Stellaspire
Machine Learning Engineer
Skills
5 days ago
Share this opportunity
Share this opportunity to other talents of your network:
✓ Offer them a visibility boost with clients.
✓ Help your contacts find their next job.
Important information
Contract type:
Permanent
Location:
Karnataka, India
Work mode:
Onsite
Published on:
15 October 2026
What they need
Machine Learning Engineer
Full-Time | Bengaluru, Work from Office
Qualifying Degree: B.Tech from a Tier 1 Institute | Experience: 3+ years
About Us
Our client is building the first precision health platform for pets , a sensor-driven, AI-powered ecosystem that decodes the health signals dogs give off every day, the ones most people miss, and turns them into insight you can act on.
It starts with EverBowl, a clinical-grade device that reads hydration, intake, body temperature, eating behavior, and the sound of a bite , building toward a single daily wellness score. Paired with the app and Protect+, our insurance-rewards membership, we're helping pet parents move from guesswork to knowing. Calm. Confident. In control.
We're not building another pet gadget. Every signal we decode , acoustic, motion, thermal , depends on models that actually work in the field, not just in a notebook. That's the problem this role exists to solve.
About the Role
We're looking for a hands-on ML engineer to build and ship models across sensor-driven product ecosystem, working closely with the ML Lead on digital signal processing, computer vision, and time series problems. You're comfortable taking a model from an early prototype through to a reliable, production-deployed system.
What You'll Do
- Build and iterate on ML models for time series, audio signal, and sensor fusion problems, under the guidance of the ML Lead
- Build and maintain data preprocessing and feature engineering pipelines that prepare sensor data for training and inference at scale
- Package and deploy models into production, including on edge or embedded compute, with attention to latency and resource constraints
- Run structured experiments to evaluate model accuracy, generalization, and failure modes, and document findings clearly
- Support monitoring and retraining pipelines that track model performance and drift after deployment
- Work closely with firmware, hardware, and app teams to turn model outputs into clear, actionable product insight
You Might Be a Fit If…
- You have a B.Tech in Computer Science, Electrical Engineering, or related field from a Tier 1 institute (IIT, NIT, BITS Pilani, or equivalent) , mandatory
- You have 3+ years of applied machine learning experience
- You have a solid understanding of time series analysis and at least one of CNNs, RNNs, or signal processing techniques
- You're proficient in Python and at least one ML framework (TensorFlow or PyTorch)
- You've taken at least one model from prototype to a production or near-production deployment
- Bonus: experience with audio signal processing or accelerometer-based activity classification
- Bonus: familiarity with edge deployment of ML models on embedded compute
- Bonus: exposure to MLOps tools and practices
- Bonus: prior experience in IoT, wearables, or health-tech
Why Join Us?
- Ship models that run on real hardware, on real dogs , not just in a notebook
- Learn directly from the ML Lead while owning real pieces of the roadmap
- Take ownership early, with a direct line to the people building the rest of the product
- Join a small, fast-moving team building a category-defining, sensor-driven product
To Apply
Share your background, along with any models you've taken from prototype to production. Shortlisted candidates will complete a short assignment as part of our process.
Other offers great for you!
These companies are also looking for great profiles
Hito
ML Engineer
Freelance
Paris, France
Hybrid
Skills
2 months ago
Quick apply
Mobiskill
Machine Learning Engineer
500
Freelance
Remote
Top Recruiter
Skills
5 days ago
Quick apply
Theodo
Machine Learning Engineer / ML Engineer
480 - 580
Freelance
Paris, France
Hybrid
Skills
39 minutes ago
Quick apply