Machine Learning Engineer, Gecko Robotics

• 5+ years of engineering experience, with at least 3+ years in a dedicated machine learning role
• Practical knowledge of machine learning algorithms and frameworks suitable for time-series analysis and anomaly detection in signal data
• Ability to read and implement ML papers
• Knowledge of at least 1 machine learning framework (i.e. PyTorch) and has seen at least one ML model in production
• Familiarity with MLOps concepts
• A strong sense of intellectual curiosity, and the desire to dive deep into exploratory projects alongside production ready deployments
• Preference for projects with high ownership, and the ability to work effectively both autonomously and on teams
• Desire to have a high impact at a fast-moving startup as a key contributor on a new project and fast-growing team
• Exceptional communication skills and commitment to receiving and providing continuous feedback
• Bachelor’s degree in Computer Science or closely related field (or equivalent experience)

Desirable

• As a Machine Learning Engineer at Gecko, you will be working with Gecko’s unique dataset to develop and deploy machine learning models to solve critical business problems
• You will work deeply on problems such as: classifying valid vs. invalid signals; taking accurate measurements from valid signals; and identifying damage mechanisms such as cracks, corrosion, or laminations across a large collection of signals
• Gecko owns a growing repository of mechanical integrity data, including large volumes of ultrasonic, imagery, and other data points concerning the integrity of critical infrastructure assets worldwide
• Gecko is expanding our Machine Learning team to better leverage the vast data store we have collected over time
• This is a chance to be one of the first dedicated engineers in an area we expect to grow significantly over the next few years, within a space that is ripe for innovation and solving problems in a way they haven’t been attempted before
• Develop novel (supervised and unsupervised) ML models to help solve important business problems, becoming an expert in unique domains like ultrasonic digital signal processing for non-destructive testing
• Roll out models to production by developing integrations with mission critical analytical tools and building the necessary ML Ops infrastructure to support high quality iteration
• Help Gecko identify new problems we could tackle with AI/ML (such as defect detection, automated repair planning, and more) and help cultivate necessary training sets to start solving those problems