Design and implement machine learning models for defense infrastructure, leveraging deep learning frameworks and expertise in Python. Process massive streams of unstructured time-series data in real-time and deploy models in custom Kubernetes environments. Collaborate with data ingest teams to optimize hardware acceleration and low-level system performance.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Senior Machine Learning Engineer (Remote)
High-Growth Defense Startup
Up to $250,000 + Benefits
The Company
- My client is building next-generation situational awareness and telemetry platforms for critical defense infrastructure.
- They are transitioning from heavy government R&D into a highly agile, product-led operational model.
- The team operates fully remote, prioritizing engineering velocity and rigorous technical debate over corporate bureaucracy.
Why Join?
- You will be the foundational machine learning SME, defining the model architectures rather than inheriting legacy technical debt.
- Tackle extreme engineering constraints, processing unstructured telemetry across thousands of sensors at 30kHz.
- Work in an autonomous, tight-knit engineering culture where your technical opinions drive the roadmap.
- Escape the SaaS-wrapper ecosystem and build resilient, high-performance models for air-gapped and raw Kubernetes environments.
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The Role – A technical, hands-on position where you will:
- Architect, train, and optimize deep learning inference models entirely from scratch.
- Process massive streams of unstructured time-series data (RF, audio waveforms, telemetry) in real-time.
- Build a “mixture of experts” inference architecture to balance speed and classification confidence.
- Bypass managed cloud platforms to deploy robust models directly into custom Kubernetes infrastructure.
- Work closely with data ingest teams to optimize hardware acceleration (CUDA) and low-level system performance.
Essential Requirements
- U.S. Citizenship with the ability to obtain a U.S. Security Clearance.
- Deep expertise in Python and deep learning frameworks (PyTorch preferred over TensorFlow).
- Proven history architecting models for high-velocity time-series or unstructured data.
- Demonstrated ability to deploy models in non-managed, cloud-native environments (OCI, Docker, Kubernetes).
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What Will Make You Stand Out
- Systems programming proficiency (C/C++) for extreme performance optimization of Python modules.
- Previous experience operating within the defense sector, high-frequency trading, or critical infrastructure.
If you are interested in this role, please apply with your resume through this site.
Disclaimer
No terminology in this advert is intended to discriminate on the grounds of age, sex, race, religion or belief, disability, pregnancy and maternity, marriage and civil partnership, sexual orientation, gender, and/or gender reassignment, and we confirm that we are happy to accept applications from anyone for this role. Attis Global Ltd operates as an employment agency and employment business. More information can be found at attisglobal.com.
Keywords for Search (SEO):
Senior Machine Learning Engineer, ML Engineer, Deep Learning, PyTorch, CUDA, Time-Series Data, Telemetry, Signal Processing, Computer Vision, Model Architecture, AI Builder, C++, Kubernetes, K8s, Defense Tech.
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