Senior Machine Learning Engineering Manager, Risk and Fraud
Coinbase
Senior Machine Learning Engineering Manager, Risk and Fraud
Job Description
Responsibilities
- Lead, manage, and scale the Risk AI/ML organization, fostering a culture of technical excellence and rapid execution.
- Define and execute the multi-year technical and strategic roadmap for Risk AI/ML, identifying new threats and opportunities in the crypto ecosystem.
- Directly manage and mentor other ML managers and senior technical leads, growing their careers and impact.
- Guide a 25+ person organization to design, build, and deploy the next generation of risk models (e.g., for Scams, ATO, Payments, and On-Chain Fraud) that have a direct, measurable impact on business goals.
- Take full ownership of the end-to-end ML systems for Risk, from feature engineering and model development to live production monitoring and performance.
- Serve as the primary AI/ML voice for the Risk domain, collaborating with VPs and Directors in Product, Engineering, and Operations to turn complex business problems into a tangible ML roadmap.
- Work with our talent organization to attract, hire, and retain top-tier ML managers and engineers.
Required Qualifications
- 10+ years of working experience in machine learning and 5+ years of ML/engineering management experience, with at least 2 years of experience managing other managers (managing through others).
- Proven experience and deep domain knowledge in the Risk, Fraud or Trust & Safety space. You have a track record of building ML systems to combat adversarial behavior (e.g., fraud, scams, account takeover, payment risk).
- Experience setting a multi-quarter strategic roadmap for multiple ML teams and interfacing with senior-level (VP/Director) partners to drive business outcomes.
- Strong technical background in modern machine learning techniques and platforms (e.g., supervised/unsupervised learning, deep learning, MLOps, and common ML platforms like Tensorflow/PyTorch).
- A strong track record of hiring and developing top-performing ML managers and engineers.
- An execution-focused mindset with a proven ability to navigate ambiguity, break down complex problems, and lead a large organization to deliver results.
- Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical senior audiences.
Preferred Qualifications
- Previous experience in FinTech or Crypto.
- Experience applying advanced ML techniques to risk problems (e.g., Graph Neural Networks (GNNs), Transformers, LLMs, anomaly detection).
- Deep expertise with high-performance ML serving and MLOps platforms
Required Skills
- Machine learning
- ML/engineering management
- Risk, Fraud or Trust & Safety domain knowledge
- Strategic leadership
- Modern machine learning techniques (supervised/unsupervised learning, deep learning)
- MLOps
- Tensorflow/PyTorch
- Hiring and team building
- Execution focus
- Communication skills
Benefits
- Bonus eligibility
- Equity eligibility
- Benefits (including medical, dental, vision and 401(k))
Salary Range
$236725 - $278500 USD
Locations
- Canada, Canada (Remote)
- USA, United States (Remote)
Salary
236,725 - 278,500 USD / yearly
Skills Required
- Machine learningintermediate
- ML/engineering managementintermediate
- Risk, Fraud or Trust & Safety domain knowledgeintermediate
- Strategic leadershipintermediate
- Modern machine learning techniques (supervised/unsupervised learning, deep learning)intermediate
- MLOpsintermediate
- Tensorflow/PyTorchintermediate
- Hiring and team buildingintermediate
- Execution focusintermediate
- Communication skillsintermediate
Required Qualifications
- 10+ years of working experience in machine learning and 5+ years of ML/engineering management experience, with at least 2 years of experience managing other managers (managing through others). (experience)
- Proven experience and deep domain knowledge in the Risk, Fraud or Trust & Safety space. You have a track record of building ML systems to combat adversarial behavior (e.g., fraud, scams, account takeover, payment risk). (experience)
- Experience setting a multi-quarter strategic roadmap for multiple ML teams and interfacing with senior-level (VP/Director) partners to drive business outcomes. (experience)
- Strong technical background in modern machine learning techniques and platforms (e.g., supervised/unsupervised learning, deep learning, MLOps, and common ML platforms like Tensorflow/PyTorch). (experience)
- A strong track record of hiring and developing top-performing ML managers and engineers. (experience)
- An execution-focused mindset with a proven ability to navigate ambiguity, break down complex problems, and lead a large organization to deliver results. (experience)
- Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical senior audiences. (experience)
Preferred Qualifications
- Previous experience in FinTech or Crypto. (experience)
- Experience applying advanced ML techniques to risk problems (e.g., Graph Neural Networks (GNNs), Transformers, LLMs, anomaly detection). (experience)
- Deep expertise with high-performance ML serving and MLOps platforms (experience)
Responsibilities
- Lead, manage, and scale the Risk AI/ML organization, fostering a culture of technical excellence and rapid execution.
- Define and execute the multi-year technical and strategic roadmap for Risk AI/ML, identifying new threats and opportunities in the crypto ecosystem.
- Directly manage and mentor other ML managers and senior technical leads, growing their careers and impact.
- Guide a 25+ person organization to design, build, and deploy the next generation of risk models (e.g., for Scams, ATO, Payments, and On-Chain Fraud) that have a direct, measurable impact on business goals.
- Take full ownership of the end-to-end ML systems for Risk, from feature engineering and model development to live production monitoring and performance.
- Serve as the primary AI/ML voice for the Risk domain, collaborating with VPs and Directors in Product, Engineering, and Operations to turn complex business problems into a tangible ML roadmap.
- Work with our talent organization to attract, hire, and retain top-tier ML managers and engineers.
