Machine Learning Engineer I
Role details
Job location
Tech stack
Job description
As a Machine Learning Engineer, you will be a hands-on leader tasked with deploying machine learning models in creative ways while working with highly cross-functional teams to make power tool solutions that change the lives of our users. You will act as a technical expert in the creation and execution of these concepts into products, supporting the team through implementation, validation, and transfer to production.
Requirements
Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time., This role requires excellent problem-solving skills, critical thinking, and the ability to work well under pressure in a dynamic environment. You will leverage strong technical communication skills and fundamental project management abilities to ensure clarity and alignment across teams. Additionally, you will demonstrate a strong sense of ownership for projects and tasks, with a clear understanding of how they connect to broader initiatives., * Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
- Completed course work or specialization in Machine Learning and/or Data Science
- Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization)
- Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision
- Proficient developing and debugging code in Python
- Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)
- Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)
- Sold mathematical foundation in statistics, linear algebra, calculus and optimization
- Ability to travel up to 10% of the time (domestic and international).
Other TOOLS you may have (Preferred):
- Master's degree or PhD in Machine Learning or related field
- At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field are preferred
- Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
- Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
- Experience working with modern software development tools and version control tools