Senior Machine Learning Engineer

Summary

Join Gemini's Trust & Safety team as a Senior Machine Learning Engineer and leverage your expertise to build and optimize machine learning models for fraud detection, anti-money laundering, and other critical functions. You will collaborate with cross-functional teams, analyze large datasets, and communicate insights to stakeholders. This role requires a strong background in data science, machine learning, and financial services. You will be responsible for designing, developing, and deploying ML models at scale, ensuring their effectiveness, and staying current with industry advancements. Gemini offers a competitive compensation and benefits package, including a discretionary annual bonus, equity grant, comprehensive health plans, 401k matching, paid parental leave, and flexible time off.

Requirements

• Bachelor's degree in computer science, data science, mathematics, or a related field
• 4+ years of work experience in analytics and data science domain focusing on financial services-related business problems
• 3+ years of experience deploying statistical and machine learning models in production
• 2+ years of experience in integrating data science models into applications
• Proven experience in developing and deploying ML models at scale, with a deep understanding of model lifecycle management
• Knowledge and experience of crypto exchange trading, financial markets, or banking
• Extensive knowledge of ML frameworks (Sagemaker or ML Flow) , libraries, data structures, data modeling, and software architecture
• Advanced skills with SQL are a must
• Proficient in Python
• Experience with one or more big data tools and technologies like Snowflake, Databricks, S3, Hadoop, Spark
• Experienced in working collaboratively across different teams and departments
• Strong technical and business communication

Responsibilities

• Design and develop Trust & Safety machine learning and AI models to optimize across fraud, crypto exchange trading, and anti money laundering
• Distill complex models and analysis into compelling insights for our stakeholders and executives
• Analyze large and complex datasets to identify patterns for feature engineering, trends, and anomalies and develop predictive models that can be used for decision-making
• Collaborate with software developers to design and implement machine learning systems that can improve the speed and accuracy of the machine learning models
• Monitor and analyze the performance of our machine learning models and systems and make necessary improvements to ensure their effectiveness
• Stay up-to-date with data science tools and methodologies in technology and financial domain
• Perform root cause analysis and resolve production and data issues

Preferred Qualifications

• Master’s degree in computational linguistics, data science, data analytics, or similar
• Proficient in Developing LookML
• Experience working with NLP applications is a plus
• Experience working in small firms, financial technology, or start up technology

Benefits

• Competitive starting salary
• A discretionary annual bonus
• Long-term incentive in the form of a new hire equity grant
• Comprehensive health plans
• 401K with company matching
• Paid Parental Leave
• Flexible time off
• In the United States, we have a flexible hybrid work policy for employees who live within 30 miles of our office headquartered in New York City and our office in Seattle