Machine Learning Engineer, Detection and Tracking

Helsing; Washington (District of Columbia); Hybrid; USD 100,000 - 130,000; Full time

Benefits offered by this job

Generous compensation package

Flexible paid time off

Remote and/or hybrid work options

Job summary

Helsing in Washington DC seeks an experienced applied machine learning professional to own detection and tracking models. You'll manage model lifecycle from training to deployment, working with various architectures and datasets.

Ideal candidates will have 5+ years in machine learning, a relevant Bachelor's or higher degree, and hands-on experience with object detection models. Benefits include a generous compensation package, flexible time off, and remote or hybrid work options.

Qualifications

• 5+ years of experience in applied machine learning or computer vision.
• Production experience training and deploying object detection models required.
• Experience optimizing models for deployment on SWaP-constrained platforms.

Responsibilities

• Manage the full model lifecycle including training, evaluation, and deployment.
• Train and fine-tune detection models on mission-specific datasets.
• Collaborate with systems engineers to integrate models into the broader platform.

Skills

Applied machine learning

Computer vision

Python

PyTorch

Model optimization

Education

Bachelor's degree in Computer Science or related field

Master's or PhD in a related field

Tools

TensorRT

ONNX

CVAT

Label Studio

Job description

The role

You will own the detection and tracking models that power Helsing's products — training, tuning, and deploying models against US-specific datasets. This is an applied ML role: you won't be writing research papers, but you will be expected to have strong intuition for model performance, data quality, and the practical trade-offs involved in getting detection and tracking systems to work reliably in production. You will manage the full model lifecycle — from assessing and curating training data through annotation, training, evaluation, and deployment to edge platforms.

The day-to-day

• 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

You should apply if you

• Have 5+ years of experience in applied machine learning or computer vision
• Have a Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's or PhD strongly preferred
• Have production experience training and deploying object detection models — not just research or academic projects
• Are proficient in Python and PyTorch or a comparable deep learning framework
• Have 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
• Have 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
• Are a U.S. citizen with an active security clearance or the ability to obtain one

Nice to have

• Strong proficiency in Rust or C++ for production model deployment and optimization
• Experience with multiple sensor modalities — particularly infrared or thermal imaging
• Familiarity with MLOps tooling: experiment tracking (MLflow, Weights & Biases), dataset versioning, model registries
• Experience with annotation tools and workflows (CVAT, Label Studio, or similar)
• Background in computer vision beyond detection — segmentation, pose estimation, activity recognition
• Experience with simulators, emulators, or synthetic data generation for training and evaluation
• Experience deploying models on GPU-accelerated embedded platforms (NVIDIA Jetson, similar)
• Background in defense, intelligence, or other mission-critical environments

What we offer

• A focus on outcomes, not time-tracking

• A generous compensation and benefits package (in addition to base salary) that includes, but may not be limited to, insurance coverage (medical and travel), flexible paid time off, paid holidays, and remote and/or hybrid work available depending on position. All compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated or superseded from time to time.

Helsing is an Equal Opportunity Employer. We will consider all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, genetics, or any other characteristic protected by applicable federal, state, or local law. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.