AI/ML Engineer

Job not on LinkedIn

🕒 March 27

🇩🇪 Germany – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 55%

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Logo of XO Life

XO Life

11 - 50 employees

💼 Consulting

📦 Logistics

📣 Marketing

💰 Seed Round on 2022-02

Consulting • Logistics • Marketing

XO Life is a digital health platform known as ImpactMonitor™ that connects patients with healthcare professionals and pharmaceutical companies to provide enhanced digital treatment support. The platform is a one-stop-shop for providing a comprehensive suite of services, including digital product and therapy accompaniment, real-world patient insights, and pharmacovigilance. It aims to reduce the need for individual health apps by offering a unified space where Pharma and medical product manufacturers can easily connect with patients. XO Life focuses on improving patient outcomes through better-informed and supportive treatment processes. The company is rapidly expanding with a mission to become a trusted resource for patients seeking health information and support.

📋 Description

• Analyze, visualize, and ensure the quality of healthcare data to extract actionable insights • Design, prototype, and deploy ML models and algorithms in collaboration with data scientists and engineers • Ensure robust data workflows and support MLOps best practices • Develop and maintain scalable ML pipelines and microservices, including automation of deployment, monitoring, and retraining • Work closely with product, engineering, and business teams to deliver impactful AI solutions • Present findings, lead cross-functional AI initiatives

🎯 Requirements

• PhD in Computer Science, Machine Learning/AI, Statistics, or related fields, OR Master’s with 5+ years relevant experience • Strong foundation in mathematics, statistics, and algorithms • Programming: Python, JavaScript/TypeScript • ML/AI: Vertex AI, LangGraph, TensorFlow, PyTorch, Scikit-learn, Keras • Cloud: AWS, GCP • Data: Snowflake, Apache Superset, MongoDB, Pandas, NumPy, Jupyter • MLOps: Docker, Kubernetes, CI/CD, MLflow, Weights & Biases • ML algorithms (supervised, unsupervised, reinforcement learning) • Deep learning (CNNs, RNNs, Transformers) • Statistical methods, experimental design • Big data frameworks (Spark, Dask)

🏖️ Benefits

• 100% remote with best IT equipment • Enjoy full remote work • Regular team events • Top-notch equipment

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