Embodied AI / ML Engineer — Sensor Data (On-site)

Tacniq; Singapore; On-site; SGD 42,000 - 66,000; Full time

Job description

[This role is based at our Singapore headquarters; overseas applicants are welcome but must work on-site.]

TacnIQ.ai is bridging AI and the physical world, building the foundation model for physical interaction, starting with tactile. We're creating a simple platform for engineers to build physical AI with any sensor, across wearables, robotics, and simulation. Our wearable data collection node is already live across five industries, logistics, construction, hospitality, e-commerce, and healthcare, feeding a pipeline that's turning raw sensor data into the foundation model nobody else has built.

This is a rare shot to work at the ground floor of a new category, on hardware and AI, on a problem that's genuinely unsolved, with a team that already has real-world traction to prove it.

Role Overview

This is a hands-on role for someone at the beginning of their AI/ML career who wants to work on real, novel problems rather than optimise dashboards. You will work directly under the Senior AI/ML Research Engineer, supporting experiments, building data pipelines, running training jobs, and evaluating models. You will also serve as an anchor and informal mentor for interns on the R&D track.

We believe in learning by doing. If you are someone who has trained models in your own time, contributed to open-source ML projects, or built something unusual with sensor data, we want to hear from you.

Key Responsibilities

Support model training, experimentation, and evaluation under senior direction.

Support data collection efforts, including sensor data gathering, labelling, and quality checks.

Build and maintain data pipelines for sensor data ingestion and preprocessing.

Run and document training jobs; track experiments and results systematically.

Assist with literature reviews and benchmarking of relevant architectures.

Onboard and support interns on the R&D track.

Requirements

Genuine curiosity about how models work and a drive to understand things at a mechanistic level.

Proficiency in Python and at least one ML framework (PyTorch preferred).

Comfortable running experiments, reading loss curves, and iterating.

Passion for the problem space. Sensor data, embodied AI, or robotics is a plus.

Fresh graduates welcome; strong internship or personal project experience matters more than years.

Build the category, not just join it. We're building the foundation model for physical interaction, starting with tactile, across wearables, robotics, and simulation.

Real traction, not just a vision. Already live across five industries: logistics, construction, hospitality, e-commerce, and healthcare.

Real ownership. Work across hardware, firmware, AI, and go-to-market with a clear path to leadership for those who deliver.

Lean, flat, and human. Flexible by design, transparent by default, genuinely invested in your wellbeing and anyone can make a difference.

TacnIQ.ai welcomes applicants from different educational, professional, and personal backgrounds.

If the role interests you but your experience does not match every requirement, we still encourage you to apply. What matters most is your ability to learn, build, communicate, and take ownership.