Machine Learning Engineer

Machine Learning Engineer at Cerberus Capital Management

Cerberus Capital Management (CCM) is searching for a highly skilled Machine Learning Engineer to join our Cerberus Technology Solutions (CTS) team. As a member of CTS, you will be pivotal in designing, implementing, and deploying cutting-edge machine learning solutions across various business objectives, including asset pricing, demand forecasting, sentiment analysis, and more.

About Cerberus Capital Management

Established in 1992, Cerberus Capital Management, L.P. is a global leader in private investment. Our firm specializes in transforming undervalued and underperforming companies into industry leaders through financial resources and operational expertise. We manage controlling or significant minority interests in diverse industries globally.

About Cerberus Technology Solutions (CTS)

Cerberus Technology Solutions is a subsidiary focused on leveraging emerging technologies, data, and advanced analytics to drive transformations. Our CTS team collaborates closely with investment and operating professionals across Cerberus’ global platforms to identify opportunities and generate value from data.

Responsibilities

• Develop predictive models utilizing machine learning techniques on modern platforms like Spark and Hadoop.
• Productionalize containerized algorithms for hybrid cloud deployments (GCP, Azure).
• Integrate and analyze data from various sources using tools like Python, Pandas, and SQL.
• Create metrics and analytical reports to ensure data quality and business value.
• Participate in developing both back-end data pipelines and front-end applications.
• Use statistical methods to predict future business outcomes and generate analytical reports.
• Conduct due diligence for investment proposals as a technology expert.
• Evaluate third-party solutions for functionality and quality.

Requirements

• 6+ years of engineering experience with a degree in Mathematics, Engineering, Statistics, Computer Science, or Physics. An advanced degree is preferred.
• Proficiency in Linear Algebra, Probability Theory, Statistics, and Optimization, including regression analysis and hypothesis testing.
• Experience with machine learning methods like regularization, random forests, neural networks, and deep learning.
• Ability to write algorithms and implement pipelines in Python. Knowledge of Scala and R is a plus.
• Experience with SQL and various relational database platforms like MySQL, PostgreSQL, and Oracle.
• Familiarity with DevOps processes for model deployment and unit testing.
• Experience working in cloud environments, particularly Microsoft Azure.
• Ability to collaborate effectively using development tools such as GIT, Azure DevOps, and JIRA.
• Strong communication skills to present ideas clearly to colleagues, management, and clients.

Compensation and Benefits

The base salary for this position ranges from $130,000.00 to $200,000.00+, depending on the candidate’s experience and qualifications. The compensation package also includes an annual discretionary bonus and a robust benefits package.