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Machine Learning Engineering Lead

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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. More than 10,000 organizations across the globe have used Teramind to mitigate insider threats and protect their sensitive company data with the most robust, enterprise-grade software on the market.

As a global team, Teramind embraces an inclusive and flexible work environment and team culture. We win together, learn from each other, and respect each other while delivering best-in-class security solutions.

About the role

As the Machine Learning Engineering Lead at Teramind, you will be responsible for overseeing the development and implementation of robust machine learning models that drive our platform’s capabilities. This is a key leadership role where you will guide a talented team of ML engineers, foster innovation, and ensure best practices in machine learning lifecycle management are adhered to.

Your contributions will directly impact the effectiveness of our solutions in insider threat detection and user behavior analytics, allowing organizations to make informed decisions based on data-driven insights.

Your 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

7+ 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)

This is a remote job. Work from anywhere! We're a global, distributed team looking for the finest talent. We've been thriving as a fully-remote team since 2014. To us, remote work means flexibility and having truly diverse, global teams.

At Teramind, we're a collaborative, forward-thinking team where new ideas come to life, experience is valued and talent is incubated.

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

About our recruitment process
We don’t expect a perfect fit for every requirement we’ve outlined. If you can see yourself contributing to the team, we want to hear your story. You can expect up to 4 interviews:

Test task
Intro-call
Technical interview
Final interview

All roles require reference and background checks
Teramind is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration without regard to race, age, religion, color, marital status, national origin, gender, gender identity or expression, sexual orientation, disability, or veteran status.

Average salary estimate

$150000 / YEARLY (est.)

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$120000K

$180000K

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What You Should Know About Machine Learning Engineering Lead, Teramind

Are you ready to take the lead in shaping the future of machine learning at Teramind? As the Machine Learning Engineering Lead, you will join a vibrant and innovative team dedicated to revolutionizing Insider Risk Management and User Behavior Analytics. With over 10,000 organizations trusting Teramind to protect their sensitive data, your role will be critical. You’ll guide a talented bunch of ML engineers, providing mentorship and technical direction while fostering a culture of collaboration and innovation. From designing machine learning models to overseeing their entire lifecycle, you’ll play a key part in driving our platform's capabilities. You’ll collaborate with cross-functional teams, ensuring our projects align with business objectives and keeping abreast of industry trends to integrate the latest methodologies seamlessly into our work. At Teramind, we believe in continuous improvement, so you'll also focus on enhancing our ML processes to ensure top-notch performance and interpretability. With your solid experience in machine learning practices and leadership, you’ll inspire your team and make a significant impact in the exciting world of data-driven insights. Join us and enjoy the perks of remote work, flexible time off, great health benefits, and an environment where new ideas thrive and career growth is encouraged. Let’s win together and redefine security solutions for organizations worldwide!

Frequently Asked Questions (FAQs) for Machine Learning Engineering Lead Role at Teramind

What are the responsibilities of a Machine Learning Engineering Lead at Teramind?

As a Machine Learning Engineering Lead at Teramind, your primary responsibilities include overseeing the development of machine learning models, guiding a team of engineers, designing the ML lifecycle, and ensuring alignment with business objectives. You will also stay updated on industry trends and drive continuous improvement in ML processes, helping enhance the company’s capabilities in insider threat detection and user behavior analytics.