ML Ops Engineer-  base to maybe $170K, stock options 112 - Hatch Global Search

Job Description

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production environments. This role bridges the gap between data science and IT operations, ensuring seamless integration of machine learning models into operational workflows.

ML Ops Engineer

Our client is a growing software company. Several key positions have opened because of this expansion including Machine Learning Ops Engineers at Senior and Principal levels with machine learning experience. These are hybrid positions in Monmouth County. If you have solid computer science fundamentals (data structures, algorithms, etc.) and experience with C or Python and Linux you may qualify for one of these exceptional opportunities.

The ML Ops Engineer roles involve deploying, managing, and optimizing machine learning systems and pipelines, with a focus on ransomware acquisition and analysis operations. Key responsibilities include managing cloud services, data pipelines, and system administration tasks while collaborating with cross-functional teams to ensure seamless integration of ML models. Proficiency in Python, shell scripting, VMware administration, and data analysis is essential. Strong problem-solving, communication, and teamwork skills, along with experience in ML model deployment and pipeline management, are critical for success in this role. Full job description is available.

Requirements include: BS, MS or PhD in CS, CE, EE, Math, or other technical discipline; Machine Learning Ops knowledge; a few years of software development; team player with great interpersonal skills; desire to contribute and learn;

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