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Lead AI Engineer responsible for the end-to-end AI/ML lifecycle at an education company, including building data pipelines, developing deep learning, generative AI, and NLP models, and designing scalable AI/ML infrastructure.
Develop AI/ML models and signal-processing algorithms to detect, classify, and interpret complex real-world signals for defence sensing applications.
This role involves building data quality pipelines and conducting ML experiments to improve robot control models within Sber's Robotics Center. The engineer will analyze multimodal datasets, evaluate model performance, and translate data insights into actionable improvements for model training and data collection.
AI/ML Engineer designing, deploying, and sustaining production ML models, NLP/genAI solutions, and real-time decision-support systems for a SOCOM mission partner using Python, ML frameworks, and MLOps/DevSecOps practices in secure environments.
Own the full ML lifecycle—data analysis, model development, and production pipelines—at a Berlin SaaS company building cloud software for automotive repair shops, using Python, SQL, and cloud platforms.
The AI/ML ASIC Architect will design and define architecture specifications for next-generation AI storage and accelerator solutions, focusing on I/O subsystems and high-performance interfaces like PCIe, CXL, and UCIe. The role involves collaborating with cross-functional teams to optimize performance, power, and area for large-scale LLM training and inference workloads.
Computer Vision Engineer taking the Vision Weigh animal measurement product from prototype to production on commercial farms—building and deploying models on edge hardware (Jetson, NPU boards) using Python, PyTorch, and depth sensing, with a focus on rapid iteration over perfection.
Computer Vision Engineer taking the Vision Weigh livestock measurement system from prototype to production on edge hardware in paddocks, using Python, PyTorch, depth sensing, and classical CV techniques deployed on Jetson/NPU boards.
Lead ML innovations for Coupang Eats Search, shaping how customers discover food/delivery items via retrieval and relevance models. Own end-to-end stack, including query understanding, candidate retrieval, and relevance measurement, while driving business growth through scalable, low-latency solutions.
Designs and deploys AI/ML models to support public health initiatives using modern AI techniques in a mission-driven federal program.
Build and optimize ultra-low-latency ML inference pipelines for quantitative trading, tuning GPU/FPGA kernels and memory hierarchies to microsecond precision.
Build multimodal perception and authentication systems using vision, audio, and sensor data to help AI understand the physical world and people in real-world environments.
Leads a growing team of applied ML scientists to develop and deploy fraud detection and identity verification models for SentiLink’s fintech solutions, driving product strategy and technical decisions while ensuring AI safety and data governance.
Leads a growing team of applied ML scientists to develop and deploy fraud detection/identity verification models for US financial institutions, balancing technical execution, mentorship, and product strategy in fintech risk solutions.
Builds and deploys AI/ML models for a client’s product, focusing on data pipelines, model optimization, and production integration using Python, TensorFlow/PyTorch, and cloud platforms.
This role involves building and maintaining scalable machine learning infrastructure on AWS to support drug discovery initiatives. The engineer will automate deployments, manage CI/CD pipelines, and collaborate with data scientists to optimize computational workflows.
Develops and owns end-to-end AI/ML systems for the Food & Beverage supply chain domain, focusing on dataset design, performance monitoring, and cross-team collaboration to deliver scalable solutions.
Build and deploy ML/LLM solutions end-to-end for diverse clients, from data prep to production APIs, while collaborating in a team of ML engineers.
Technical Product Manager leading the definition, delivery, and scaling of ML and GenAI-powered analytical products at an automotive mobility company, collaborating with data scientists and engineers on AWS/Azure using Agile practices.
NVIDIA is hiring 2027 New College Graduates for Deep Learning and High-Performance Computing Engineering roles in Shanghai, focusing on areas like LLM inference optimization, AI compilers, parallel computing, and GPU architecture.
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