Machine Learning Engineer

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)

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.

Experience with PyTorch
Experience with MLOps tools such as MLFlow
Knowledge of signal processing techniques
Machine Learning work in ultrasonic signals, audio signals, or another unconventional domain
Evidence of clear impact and growth in a fast-growing startup environment