Senior Machine Learning Engineer

March 27

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Teramind

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Teramind is a leading provider of behavior analytics and productivity optimization solutions for businesses. The company offers a comprehensive platform focused on cybersecurity, insider threat management, data loss prevention, and user activity monitoring. Teramind's innovative products help organizations enhance their security posture, optimize workforce productivity, and ensure compliance with industry regulations. By utilizing advanced behavior analytics, Teramind helps companies gain critical insights into user actions to mitigate risks and improve operational efficiency. Their services are relevant across multiple sectors, including healthcare, financial services, and customer service, showcasing their versatility in addressing complex security and productivity challenges.

Activity Monitoring • Audit and Forensics • Business Intelligence (BI) Reports • Compliance Management • DLP Technology

51 - 200 employees

Founded 2013

🔒 Cybersecurity

⚡ Productivity

🏢 Enterprise

📋 Description

• Teramind is a hybrid, global workforce building the next-generation Insider Risk Management and User Behavior Analytics platform. • Join our team of innovators who are redefining insider risk management through cutting-edge technology. • We are looking for a Senior Machine Learning Engineer to help us build and deploy production-ready machine learning systems. • You'll convert advanced data science models into scalable and efficient code capable of processing vast amounts of user activity data in real-time. • Your day-to-day includes implementing and optimizing machine learning models, developing data processing pipelines, and closely collaborating with data scientists and software engineers.

🎯 Requirements

• Experience: 5+ years of hands-on experience in implementing and scaling production machine learning systems. • Technical Proficiency: Strong software engineering skills, with a focus on machine learning implementation and optimization. • Framework Expertise: Proficiency with popular machine learning frameworks and tools (e.g., TensorFlow, PyTorch) to drive model development. • Distributed Computing Knowledge: Understanding of distributed computing principles and experience with real-time data processing architectures. • ETL Systems: Experience in deploying systems for efficient batch processing and online ETL (Extract, Transform, Load). • Performance Optimization: Familiarity with model optimization techniques and performance tuning to ensure efficient operation. • Security-Savvy: Experience with machine learning applications focused on security is a plus and will be highly regarded.

🏖️ Benefits

• Competitive salary with a focus on a global market. • Career-growth opportunities. • Flexible Time Off and Paid Time Off benefits. • Ongoing training and development opportunities.