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Owns AI/algorithm (ML, DL, LLMs) solutions, from research to production deployment, guiding architecture and driving advanced techniques like RAG; core technologies include AI/ML/DL, LLMs, RAG, Generative AI, Python, C++.
Data Scientist applying ML/AI to biologicals discovery for crop health, building predictive models that integrate genomic, metabolomic, and phenotypic data using Python, PyTorch, and deep learning.
Develop and deploy machine learning and deep learning models for OCT-based intravascular imaging systems, including semantic segmentation, feature detection, and quantitative analysis, using Python and frameworks like PyTorch/TensorFlow in a regulated medical device environment.
Develop and deploy machine learning and generative AI applications—including LLMs, RAG pipelines, and GenAI services—using Python, PyTorch, Azure, and vector databases in an on-site role at HP.
Tenure-track Assistant/Associate Professor conducting AI/ML research applied to veterinary medicine, disease prevention, and population health, while teaching and mentoring veterinary and graduate students at Ohio State University.
Develops production-ready AI modules (LLMs, speech, RAG) for a SaaS route-planning product used in home care, waste management, and retail fleets, using Python, ML frameworks like TensorFlow/PyTorch, and MLOps practices.
The Alibaba-NTU Global e-Sustainability CorpLab (ANGEL) represents a key collaboration between Alibaba Group and Nanyang Technological University (NTU). Supported by the Singapore RIE2025 Fund, ANGEL creates and…
Location : Novi Sad We are building an AI department, and this is one of the first roles in it. We bring engineering excellence and scale to help our customers build digital products of the future. For years, our work…
COMPANY OVERVIEW We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new…
Design and implement functionally safe perception software for humanoid robots used in warehouses and manufacturing, working with C++/C/Rust on Linux and RTOS while applying functional safety standards.
Designs and deploys advanced Retrieval-Augmented Generation (RAG) models for clients, optimizing AI-driven applications with retrieval and generation techniques.
Build and improve production LLM systems (RAG, agents) using Python, focusing on accuracy, cost, and latency while collaborating with research and product teams.
Senior Data Scientist owning the full ML production lifecycle—scaling deep learning models from R&D to reliable production systems, building data/feature pipelines, and establishing MLOps standards. Core stack includes Python/Go/Java, GCP (Vertex AI, BigQuery), Docker, Kubernetes, and MLflow/Kubeflow.
This postdoctoral researcher will use computational design, molecular modelling, and machine learning to develop peptide-based therapeutics for ischemic stroke. The role involves working within an interdisciplinary team at the University of Copenhagen to design brain-targeting shuttles that cross the blood–brain barrier.
Frontend engineer building interfaces for a surgical AI copilot, including visualization tools for surgical video and medical imaging, using React/TypeScript with real-time data streams from edge devices.
Builds full-stack surgical AI software, including backend APIs, real-time data pipelines, and front-end interfaces for medical devices, bridging research models with production-grade systems under regulatory standards.
Software Engineer on the Perception team at Intrinsic (Google's AI robotics group), building and deploying deep learning and 3D computer vision models for industrial robots using frameworks like PyTorch, TensorFlow, or JAX in Python/C++.
Research and develop post-training methods (RLHF, SFT, PEFT, reward-based optimization) for Enchant, Iambic's large multimodal transformer model used in drug discovery, using Python and PyTorch at scale.
Research and develop post-training methods for a large multimodal transformer model (Enchant) in drug discovery, focusing on fine-tuning, reinforcement learning, and evaluation frameworks to advance AI-driven therapeutic development.
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