Machine Learning Engineer
J
JobgetherMachine Learning
Our partner is looking for a Machine Learning Engineer based in Germany. ... Fully remote full-time position with the flexibility to work from Europe.Full-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- PythonPyTorchSoftware EngineeringDeep Learning
Requirements
- Proven experience designing, developing, and deploying machine learning systems used in production environments.
- Strong expertise in Python and deep learning frameworks such as PyTorch and/or JAX.
- Hands-on experience with GPU-based training and inference systems, including performance optimization and large-scale model deployment.
- Solid understanding of modern machine learning models, their behavior in production, and strategies for identifying and resolving failure modes.
- Experience writing clean, maintainable, and production-quality software with a systems-oriented engineering mindset.
- Ability to independently manage projects from concept through deployment while balancing speed, quality, and reliability.
- Strong analytical and problem-solving skills with an iterative, data-driven approach to improving machine learning performance.
- Excellent communication and collaboration skills, with experience working alongside research, engineering, and product teams.
- Previous mentoring or technical leadership experience is considered an advantage.
Responsibilities
- Design, develop, and maintain production-ready machine learning systems supporting advanced AI-powered products.
- Own the complete machine learning lifecycle, including data preparation, model training, evaluation, deployment, inference, monitoring, and continuous improvement.
- Translate research concepts into scalable, reliable production solutions that meet business and technical objectives.
- Investigate, troubleshoot, and resolve model performance issues and production incidents using real-world data and operational insights.
- Continuously optimize machine learning models for accuracy, latency, scalability, reliability, efficiency, and operational cost.
- Collaborate closely with cross-functional teams to integrate machine learning capabilities into production products.
- Mentor other machine learning engineers through technical guidance, code reviews, and knowledge sharing.
- Build and maintain robust training, inference, and data pipelines while ensuring system stability under production constraints.
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