Machine Learning Engineer (Onsite- Bangalore)

Experience: 3.00 + years
Salary: INR 2500000-3500000 / year (based on experience)
Expected Notice Period: 7 Days
Shift: (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type: Office ()
Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: A pet health-tech startup)
(*Note: This is a requirement for one of Uplers' client - A pet health-tech startup)
What do you need for this opportunity?
Must have skills required:
CNNs, Firmware, Hardware, HealthTech, Rnn, IoT, ML framework, retraining pipelines, Wearables, Data Modelling, Machine Learning, Python
A pet health-tech startup is Looking for:
Machine Learning Engineer
About Us
At HM, we''re 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 HM 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 HM''s 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
How to apply for this opportunity?
Step 1: Click On Apply! And Register or Login on our portal.
Step 2: Complete the Screening Form & Upload updated Resume
Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
About Uplers:
Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.
(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).
So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Work arrangement
No