Defense / Edge Tech Lead at Jobgether – United States

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Defense / Edge Tech Lead in United States.

This role sits at the intersection of advanced AI, embedded systems, and defense-grade computing environments, where cutting-edge speech models must operate far beyond traditional cloud infrastructure. You will lead the effort to bring high-performance speech AI into edge, on-premises, and disconnected systems with strict constraints on latency, power, and compute. Working across hardware partners, defense ecosystems, and internal research teams, you will define how large-scale AI models are optimized, deployed, and secured in mission-critical environments. This is a highly technical leadership role requiring deep systems thinking and a strong ability to translate AI innovation into real-world, constrained deployments. You will influence both architecture and execution, ensuring models perform reliably on diverse hardware platforms. The environment is fast-moving, experimental, and deeply technical, with significant strategic impact on next-generation AI infrastructure.

• Define and lead the technical strategy for deploying speech AI models across edge, embedded, on-premises, and air-gapped environments.
• Architect and optimize model performance for constrained systems through quantization, pruning, distillation, and runtime engineering.
• Partner with hardware vendors and ecosystem players to ensure efficient model execution across chipsets, SDKs, and device architectures.
• Design and build edge runtime infrastructure, including deployment pipelines, OTA updates, model packaging, and telemetry systems.
• Implement security-hardened deployments for defense and government use cases, including encryption, secure boot, and tamper resistance.
• Benchmark and validate performance across multiple hardware platforms, ensuring reproducibility in latency, accuracy, and power efficiency.
• Collaborate with research and engineering teams to guide model design toward edge-friendly architectures from the outset.
• Provide technical leadership across cross-functional teams, setting standards, reviewing designs, and mentoring engineers working on edge systems.

• 5+ years of experience in systems engineering, embedded systems, edge AI, or performance-critical software development.
• Strong programming expertise in C, C++, and/or Rust with experience in low-level, resource-constrained environments.
• Proven experience optimizing machine learning models for edge deployment using techniques such as quantization, pruning, or distillation.
• Familiarity with inference runtimes and toolchains such as ONNX Runtime, TensorRT, TFLite, or vendor-specific SDKs (e.g., Qualcomm QNN/SNPE).
• Deep understanding of hardware-software interaction, including CPU/GPU/NPU architectures, memory systems, and power/performance tradeoffs.
• Experience with secure system design practices, including encryption, secure boot, and trusted deployment pipelines.
• Strong communication skills with experience acting as a technical interface to external partners and enterprise or defense stakeholders.
• Bonus: exposure to defense or government environments, real-time audio processing, or advanced ML optimization techniques.

• Comprehensive medical, dental, and vision coverage
• Mental health support and annual wellness stipend
• Unlimited PTO and flexible work arrangements
• Generous paid parental leave
• Retirement savings plan with company match (401k or local equivalent)
• Learning, training, and conference budget for professional development
• Home office and productivity stipends
• Life and disability insurance coverage
• Employee wellbeing programs, workshops, and AI-focused enablement initiatives