Senior Machine Learning Engineer developing deep learning models for camera - based perception in autonomous trucks. Building robust camera models for safe and reliable autonomous driving.
About the role
- Machine Learning Engineer developing innovative computer vision solutions for defense and commercial applications. Collaborating with R&D on algorithms for detection, classification, and tracking capabilities.
Responsibilities
- Support development of computer vision and machine learning algorithms capable of detection, classifying, localizing, and tracking objects-of-interest from a group 1 UAV using the existing gimballed camera payload
- Write and test software to support the integration of machine learning algorithms into aircraft (such as autopilots, payloads, or other functional components) or other robotic systems.
- Explore and visualize data to gain an understanding of it, then identifying differences in data distribution that could affect.
- Implement Machine Learning systems and validate designs through a series of purpose-designed experiments.
- Create objectives and develop models that help to achieve them, along with metrics to track their progress.
- Perform analysis tasks using AeroVironment and industry developed tools.
- Managing available resources such as hardware, data, and personnel so that deadlines are met.
- Analyze the ML algorithms to solve a given problem and ranking them by their success probability. Performance when deploying the model in the real world; Verify data quality, and/or ensure it via data cleaning.
- Analyze the errors of the model and designing strategies to overcome them.
- Study and transform data science prototypes; Research and implement appropriate ML algorithms and tools.
- Select appropriate datasets and data representation methods; Run machine learning tests and experiments.
- Works on problems of moderate scope where analysis of situations or data requires a review of variety of factors. Exercises judgment within defined procedures and practices to determine appropriate action.
- Other duties as assigned.
Requirements
- BS in Computer Vision and Machine Learning is required or equivalent combination of education, training, and experience - with qualifications in Mathematics, Optimization, Computer Science/Engineering, Electrical Engineering, Aerospace, or Mechanical Engineering
- Minimum of 2 – 5 years' relevant experience
- Familiarity with C/C++ and Matlab required
- Familiarity with office software and computer-based productivity tools
- Demonstrated ability to troubleshoot complex systems
- Proficiency with a deep learning framework such as TensorFlow or Keras
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
- Expertise in visualizing and manipulating big datasets
- Proficiency with OpenCV
- Familiarity with Linux
- Ability to select hardware to run an ML model with the required latency
- Computational statistics
- Mathematical optimization
- Data mining
- Exploratory data analysis
- Predictive analytics
Benefits
- medical
- dental vision
- 401K with company matching
- a 9/80 work schedule
- paid holiday shutdown
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Senior Machine Learning Engineer at Disney designing machine learning models for self - healing infrastructure. Collaborating with cross - functional teams to enhance enterprise technology strategies.
Machine Learning Engineer at Capital One responsible for productionizing ML applications in Agile teams. Focused on ML architectural design, coding, and maintaining high availability of models.
Lead Machine Learning Engineer at Capital One focused on machine learning applications and systems. Collaborate with Agile teams to develop scalable solutions for business problems.
Machine Learning Systems Research Intern at Red Hat working on AI inference and model optimization techniques. Collaborating with experts in the field while gaining hands - on experience in applied ML research.
Senior Machine Learning Engineer focused on Machine Learning Ops for Autodesk software products. Building production infrastructures, ensuring AI - powered experiences, and collaborating with cross - functional teams.
Senior Machine Learning Engineer developing and deploying machine learning models for autonomous trucks. Collaborating with various teams to enhance safe and efficient decision - making in freight environments.
AI Engineer at PayPal designing, building, and deploying autonomous AI systems powered by LLMs. Collaborating across teams on AI engineering, distributed systems, and product development.
Machine Learning Engineer designing and deploying advanced training capabilities to support U.S. Navy operational readiness. Collaborate on machine - learning models to enhance combat system training environments.
Cloud MLOps Engineer supporting Data Science and Engineering teams by automating CI/CD pipelines and managing multi - cloud infrastructure for ML production.