Benefits
- general: Bonus eligibility
- general: Equity eligibility
- general: Benefits (including medical, dental, vision and 401(k))
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Senior Machine Learning Engineering Manager, Risk and Fraud
Coinbase
Senior Machine Learning Engineering Manager, Risk and Fraud
Job Description
Responsibilities
- Lead, manage, and scale the Risk AI/ML organization, fostering a culture of technical excellence and rapid execution.
- Define and execute the multi-year technical and strategic roadmap for Risk AI/ML, identifying new threats and opportunities in the crypto ecosystem.
- Directly manage and mentor other ML managers and senior technical leads, growing their careers and impact.
- Guide a 25+ person organization to design, build, and deploy the next generation of risk models (e.g., for Scams, ATO, Payments, and On-Chain Fraud) that have a direct, measurable impact on business goals.
- Take full ownership of the end-to-end ML systems for Risk, from feature engineering and model development to live production monitoring and performance.
- Serve as the primary AI/ML voice for the Risk domain, collaborating with VPs and Directors in Product, Engineering, and Operations to turn complex business problems into a tangible ML roadmap.
- Work with our talent organization to attract, hire, and retain top-tier ML managers and engineers.
Required Qualifications
- 10+ years of working experience in machine learning and 5+ years of ML/engineering management experience, with at least 2 years of experience managing other managers (managing through others).
- Proven experience and deep domain knowledge in the Risk, Fraud or Trust & Safety space. You have a track record of building ML systems to combat adversarial behavior (e.g., fraud, scams, account takeover, payment risk).
- Experience setting a multi-quarter strategic roadmap for multiple ML teams and interfacing with senior-level (VP/Director) partners to drive business outcomes.
- Strong technical background in modern machine learning techniques and platforms (e.g., supervised/unsupervised learning, deep learning, MLOps, and common ML platforms like Tensorflow/PyTorch).
- A strong track record of hiring and developing top-performing ML managers and engineers.
- An execution-focused mindset with a proven ability to navigate ambiguity, break down complex problems, and lead a large organization to deliver results.
- Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical senior audiences.
Preferred Qualifications
- Previous experience in FinTech or Crypto.
- Experience applying advanced ML techniques to risk problems (e.g., Graph Neural Networks (GNNs), Transformers, LLMs, anomaly detection).
- Deep expertise with high-performance ML serving and MLOps platforms
Required Skills
- Machine learning
- ML/engineering management
- Risk, Fraud or Trust & Safety domain knowledge
- Strategic leadership
- Modern machine learning techniques (supervised/unsupervised learning, deep learning)
- MLOps
- Tensorflow/PyTorch
- Hiring and team building
- Execution focus
- Communication skills
Benefits
- Bonus eligibility
- Equity eligibility
- Benefits (including medical, dental, vision and 401(k))
Salary Range
$236725 - $278500 USD
Locations
- Canada, Canada (Remote)
- USA, United States (Remote)
Salary
236,725 - 278,500 USD / yearly
Skills Required
- Machine learningintermediate
- ML/engineering managementintermediate
- Risk, Fraud or Trust & Safety domain knowledgeintermediate
- Strategic leadershipintermediate
- Modern machine learning techniques (supervised/unsupervised learning, deep learning)intermediate
- MLOpsintermediate
- Tensorflow/PyTorchintermediate
- Hiring and team buildingintermediate
- Execution focusintermediate
- Communication skillsintermediate
Required Qualifications
- 10+ years of working experience in machine learning and 5+ years of ML/engineering management experience, with at least 2 years of experience managing other managers (managing through others). (experience)
- Proven experience and deep domain knowledge in the Risk, Fraud or Trust & Safety space. You have a track record of building ML systems to combat adversarial behavior (e.g., fraud, scams, account takeover, payment risk). (experience)
- Experience setting a multi-quarter strategic roadmap for multiple ML teams and interfacing with senior-level (VP/Director) partners to drive business outcomes. (experience)
- Strong technical background in modern machine learning techniques and platforms (e.g., supervised/unsupervised learning, deep learning, MLOps, and common ML platforms like Tensorflow/PyTorch). (experience)
- A strong track record of hiring and developing top-performing ML managers and engineers. (experience)
- An execution-focused mindset with a proven ability to navigate ambiguity, break down complex problems, and lead a large organization to deliver results. (experience)
- Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical senior audiences. (experience)
Preferred Qualifications
- Previous experience in FinTech or Crypto. (experience)
- Experience applying advanced ML techniques to risk problems (e.g., Graph Neural Networks (GNNs), Transformers, LLMs, anomaly detection). (experience)
- Deep expertise with high-performance ML serving and MLOps platforms (experience)
Responsibilities
- Lead, manage, and scale the Risk AI/ML organization, fostering a culture of technical excellence and rapid execution.
- Define and execute the multi-year technical and strategic roadmap for Risk AI/ML, identifying new threats and opportunities in the crypto ecosystem.
- Directly manage and mentor other ML managers and senior technical leads, growing their careers and impact.
- Guide a 25+ person organization to design, build, and deploy the next generation of risk models (e.g., for Scams, ATO, Payments, and On-Chain Fraud) that have a direct, measurable impact on business goals.
- Take full ownership of the end-to-end ML systems for Risk, from feature engineering and model development to live production monitoring and performance.
- Serve as the primary AI/ML voice for the Risk domain, collaborating with VPs and Directors in Product, Engineering, and Operations to turn complex business problems into a tangible ML roadmap.
- Work with our talent organization to attract, hire, and retain top-tier ML managers and engineers.
Benefits
- general: Bonus eligibility
- general: Equity eligibility
- general: Benefits (including medical, dental, vision and 401(k))
Tags & Categories
Answer 10 quick questions to check your fit for Senior Machine Learning Engineering Manager, Risk and Fraud @ Coinbase.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs