# Machine Learning Engineer, Detection and Tracking at Helsing

> United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Ahelsing%3A4953562101 (read 2026-11-07).

## Facts (observed)

- Company: [Helsing](https://alderhq.app/companies/helsing)
- Location text: Washington, DC; Washington, DC
- Where it can be done from (inferred): United States (evidence: "Location: Washington, DC; Washington, DC")
- Posted: 2026-08-18 (81 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://helsing.ai/jobs/4953562101?gh_jid=4953562101
- Skills listed (inferred): Python, Rust, C++, PyTorch, LLMs, Distributed systems

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (Washington DC, n 24): p25 $156k, median $173k, p75 $211k
- Licensed UK sponsor: registered as "Helsing Limited" (checked 2026-11-03, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers))

## Description (the employer's text)

### Who we are

Helsing develops artificial intelligence-enabled capabilities to protect and defend democracies. We build Altra, an AI-powered drone software platform, and HX-2, our autonomous drone. We are growing our US operations, cultivating an ambitious and committed team of mission-driven professionals to apply their skills to solve challenging problems.

### 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
- U.S. citizenship required
### 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
### Join Helsing and work with world-leading experts in their fields

Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns

The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world

Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defense industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Ahelsing%3A4953562101 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.