Sr. Deep Neural Network (DNN) Deployment Engineer

Job Title: Senior Deep Neural Network (DNN) Deployment Engineer
Location: Beavercreek, OH (remote or hybrid is an option)
Company: Oculii Corp– A Subsidiary of Ambarella Corporation

About Us:
Oculii is transforming the future of autonomy by developing high-resolution imaging radar systems that power next-generation autonomous vehicles and intelligent machines. Our work is cutting-edge, our team is passionate, and our mission is clear: Independently Build. Collectively Driven.

This isn’t your typical software engineering role, it's an opportunity to drive real innovation where AI meets real-time hardware.

Role Overview:

We’re seeking an experienced Senior Deep Neural Network (DNN) Deployment Engineer to lead the optimization and deployment of complex deep learning models on real-time, resource-constrained hardware platforms. You’ll work at the intersection of AI research and embedded system performance, delivering scalable, high-speed, and power-efficient inference solutions for mission-critical applications.

Key Responsibilities:

• Own the end-to-end deployment pipeline for deep learning models on platforms such as GPUs, NPUs, and embedded systems.
• Optimize and validate DNN architectures (CNNs, RNNs, Transformers) to meet performance targets across latency, throughput, and power.
• Utilize tools like ONNX, TensorRT, and others for model conversion, graph optimization, and performance benchmarking.
• Conduct detailed resource analysis (compute, memory, bandwidth) and feasibility assessments.
• Apply advanced training-time optimization techniques: quantization, pruning, knowledge distillation, and more.
• Troubleshoot and resolve bottlenecks in the end-to-end inference pipeline.
• Collaborate with research and hardware teams to align model architecture with deployment goals.
• Mentor junior engineers and help establish deployment best practices.
• Stay ahead of advancements in model optimization, deployment tools, and hardware acceleration.

Required Qualifications:

• Bachelor's or Master’s degree in Computer Science, Electrical Engineering, or a related field or 5 plus years of experience with no degree.
• 5+ years of professional experience deploying DNNs in real-time applications.
• Deep understanding of model architectures and optimization strategies for constrained environments.
• Strong expertise in ONNX Runtime and deployment frameworks like TensorRT.
• Proven experience profiling and optimizing models on hardware platforms.
• Proficiency in Python and deep learning libraries (PyTorch preferred).
• Hands-on with version control (Git) and AI-assisted coding tools (e.g., GitHub Copilot).
• Strong analytical, debugging, and communication skills.

Preferred Qualifications:

• Experience with real-time inference engines: NVIDIA TensorRT, Intel OpenVINO, Qualcomm SNPE, etc.
• Development of custom DNN operators.
• Familiarity with GPU/NPU programming models beyond framework APIs.
• Experience using performance analysis tools and debugging hardware-level issues.
• Leadership or mentoring experience.
• Knowledge of MLOps practices and CI/CD for ML systems.

Join us to learn the way. Stay to lead the way.
At Oculii, you’ll help shape the future of autonomy while working with a team that’s redefining what’s possible in radar and AI.