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Remote Machine Learning Engineer

Job not on LinkedIn

March 28

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Logo of Anagenex

Anagenex

Artificial Intelligence • Biotechnology • Pharmaceuticals

Anagenex is a company focused on accelerating drug discovery using advanced AI technology and large-scale data. By testing billions of molecules and generating high-quality datasets, Anagenex leverages proprietary neural networks to design and refine new compounds that can potentially treat diseases more efficiently. The company aims to overcome the traditional 25-year timeline from disease protein identification to medicinal application, integrating iterative AI and real laboratory experiments to speed up the process, thereby bringing medicines to patients faster.

11 - 50 employees

🤖 Artificial Intelligence

🧬 Biotechnology

đź’Š Pharmaceuticals

đź’° $30M Series A on 2022-06

đź“‹ Description

• We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics. • Build and deploy the ML pipelines that power the company machine learning platform. • Manage MLOps infrastructure to monitor and optimize models.

🎯 Requirements

• Experience: 1+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist. • Proficiency across topics in machine learning and statistics. • Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas). • Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services. • Familiarity with CNNs, RNN, LSTMs, and the latest research trends. • Experience implementing, deploying, and maintaining production machine learning systems. • Experience monitoring and optimizing model performance. • Experience with Linux, Docker and AWS, and basic development operations. • Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.

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