Machine Learning Engineer
About Us
Planck Technologies is a company specialized in Software Development, dedicated to shaping futures and creating value through innovative IT solutions. By expanding teams and offering a comprehensive range of services—from Software Development and Infrastructure Management to Cybersecurity—we empower clients with all the expertise they need in one place. Inspired by the principles of quantum physics, we push beyond traditional boundaries to deliver customized solutions that redefine the IT landscape and drive shared success.
About the job
Design and develop generative AI solutions with LLMs, multimodal models, and
- based systems.
Build and optimize MLOps pipelines for scalable model training, deployment, and lifecycle management.
Create agentic workflows and tools for advanced
- solving.
Implement CI/CD pipelines with automated testing, validation, and deployment for ML models.
Collaborate with data scientists, engineers, and product teams to deliver
-
- end ML solutions.
Ensure best practices in model versioning, testing, monitoring, and reproducibility in production.
What are we looking for?
More than 3 years of experience in machine learning engineering, with focus on Gen
AI and MLOps.
Proven track record in building agentic workflows and agent tools.
Familiarity with LLMs, prompt engineering, and agent frameworks (e. g. , Lang
Chain, Llama
Index, Auto
Gen).
Strong Python skills and experience with ML frameworks (Py
Torch, Hugging Face, Scikit Learn, Spark
ML).
Knowledge of distributed computing (Py
Spark, Hadoop).
Solid understanding of MLOps practices (CI/CD, monitoring, retraining, data versioning).
Experience with MLOps tools (MLflow, Kubeflow or similar).
Hands-on experience with cloud (Azure preferred), Docker, and Kubernetes.
Strong
- solving, structured thinking, and communication skills.
Location: Hybrid, Maia
We're waiting for you !
- Informações detalhadas sobre a oferta de emprego
Empresa: Planck Technologies Localização: Maia
Maia, Porto District, PortugalPublicado: 5. 9. 2025
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