Applied ML Engineer — Detection & Tracking on Edge

Fdetimes; Washington (District of Columbia); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Insurance coverage

Remote or hybrid work

Paid time off

Job summary

Helsing is seeking an experienced ML/CV engineer to own detection and tracking models powering its Altra platform. You will train, tune, and deploy models using US-specific datasets and manage the full lifecycle from data curation to edge deployment.

You will work on YOLO/DETR/Faster R-CNN architectures, develop multi-object tracking pipelines, and optimize for SWaP-constrained hardware. Citizenship in the US is required.

Qualifications

• 5+ years of experience in applied machine learning or computer vision.
• Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's or PhD strongly preferred.
• Production experience training and deploying object detection models — not just research or academic projects.
• Proficient in Python and PyTorch or a comparable deep learning framework.
• Strong intuition for data quality; you can look at annotated datasets, training curves, and evaluation metrics and know what's wrong.
• Have experience with the full model training lifecycle: data curation, annotation management, training, evaluation, and deployment.
• Experience optimizing models for deployment on SWaP-constrained and edge platforms (TensorRT, ONNX, quantization).
• Understand multi-object tracking and have implemented or worked with tracking algorithms in practice.
• Can read and contextualize scientific papers in computer vision and apply findings to production systems.
• U.S. citizenship required.

Responsibilities

• Training and fine-tuning detection models (YOLO, DETR, Faster R-CNN, and similar architectures) on mission-specific datasets.
• Implementing and improving multi-object tracking pipelines (SORT, DeepSORT, ByteTrack, or similar).
• Evaluating model performance: analyzing metrics, diagnosing failure modes, and iterating on data and model improvements.
• Managing the data pipeline end-to-end: assessing raw data, coordinating annotation, curating datasets, and implementing augmentation strategies.
• Optimizing models for deployment on SWaP-constrained and embedded platforms (quantization, pruning, TensorRT, ONNX export).
• Collaborating with systems engineers to integrate models into the broader Altra platform.
• Working across sensor modalities as needed, including electro-optical, infrared, and other imaging sources.

Skills

Applied ML

Computer Vision

Python

PyTorch

Data Quality

Model Lifecycle

Edge Deployment

TensorRT

ONNX

Education

Bachelor's degree

Master's/PhD preferred

Tools

YOLO

DETR

Faster R-CNN

SORT

DeepSORT

ByteTrack

ONNX export

Job description

Helsing is seeking an experienced ML/CV engineer to own detection and tracking models powering its Altra platform. You will train, tune, and deploy models using US-specific datasets and manage the full lifecycle from data curation to edge deployment.

You will work on YOLO/DETR/Faster R-CNN architectures, develop multi-object tracking pipelines, and optimize for SWaP-constrained hardware. Citizenship in the US is required.