The ideal candidate will have a solid background in applying machine learning to Digital Signal

Processing, particularly in audio signal analysis and accelerometer data analysis. This role involves

developing innovative ML models, including CNNs, RNNs, GANs, and leveraging techniques such as LLMs

and low-rank adaptation for enhancing our product offerings. The successful candidate will also be

proficient in MLOps practices and deploying ML models into production environments.

Key Responsibilities:

1. Custom ML Model Development: Design and build custom machine learning models from

scratch, tailored to specific applications in digital and audio signal processing, and accelerometer

data analysis. The ideal candidate will have published papers or demonstrable customized model

custom built for specific problem domains.

2. Advanced ML Techniques: Apply advanced machine learning techniques, including time series

analysis, CNNs, RNNs, GANs, LLMs, and low-rank adaptation, to solve complex problems in pet

wellness technology.

3. Data Analysis and Processing:



Perform sophisticated data analysis and preprocessing to prepare

datasets for machine learning applications.

4. MLOps and Model Deployment: Implement MLOps practices to streamline the deployment of

machine learning models into production, ensuring scalability, performance, and reliability.

5. Performance Optimization: Continuously monitor and optimize ML models to improve accuracy

and efficiency.

6. Cross-functional Collaboration: Work closely with product development, engineering, and data

science teams to integrate ML models into Hoomanely Inc.’s product ecosystem.

7. Research and Innovation: Stay abreast of the latest developments in machine learning and

signal processing to drive innovation within the company.

Qualifications:

● Bachelors/Masters in Engineering in Computer Science, Data Science, Electrical Engineering, or a

related field with a focus on machine learning. Preferably from a top

📌 Hoomanely - Machine Learning Engineer (Bengaluru)
🏢 NextHire
📍 Bengaluru