Omen is developing proprietary sensing hardware to create a dataset which will train the world’s most accurate predictive model that can predict and prevent errors and breakdowns in heavy equipment. Omen has raised $1.7m in pre-seed led by Caffeinated Capital with other investors including; Pareto Holdings, Cory Levy, 640 Oxford, Genius Ventures, Karmen Ventures, Mute Ventures, LMNT Ventures, and Backwards Capital.

Basic Qualifications

Proven experience in developing machine learning and deep learning models, preferably with time series sensor data
Strong proficiency in Python and ML frameworks e.g. PyTorch, Tensorflow
Experience with data analysis, including time-series data, sensor data, and signal filtering and processing
Solid understanding of data preprocessing, feature extraction, and model evaluation techniques
Familiar with software development standard methods/collaborations
Sufficient SW skills to run large ML training jobs efficiently on a distributed backend with large volume of data

Nice to have

Background in physics
Experience with low power/low data embedded systems
Experience developing production data processing pipelines for real products.

Responsibilities

In this role, you will be at the forefront of developing ML algorithms for machine health sensing applications and ensuring the efficient evaluation of these models to be in production at scale
You will be responsible for measuring model performance and consistent incremental improvements
You will be delivering solutions on time and with high quality standing up to the standards considering a customer facing product
Focus on projects with clear path to production value and customer impact

Benefits

Lead ML engineering efforts at small, well-funded early stage tech company
Company is open to alternative/flexible work hours and location
Total compensation includes cash, healthcare, and equity †
Unlimited access to a 3 ton mini-excavator!

Omen AI

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Sensing ML Engineer