Machine Learning Engineer I

About the role

Abnormal AI is on the lookout for a Machine Learning Engineer to enhance its Misdirected Email Detection team. This position is dedicated to developing and refining systems that help prevent inadvertent data loss by accurately identifying and blocking emails sent to incorrect recipients. In this role, you will be responsible for creating comprehensive machine learning solutions that span the entire process, from data preparation to deployment in production environments. You will collaborate closely with both product and engineering teams to meet customer requirements effectively.

Key facts

What you'll do

• Work in tandem with product managers and technical leads to ensure alignment between development activities and product roadmaps, facilitating successful product launches.
• Oversee the entire machine learning pipeline for misdirected email detection, which includes data processing, feature engineering, model development, deployment, and continuous performance monitoring.
• Execute detailed experiments and evaluations, utilizing offline metrics, A/B testing, and post-launch assessments to identify potential regressions and enhance system performance.
• Clearly communicate technical information across various time zones and maintain thorough documentation to support team collaboration.
• Participate in an on-call rotation to troubleshoot issues related to detection accuracy and the performance of real-time scoring systems.
• Engage in the design and implementation of machine learning models that are robust and scalable, ensuring they meet the needs of diverse user scenarios.
• Analyze production data to uncover trends and behavioral changes, launching targeted experiments to improve model effectiveness.
• Collaborate with cross-functional teams to integrate machine learning models into existing systems, ensuring seamless functionality and user experience.
• Stay updated on the latest advancements in machine learning and apply relevant techniques to enhance existing models and algorithms.
• Contribute to the development of best practices for machine learning workflows, ensuring high standards of quality and efficiency in all processes.
• Mentor junior team members and share knowledge to foster a culture of continuous learning and improvement within the team.

Requirements

• A Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Information Systems, or a similar technical discipline.
• A minimum of 1 year of experience in building and deploying machine learning features within production settings.
• Proven experience in contributing to comprehensive machine learning systems, including data preparation (both text and structured), feature engineering, model selection, training, evaluation, and deployment with monitoring capabilities.
• Proficiency in implementing and analyzing algorithms, developing features, integrating data signals, and performing numerical computations.
• Competence in analyzing production data to identify trends and behavioral shifts, as well as conducting targeted experiments to optimize model performance.
• Familiarity with online versus offline processing, data tables, and labeling processes to ensure scalable and secure model deployments.
• Experience in calculating offline metrics, conducting online A/B testing, setting thresholds, and monitoring for performance drift, including the establishment of safeguards and rollback strategies.
• Strong written communication skills and the ability to collaborate asynchronously, working effectively both independently and within distributed, cross-functional teams.

Nice to have

• Knowledge of programming languages and tools such as Python, Go, AWS, Spark, and Databricks.
• Previous experience in email security, data loss prevention, or misdirected email prevention, particularly in deploying customer-facing machine learning solutions.
• Experience in creating detection rules that complement machine learning models for safer deployments and quicker iterations.
• Background in translating research concepts into reliable, scalable, and accurate systems for end-users.
• Prior involvement in a small team or project, successfully delivering a feature or component from its inception to completion.

Skills & tools

• Proficient in Python
• Familiar with Go
• Experience with AWS
• Knowledge of Spark
• Familiarity with Databricks

Practical notes

• This position requires eligibility to access technology governed by U.S. Export Administration Regulations (EAR). Employment is contingent upon obtaining the necessary government authorization.
• The company reserves the right to adjust employment start dates or withdraw offers to comply with export control regulations.
• The hiring process includes video interviews and identity verification.
• Pre-employment checks will be conducted for candidates who successfully progress through the hiring process.
• Compensation for this role will be determined based on the candidate's experience, skills, qualifications, and location, and may include equity, an annual bonus, and a comprehensive benefits package.
• Applications will be reviewed, and candidates can expect a response typically within two weeks.