
11 - 50 employees
đĽ Healthcare
đź Consulting
đŚ Logistics
Healthcare ⢠Consulting ⢠Logistics
Nacre Capital is a global venture builder that creates, builds, and grows start-ups focused on deep technologies that have a significant societal impact. The company identifies fundamental needs and develops innovative solutions in various sectors, including healthcare, biotechnology, agriculture, and aquaculture. They provide comprehensive support to start-ups, including financial, legal, and recruitment services, and actively help scale their ventures globally. Nacre Capital notably works with companies like FDNA, which assists in identifying rare diseases, and Seed-X, which advances AI-based solutions for seed and grain supply chains.
đ August 19
AWS
Azure
Cloud
Docker
Google Cloud Platform
Jenkins
Kubernetes
MongoDB
Python
PyTorch
Scikit-Learn
Spinnaker
SQL
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11 - 50 employees
đĽ Healthcare
đź Consulting
đŚ Logistics
Healthcare ⢠Consulting ⢠Logistics
Nacre Capital is a global venture builder that creates, builds, and grows start-ups focused on deep technologies that have a significant societal impact. The company identifies fundamental needs and develops innovative solutions in various sectors, including healthcare, biotechnology, agriculture, and aquaculture. They provide comprehensive support to start-ups, including financial, legal, and recruitment services, and actively help scale their ventures globally. Nacre Capital notably works with companies like FDNA, which assists in identifying rare diseases, and Seed-X, which advances AI-based solutions for seed and grain supply chains.
⢠Design, adapt, and implement machine learning and classical algorithms from proof of concept (POC) to working prototypes. ⢠Plan and conduct experiments to address critical business questions. ⢠Develop and maintain model testing and statistical verification processes. ⢠Implement data processing and training pipelines. ⢠Extend existing machine learning and deep learning codebases and frameworks. ⢠Thoroughly document POCs and experiments. ⢠Plan and lead long-term research activities. ⢠Assist in recruiting talent in the field. ⢠Stay up-to-date with the latest developments in AI and machine learning. ⢠Collaborate on real-world artificial intelligence solutions for aquaculture, using imaging technology to detect, identify, and predict traits of aquatic species.
⢠Proven track record in developing image/video processing and computer vision solutions. ⢠8+ years of experience as a machine learning engineer/researcher or in a similar role. ⢠Proficiency with common Python machine learning frameworks (scikit-learn, SciPy, Matplotlib, PyTorch, etc.). ⢠Strong understanding of data structures, data modeling, and software architecture. ⢠Ability to write clean, robust, and efficient code. ⢠Excellent communication and presentation skills in English. ⢠MSc or PhD in Computer Science, Engineering, Mathematics, or a related field. ⢠Candidates with a BSc degree and equivalent industrial experience are also encouraged to apply. ⢠Preferred: publication record in top-tier AI conferences or journals. ⢠Preferred: experience deploying machine learning/AI systems in production environments and tools. ⢠Preferred: familiarity with CUDA, ONNX, and TensorRT inference optimization techniques. ⢠Preferred: familiarity with Docker, Docker Compose, and Kubernetes. ⢠Preferred: knowledge of SQL, MongoDB, basic networking, or message-passing protocols. ⢠Preferred: experience with Google Cloud Platform, AWS, or Azure. ⢠Preferred: proficiency with DVC, MLflow, Metaflow, or Databricks. ⢠Preferred: familiarity with Jenkins, GitLab CI/CD, Screwdriver, Spinnaker, or similar CI/CD tools. ⢠Preferred: ability to visit Aquaculture sites when needed.
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