Honeywell Aerospace is a $10B+ SBG (Strategic Business Group) with 40,000 employees in over 125 domestic and international locations. We are a leading global aviation supplier designing, manufacturing, and distributing advanced electronic systems, products, and services to commercial, defense and space industries.
Join a team recognized for leadership, innovation and diversity
Honeywell is a Fortune 100 company with global sales surpassing $40B and has been one of Fortune’s Most Admired Companies for over a decade. Through innovation, the Company brings together the physical and digital world to tackle some of the toughest societal and business problems – making the world a more productive, safe, and sustainable place.
We’re looking for a new senior team member who is motivated by cracking tough challenges with data, trained in problem solving, and with an unending thirst for learning.
Have endless opportunities to progress your career as you develop new offerings that impact a wide range of industries, improve the quality of life, and truly change the world.
As a Machine Learning Engineer with Honeywell, this is your opportunity to develop machine learning models for computer vision applications to address unique and complex problems for the variety of breakthrough solutions.
- Design, develop and deploy experiments to improve efficiency of machine vision algorithms.
- Extend and enrich existing ML model pipelines for data ingestion, processing, training, deployment.
- Explore and visualize data for better understanding of outcomes of training experiments.
YOU MUST HAVE
- Master’s degree in Computer Science, Engineering, Applied Mathematics or related field.
- At least 3+ years practical experience in machine learning algorithm development within computer vision domain — key areas of interest include any of the following: object detection and instance segmentation, object tracking, activity recognition, multiple view geometry, 3D computer vision.
- At least 3+ years of experience programming in Python.
- PhD degree in Computer Science, Engineering, Applied Mathematics or related field.
- Experience with database management systems, data platforms (e.g. Streaming Data Platform, Kafka, Logstash, Teradata, Hadoop, etc.), and data formats (e.g. SQL, NoSQL, AWS S3, JSON, Redis, neo4j, etc.) for efficient ML feature extraction and data transformations.
- A strong understanding of big data concepts and knowledge of big data languages/tools.
- Exceptional data science skills, including a strong understanding of statistics, probability, and algorithms that enable you to quickly come up with solutions that combine multiple information streams.
- Experience in automation and build infrastructure in distributed environment.
- Previous experience moving prototypes to production environment and optimizing models in production environment.
- Ability to stay abreast of current and emerging technologies in support of new concept development.
- Result-driven, positive “can-do” attitude.
- Ability to work collaboratively with development/implementation staff through the design and build of new business processes and systems.