Machine Learning Engineer

Responsibilities

• Design and build custom machine learning models from scratch for digital/audio signal processing and accelerometer data analysis
• Apply advanced techniques including time series analysis, CNNs, RNNs, GANs, LLMs, and low-rank adaptation
• Perform sophisticated data analysis and preprocessing for machine learning datasets
• Implement MLOps practices to streamline model deployment into production
• Monitor and optimize ML models for accuracy and efficiency
• Collaborate with product, engineering, and data science teams to integrate models into the product ecosystem
• Conduct research to drive innovation in machine learning and signal processing

Requirements

• Bachelors or Masters in Computer Science, Data Science, Electrical Engineering, or related field
• Minimum 6 years of relevant experience building custom ML models for signal processing
• Strong knowledge of CNNs, RNNs, GANs, LLMs, and low-rank adaptation
• Experience with MLOps and production model deployment
• Proficiency in Python and frameworks like TensorFlow or PyTorch
• Proven track record in audio signal analysis or accelerometer data analysis

Preferred Qualifications

• Experience in pet wellness or related industries
• Familiarity with IoT device data processing
• Knowledge of cloud computing platforms for ML deployment

About the Company

Hoomanely focuses on pet wellness technology, leveraging advanced machine learning and signal processing to enhance pet care products.