Building foundational AI for speech transcription and understanding.
Defense – Edge Tech Lead
Location
United States
Posted
38 days ago
Salary
$195K - $260K / year
Seniority
Senior
Job Description
Defense – Edge Tech Lead
Deepgram
• Lead the technical strategy for edge deployment of Deepgram's STT and TTS models, defining the architecture for on-device, on-premises, and air-gapped inference across diverse hardware targets. • Optimize models for edge and embedded platforms, driving quantization, pruning, distillation, and runtime optimization to meet strict latency, memory, and power constraints. • Partner with Qualcomm, Motorola, and other hardware vendors to ensure Deepgram models run efficiently on their chipsets, collaborating on SDK integration, performance benchmarking, and joint go-to-market. • Support defense customer requirements through AWS NatSec partnerships, translating mission requirements into engineering deliverables and ensuring Deepgram's solutions meet the unique demands of government environments. • Design and build edge runtime infrastructure, including model packaging, deployment pipelines, OTA update mechanisms, and telemetry for devices operating in low-connectivity or disconnected environments. • Harden deployments for security-sensitive environments, implementing secure boot chains, encrypted model storage, tamper detection, and audit logging appropriate for defense and government use cases. • Benchmark and validate performance across target hardware platforms, establishing repeatable test suites for latency, accuracy, power consumption, and resource utilization. • Collaborate with Research and Engine teams to influence model architectures toward edge-friendly designs from the start, reducing the optimization burden at deployment time. • Provide technical leadership to cross-functional teams working on defense and edge projects, setting engineering standards, reviewing designs, and mentoring engineers on systems and optimization practices.
Job Requirements
- 5+ years of experience in systems engineering, embedded computing, or edge AI deployment, with a track record of delivering production systems on constrained hardware.
- Strong proficiency in C, C++, and/or Rust, with experience writing performance-critical code for resource-constrained environments.
- Hands-on experience with model optimization for edge deployment, including quantization, pruning, knowledge distillation, or architecture-specific compilation.
- Familiarity with edge inference runtimes such as ONNX Runtime, TensorRT, TFLite, or vendor-specific SDKs (Qualcomm SNPE/QNN, MediaTek NeuroPilot, etc.).
- Experience with security-conscious development practices, including secure boot, encrypted storage, code signing, and secure deployment pipelines.
- Strong understanding of hardware-software interaction — CPU/GPU/NPU architectures, memory hierarchies, power management, and how they affect model inference performance.
- Excellent communication skills — you will be the technical face of Deepgram to hardware partners and defense customers, and you need to be credible and clear in both contexts.
Benefits
- Medical, dental, vision benefits
- Annual wellness stipend
- Mental health support
- Life, STD, LTD Income Insurance Plans
- Unlimited PTO
- Generous paid parental leave
- Flexible schedule
- 12 Paid US company holidays
- Quarterly personal productivity stipend
- One-time stipend for home office upgrades
- 401(k) plan with company match
- Tax Savings Programs
Related Guides
Related Job Pages
More Full-stack Engineer Jobs
• Contribute to building and maintaining software features under the guidance of senior engineers • Write, test, and debug code for applications and services • Assist in developing and consuming RESTful APIs • Participate in code reviews and incorporate feedback • Work with databases to query and update data • Help troubleshoot issues and support production systems as needed • Collaborate with cross-functional teams including QA, product, and design • Continuously learn new technologies and development practices
• Lead the adoption of AI-first development practices across the engineering organization — including AI-assisted code generation, intelligent code review, automated documentation, and LLM-powered feature development. • Evaluate and integrate emerging AI tools, frameworks, and APIs (including large language models and generative AI platforms) into CareMetx's product and platform architecture. • Establish internal standards and best practices for responsible, scalable AI integration; conduct knowledge-sharing sessions to accelerate AI fluency across engineering teams. • Stay current with the rapidly evolving AI/ML landscape, bringing innovations back to the organization and translating them into concrete product improvements. • Architect and develop robust, scalable, and maintainable software systems across the full stack — from API design and data modeling to front-end implementation and cloud infrastructure. • Lead the technical design of complex features and platform capabilities, producing clear architectural documentation and driving cross-functional alignment before implementation begins. • Own multiple concurrent complex projects end-to-end, from requirements refinement through deployment and post-launch observability. • Proactively identify and address technical debt, refactoring opportunities, and architectural risks before they become blockers. • Collaborate closely with product management, UX, and business stakeholders to translate complex requirements into practical, elegant technical solutions.
• Design, develop, and maintain both desktop and web-based software applications using .NET technologies, primarily C#. • Implement clean, scalable, and efficient code following best practices and coding standards. • Develop APIs, services, and integration layers to connect with internal and external systems. • Participate in architectural discussions and decisions for new projects and enhancements. • Ensure adherence to design principles such as SOLID and design patterns. • Conduct code reviews and provide constructive feedback to ensure high quality code. • Work closely with stakeholders and QA teams to gather requirements and deliver quality solutions. • Lead and mentor junior developers, fostering a culture of continuous learning and improvement. • Collaborate in Agile ceremonies, including sprint planning, daily stand-ups, and retrospectives. • Optimize application performance and troubleshoot complex technical issues across both desktop and web platforms. • Maintain and enhance existing applications, ensuring stability and reliability. • Stay updated on emerging technologies and integrate them into the development process where applicable.
Java Fullstack Developer | Offshore |
PhotonAI-led Digital Transformation. Making Tomorrow Happen Today at the Intersection of Digital, Cloud, and AI.
Senior Full Stack Engineer About the Role: We are seeking a highly skilled Senior Full Stack Engineer to join our dynamic team. As a Senior Full Stack Engineer, you will play a crucial role in designing, developing, and maintaining our web applications. You will be responsible for both front-end and back-end development, ensuring a seamless user experience. Responsibilities: - Design, develop, and deploy robust and scalable web applications. - Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. - Develop and maintain RESTful APIs and microservices. - Write clean, well-documented, and maintainable code. - Participate in code reviews and provide constructive feedback. - Troubleshoot and resolve complex technical issues. - Mentor junior team members and foster a culture of continuous learning. - Stay up to date with the latest web development technologies and industry trends. Requirements: - 5+ years of experience in full-stack web development. - Strong proficiency in JavaScript, HTML, and CSS. - Expertise in modern JavaScript frameworks like React, Angular, or Vue.js. - Solid understanding of backend development with languages like Node.js, Python, or Java. - Experience with databases (SQL and NoSQL) and data modeling. - Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Excellent communication and teamwork skills. Preferred Qualifications: - Experience with serverless architectures and functions. - Knowledge of GraphQL and other API design paradigms. - Experience with testing frameworks (Jest, Mocha, Cypress). - Certification in relevant technologies (AWS, Azure, Google Cloud).
