
Machine Learning Engineer
3 days ago
InnerGize
is a consumer health and wellness platform that uses wearable patches to help people manage stress, sleep and mental performance. We are building algorithms that make our product more accurate and user-friendly.
We are looking for a
Machine Learning Engineer
with 2–4 years of experience to design and deploy
convolutional neural network (CNN) algorithms
that can detect and validate correct patch placement based on sensor data.
This position focuses on developing and refining CNN-based models from data collection through to deployment.
Job Requirements
:
- Design, train, and optimize CNN architectures for correct wearable patch placement detection using available sensor data.
- Build and maintain data pipelines for collection, labeling, augmentation, and validation of training datasets.
- Evaluate model performance and iterate to improve accuracy and robustness across users.
- Prepare models for deployment on mobile or embedded systems (optimizing for latency and size).
- Document experiments, models, and performance metrics clearly for internal teams.
- Collaborate with data, product and firmware teams to integrate model outputs into the InnerGize ecosystem.
Education Requirements:
- B.Tech / B.E. in Computer Science or a related field with specialization in Machine Learning, OR
- Master's / Ph.D. in Machine Learning, Data Science, or Applied Mathematics (preferred).
- Experience:
- 2–4 years of professional experience developing machine learning models, with a strong focus on CNN architectures.
- Technical Skills:
- Proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Demonstrated experience designing, training, and deploying CNNs for classification or regression tasks.
- Ability to work with real-world datasets, including preprocessing and augmentation.
- Familiarity with on-device or edge deployment tools such as TensorFlow Lite or ONNX (a plus).
- Soft Skills:
- Strong analytical and problem-solving skills.
- Good communication and documentation abilities.
- Comfortable working cross-functionally with other teams.
Preferable Skills:
- Exposure to time-series or sensor-based data.
- Understanding of mathematical/statistical models for signal behavior.
- Prior experience deploying models on constrained devices.
CTC:
₹12–18 LPA
, commensurate with experience and expertise.
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