Machine Learning Engineer at DentalMonitoring developing and improving ML models for orthodontic treatment solutions. Engage in deep learning and computer vision tasks within a hybrid work environment.
About the role
- Senior AI/ML Engineer designing and deploying AI/ML solutions for validation challenges at Micron. Working on machine learning models and optimization solutions to enhance product quality and validation efficiency.
Responsibilities
- Develop machine learning models for automated root cause analysis of validation and test failures
- Build predictive analytics to support failure detection, forecasting, and risk identification
- Design pattern-recognition techniques to identify failure signatures in historical validation data
- Develop dashboards and reporting tools that enable data-driven validation decisions
- Implement AI-driven test selection and prioritization approaches based on code change risk
- Develop methods to identify test coverage gaps, overlaps, and inefficiencies
- Contribute to optimization solutions that reduce test execution time while maintaining quality
- Develop AI-powered test generation solutions using requirements and code change data
- Build adaptive test execution capabilities informed by historical performance data
- Assist with integrating LLM-based capabilities into validation workflows where appropriate
- Work with firmware, hardware, and system teams to understand validation challenges
- Collaborate with validation engineers to translate domain knowledge into ML features
- Partner with platform and infrastructure teams to deploy and maintain AI/ML solutions
- Support adoption of AI tools through documentation, training, and team enablement
Requirements
- 4+ years of industry experience with a Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or a related technical field
- 5+ years of software development experience, primarily using Python
- Solid understanding of machine learning fundamentals, including model development, evaluation, and feature engineering
- Experience with ML frameworks such as scikit-learn, TensorFlow, PyTorch, or similar
- Experience building and deploying ML solutions in production or large-scale environments
Benefits
- Choice of medical, dental and vision plans
- Benefit programs that help protect your income if you are unable to work due to illness or injury
- Paid family leave
- Robust paid time-off program
- Paid holidays
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
AI/ML Engineer developing advanced solutions for federal client at Niyam IT. Focusing on AI/ML models and operational efficiency improvement in federal environments.
Senior Machine Learning Engineer at Capital Group, designing Generative AI systems to enhance investment processes. Collaborating with professionals to translate ideas into reliable, production - grade systems
Machine Learning Engineer focusing on MLOps and software engineering at flaschenpost, ensuring robust planning and operational success through ML products.
AI ML Engineer at global networking leader, shaping ML strategy and building high - performance systems. Innovating with AI technology to enhance network management and develop flagship products.
Senior Staff Machine Learning Engineer leading technical architecture for GEICO's AI Agent Platform. Driving innovation and enhancing productivity for internal associates and customers.
Staff Machine Learning Engineer developing the next generation of AI Agent OS and SDKs for GEICO. Key responsibilities include architecting scalable systems and implementing observability frameworks.
Senior Machine Learning Engineer at Bumble developing scalable AI systems for personalized user interactions. Leading machine learning model development and deployment from exploration to production.
Lead Machine Learning Engineer at Bumble shaping user connections through machine learning. Driving end - to - end AI solutions while mentoring engineers in a hybrid work environment.
Designing and operating cloud - based MLOps capabilities supporting analytical and generative AI models. Collaborating with data science and business teams for high - impact AI solutions.