AI/ML Engineer developing solutions in artificial intelligence for HPE. Responsible for conducting research, designing AI solutions, and mentoring team members.
CO
Hybrid Senior Lead, Machine Learning Engineer – Enterprise Platform Technology
Posted 2 months ago
About the role
- Senior Lead Machine Learning Engineer involved in the technical design, development, and implementation of ML applications. Part of an Agile team at Capital One optimizing and scaling ML solutions.
Responsibilities
- Participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
- Focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
- Perform ML engineering activities, including design, build, and/or deliver ML models and components that solve real-world business problems.
- Inform ML infrastructure decisions using knowledge of ML modeling techniques and issues.
- Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
- Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures to deliver optimized ML models at scale.
- Construct optimized data pipelines to feed ML models.
- Leverage continuous integration and continuous deployment best practices to ensure successful deployment of ML models and application code.
- Ensure all code is well-managed to reduce vulnerabilities, and that models are well-governed from a risk perspective.
Requirements
- Bachelor’s degree
- At least 8 years of experience designing and building data-intensive solutions using distributed computing
- At least 4 years of experience programming with Python, Scala, or Java
- At least 3 years of experience building, scaling, and optimizing ML systems
- At least 2 years of experience leading teams developing ML solutions
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field (preferred)
- Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (preferred)
- 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred)
- 3+ years of experience developing performant, resilient, and maintainable code (preferred)
- 3+ years of experience with data gathering and preparation for ML models (preferred)
- 3+ years of people management experience (preferred)
- 3+ years of experience building production-ready data pipelines that feed ML models (preferred)
Benefits
- Health insurance
- Performance based incentive compensation
- Cash bonus(es)
- Long term incentives (LTI)
- Comprehensive and competitive benefits
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Machine Learning Engineer focusing on modeling cancer cells and developing related tools. Collaborating with researchers and scientists to advance cancer treatment through ML.
Machine Learning Engineer II developing production - grade ML models for fraud detection at GEICO. Collaborating on system architecture and ensuring optimal performance of fraud assessment systems.
AI/ML Engineer III designing and architecting AI solutions at Hewlett Packard Enterprise. Collaborating with teams to drive innovation and tackle complex problems.
AI/ML Engineer deploying state - of - the - art AI models to solve real - world problems at Brain Co. Working in healthcare, government, and energy sectors for impactful results.
Trainer at WeAndTheMany facilitating learning by sharing experiences and creating interactive sessions. Engaging with students to enhance their skills and knowledge through dynamic teaching methods.
Machine Learning Manager leading experienced team to drive data - driven AI/ML solutions at Ford. Overseeing strategies for product development focused on analytics in various domains.
Software Engineer I developing machine learning models and applications at Smart Data Solutions. Collaborating to improve infrastructure and automate processes using AI technology.
Intermediate Machine Learning Engineer at Aviva Canada implementing ML pipelines with required collaboration in AI/ML Operations. Join a team dedicated to operationalizing ML models for optimizing solutions.
MLOps Engineer designing and maintaining cloud infrastructure for large - scale computer vision model training. Collaborating with Data Scientists and AI Engineers to streamline model development lifecycle.