agile

Education

STEM degree + 5+ years

Tools

Kubernetes

AWS

GPU acceleration

Graph neural networks

Dagster/Airflow

Spark

Elasticsearch

Iceberg

Job description

Collins Aerospace in the United States is seeking a Machine Learning Engineer on the Aviation Intelligence team to build models powering the FlightAware Foresight product suite. This role offers a chance to work on large datasets and open-ended problems in a small team within a large organization.

You will contribute to model development, experimentation, and deployment, with opportunities to influence product direction and collaborate across disciplines while maintaining a focus on performance