Machine Learning Engineer

Job not on LinkedIn

🕒 March 31

🏖️ New Jersey – Remote

🏖️ New Jersey – Remote

⏰ Full Time

🟢 Junior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 63%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Anagenex

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

💰 $30M Series A on 2022-06

Healthcare • Consulting • Logistics

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.

📋 Description

• Build and deploy the ML pipelines that power the company machine learning platform. • Manage MLOps infrastructure to monitor and optimize models.

🎯 Requirements

• 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.