Founding Machine Learning Engineer
5 days ago
Experience
: years
Salary
: Confidential (based on experience)
Expected Notice Period
: 30 Days
Shift
: (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type
: Office (Bengaluru)
Placement Type
: Full Time Contract for 3 Months(40 hrs a week/160 hrs a month)
**(*Note: This is a requirement for one of Uplers' client - NA)
**What do you need for this opportunity?
Must have skills required:
embedded ML deployment, Neural Networks, Physics-informed learning, Data Engineering, C++, Data Science, Machine Learning, Python
NA is Looking for:****
As the Founding ML Engineer, you will develop core algorithms and models that transform raw magnetic and inertial signals into accurate, real-time location estimates. You will own the end-to-end ML stack, from denoising and map-matching to embedded deployment and work closely with hardware and field teams to close the loop between models and the real world.
Key Responsibilites
- Magnetic Signal Processing:
- Design and train denoising models across diverse environments and platforms.
- Map-Matching:
- Build pipelines to align live magnetic observations with prior maps for pose and position inference.
- Unified Modeling:
- Architect a model that fuses temporal magnetic data, inertial cues, and contextual priors with uncertainty bounds.
- Data Tooling:
- Create pipelines for collection, labeling, augmentation, and synthetic generation of trajectories.
- Evaluation & Deployment:
- Define metrics, run replays/A-B tests, and deploy on embedded devices.
- Collaboration & Documentation:
- Work with hardware/firmware teams and publish clear specs and studies.
Required Qualifications
- 2+ years in applied ML or strong research background with shipped systems
- Expertise in sequence modeling or sensor fusion (e.g., Transformers, SSMs, Kalman variants, diffusion-style denoisers)
- Experience building real-time inference systems (quantization, pruning, profiling)
- Strong skills in Python and one systems language (preferably C++)
- Practical experience with data collection, cleaning, and stress-testing
- Clear writing and ability to turn experiments into decisions
Preferred Qualifications
- Background in SLAM, map-matching, or PNT
- Edge/embedded ML deployment (Jetson, Qualcomm, ARM)
- Experience with time-series foundation models, self-supervised or contrastive learning
- Synthetic data, domain randomization, or physics-informed learning
- Familiarity with inertial sensors, magnetometers, or geophysics data
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
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