Machine Learning Engineering Lead

Summary

Join Teramind's team of innovators as the Machine Learning Engineering Lead and oversee the development and implementation of robust machine learning models. This key leadership role involves guiding a team of ML engineers, fostering innovation, and ensuring best practices. Your contributions will directly impact the effectiveness of insider threat detection and user behavior analytics solutions. This is a remote position, offering flexibility and the chance to work with a global, distributed team. Teramind values collaboration, new ideas, and experience. The company provides high-quality health benefits, a retirement plan, career-growth opportunities, flexible time off, and a professional development budget.

Requirements

• 8+ years of experience in machine learning or data science roles, with at least 3 years in a leadership position
• Strong proficiency in programming languages such as Python, R, or Java, and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Proven track record of successfully deploying ML models into production environments
• Experience with cloud-based ML platforms (e.g., AWS Sagemaker, Google AI Platform) and MLops practices
• Solid understanding of machine learning algorithms, statistical methods, and data preprocessing techniques
• Excellent leadership and team management skills with the ability to inspire and motivate team members
• Strong problem-solving skills and the ability to work collaboratively in a fast-paced environment
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders
• A degree in Computer Science, Engineering, Data Science, or a related field (Master’s or Ph.D. is a plus)

Responsibilities

• Lead and mentor a team of machine learning engineers, providing technical guidance and fostering a collaborative environment
• Design, implement, and oversee the entire ML lifecycle, from data preparation to model deployment and monitoring
• Collaborate with cross-functional teams to define project goals, communicate progress, and ensure alignment with business objectives
• Stay abreast of industry trends and advancements in ML and data science, integrating new technologies and methodologies as appropriate
• Drive continuous improvement in ML processes and practices, ensuring high standards of model performance, accuracy, and interpretability

Preferred Qualifications

Master’s or Ph.D. is a plus

Benefits

• High-quality health benefits
• Retirement Plan with employer match
• Career-growth opportunities
• Flexible Time Off and Paid Time Off benefits
• Professional development budget