ML Engineer

ProClinical Recruitment
München, Germany
6 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote
München, Germany

Tech stack

Airflow
Amazon Web Services (AWS)
Azure
Distributed Systems
Python
Machine Learning
TensorFlow
Reinforcement Learning
Google Cloud Platform
Data Ingestion
PyTorch
Transfer Learning
Spark
Scikit Learn
Kubernetes
Machine Learning Operations
Data Pipelines
Docker

Job description

On behalf of our innovative medtech client, an innovative technology client in the bioprocessing and advanced analytics space in their search for a Machine Learning / MLOps Engineer. This hands-on role focuses on deploying, optimizing, and scaling machine learning and hybrid models within a cloud native environment.You will work at the intersection of ML engineering, data pipeline development, and scalable infrastructure, enabling next generation digital modeling and decision-support solutions used in industrial and scientific settings., * Deploy and optimize ML and hybrid models in production environments

  • Build secure, scalable data pipelines for batch and real?time processing
  • Implement cloud based and high performance ML infrastructure
  • Develop CI/CD pipelines and model monitoring for reliable deployments
  • Collaborate with scientific and engineering teams to integrate ML components
  • Explore advanced ML techniques (hybrid models, RL, XAI, etc.)
  • Document workflows and clearly communicate technical concept

Requirements

Applicants must hold a valid EU work permit and/or reside within Europe. Please note that only eligible candidates will be contacted., * Strong proficiency in Python and modern ML frameworks (TensorFlow, PyTorch, Scikit-learn, JAX).

  • Experience deploying and maintaining production ML models.
  • Solid understanding of MLOps, CI/CD pipelines, monitoring, and lifecycle management.
  • Experience building scalable data pipelines (Spark, Airflow, or similar).
  • Familiarity with cloud platforms (AWS, Azure, GCP) and container technologies (Docker, Kubernetes).
  • Strong analytical problem-solving and communication skills.

Preferred

  • Experience with hybrid modeling, XAI, reinforcement learning, or transfer learning.
  • Background in distributed computing or HPC environments.
  • Experience designing end to end ML systems from data ingestion to deployment.
  • Certifications in relevant cloud platforms or Kubernetes.

Benefits & conditions

  • Contribute to cutting edge ML and simulation technologies shaping next generation process innovation.
  • Collaborate with world-class scientists, engineers, and domain specialists.
  • Work in a dynamic, innovative environment with strong opportunities for professional growth.
  • Help scale impactful AI solutions used across research, development, and manufacturing settings.

About the company

Proclinical is a leading life sciences recruiter focused on finding exceptional people and matching them with the finest positions across the globe. Proclinical is acting as an Employment Agency in relation to this vacancy.

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