Machine Learning Engineer creating and maintaining ML models for intelligent automation and forecasting at Create Music Group. Collaborating with multiple teams to implement AI - driven solutions.
About the role
- Senior AI/ML Engineer developing and deploying machine learning models for ADAS technology. Leading technical efforts and collaborating with diverse teams to enhance map content.
Responsibilities
- Our team is looking for a Senior AI/ML Engineer to be responsible for developing and deploying machine learning and statistical models and algorithms to support creating or enhancing map content for our ADAS/hands-free driving technology.
- It is expected that the person exerts technical leadership and guidance for the team in their area of expertise.
- This will include leveraging state-of-the practice tools and techniques to produce innovative solutions to complex problems.
- Design, build, and deploy predictive models and machine-learning algorithms to extract features, identify patterns, and classify outcomes using state-of-the-art frameworks and methods where practical.
- Create and enhance map data and related pipelines using cloud infrastructure and high-performance compute platforms.
- Analyze large datasets to discover trends and patterns.
- Present complex information using data visualization techniques.
- Conduct design, algorithm, notebook, and code reviews focused on machine learning and statistical analysis fundamentals, Python and relevant library best practices, and quality control and performance optimization principles.
- Document solution designs and development processes clearly and thoroughly.
- Collaborate with other ML Engineers, Data Scientists/Analysts, Software Engineers, and Product team representatives to design E2E solutions and strategies involving machine learning frameworks and big data workflows.
- Provide technical guidance and subject matter expertise to team members and stakeholders.
Requirements
- Master’s Degree in Engineering, Computer Science, Physics, Mathematics, or related quantitative field
- 6 or more years proficiency in one or more core analytical tools / suites / languages such as Python, PySpark, Spark, PyTorch, TensorFlow, and understand their limitations
- Minimum of 4 years of engineering/technical experience outside of a graduate school assistantship
- Demonstrable proficiency in statistical modeling and machine learning frameworks and tools
- Strong foundation in developing algorithms, data structures, and design patterns.
- Experience working with cloud infrastructure, high-performance compute systems, and parallel compute and data storage architectures.
- Experience leading projects and/or teams and managing customer requirements around scope, schedules, and deliverables.
Benefits
- From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions.
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