Machine Learning Architect @

2 weeks ago

Remote, Czech Republic Devire Full time

Must have:

  • Min. 5+ years of experience in Machine Learning / Deep Learning, including at least 2 years in real-time image/video processing.
  • Strong programming skills in Python and C++.
  • Hands-on experience with PyTorch and/or TensorFlow.
  • Proficiency in using TensorRT for model optimization.
  • Experience working with real-time streaming protocols and tools, especially RTSP and NVIDIA DeepStream SDK.
  • Familiarity with message streaming systems such as Kafka.
  • Experience with version control systems: GitLab, GitHub.
  • Ability to design scalable and reliable ML solutions.

Nice to have:

  • Knowledge of containerization technologies like Docker and Kubernetes (K8s).
  • Experience in edge computing or deploying models to edge devices.
  • Understanding of MLOps and ML pipeline automation.

Devire IT Outsourcing is a form of cooperation dedicated to IT professionals, based on the principles of own business - B2B, implementing projects for clients running innovative and modern projects.

Our Client offers full-cycle software development services – covering everything from gathering requirements and designing architecture to implementation, ongoing maintenance, and support – complemented by agile project management to enable smooth and efficient outsourcing.

We are looking for an experienced Machine Learning Architect to join our Client's R&D team to design and optimize advanced real-time image processing systems. This role involves end-to-end ownership of ML architecture - from concept and development to deployment in production environments using edge computing and video streaming technologies.

Location: 100% remote

Salary: 170-230 PLN net+VAT/h; B2B

Language: communication in English daily

  • Salary based on B2B contract (via Devire)
  • 100% remote
  • Flexible working hours
  • Additional benefits package (medical healthcare, sports membership, etc.)
,[Design, develop, and deploy machine learning architectures for real-time video stream processing., Build and optimize deep learning models using PyTorch and TensorFlow, leveraging hardware acceleration (GPU, TensorRT)., Integrate with streaming systems based on RTSP, NVIDIA DeepStream SDK, and message brokers such as Kafka., Collaborate with DevOps and software engineering teams on code versioning (GitLab/GitHub) and, optionally, containerization using Kubernetes., Monitor and validate model performance, adapting to changing data in real time., Provide technical leadership and participate in architectural decisions throughout the ML project lifecycle.] Requirements: Machine learning, Video processing, Python, C++, PyTorch, TensorFlow, Protocols, SDK, Kafka, Version control system, GitHub, Docker, Kubernetes, K8s, MLOps

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