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Research engineer translating biometrics and AI research into scalable production software using ML/DL, computer vision, C++, and Python to build biometric recognition systems at Thales.
Designs and implements deep learning models for autonomous truck perception, planning, and control, using PyTorch/TensorFlow and state-of-the-art neural architectures.
Develop and optimize deep learning models for autonomous truck perception, mapping, and planning using PyTorch, collaborating with cross-functional teams to integrate solutions into production pipelines.
Build and fine-tune AI models for security alert triage and risk scoring using enterprise telemetry, then deploy a multi-model routing layer that keeps costs predictable while improving accuracy over time.
Develops and deploys production AI systems for retail shelf intelligence, focusing on computer vision tasks like object detection, OCR, and product recognition to improve inventory accuracy and retail operations.
Optimize ML inference for edge accelerators and GPUs, focusing on transformer-based models for low-power in-vehicle compute by improving compilers, runtimes, and kernels.
Our Culture and People: At Goddard, our most important asset is our people. We don't just work together; we thrive together. We foster a culture of collaboration, continuous learning, and mutual support. We believe…
Build and improve an AI shopping assistant that surfaces relevant listings, compares options, and suggests fair prices for millions of users using modern ML and LLM techniques.
Leads the design and architecture of a production GenAI platform for Deliveroo and DoorDash, focusing on open-weight LLM/VLM serving, fine-tuning, and GPU infrastructure to optimize cost, latency, and scalability for business impact.
Principal AI/ML Engineer to architect and deploy cutting-edge models (LLMs, transformers) and lead AI strategy at high-growth startups in SignalFire’s portfolio.
Designs end-to-end AI/deep-learning architectures for geospatial platforms, customizing models like LLM/RAG and deploying on GPU/cloud infrastructure for defense, government, and commercial clients.
Build and scale the infrastructure that powers a computer-vision engine detecting underground utilities, designing pipelines, data systems, and deployment workflows for AI models.
AI Solutions Engineer About the Role We are seeking a dynamic AI Solutions Engineer to join my client's Enterprise Sales team. In this role, you will be the technical authority guiding enterprise clients through…
Lead the design and deployment of AI/ML solutions using Azure ML, OpenAI APIs, and generative AI for computer vision tasks like object detection and retail shelf analysis.
Build and secure AI/ML systems for national defense, including LLM apps, predictive models, and adversarial defenses, using Python, TensorFlow/PyTorch, and edge deployment tooling.
Design and deploy enterprise-grade AI systems—including LLMs, vision models, and robotics—from research to production, ensuring scalability, security, and alignment with business goals.
Design and deploy enterprise-grade AI systems—from LLMs and multimodal models to robotics and edge AI—guiding the full lifecycle from research to production while aligning with business goals and governance.
Build and optimize NVIDIA’s TensorRT and TensorRT-LLM inference engines in C++/CUDA to accelerate large language models on GPUs.
Lead product strategy for NVIDIA’s AI inference tools and SDKs, collaborating with developers to optimize GenAI deployments on GPUs.
Develop and optimize CUDA-based deep learning systems, designing custom kernels and distributed AI pipelines to maximize GPU performance for training and inference workloads.
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