Senior Staff Machine Learning Engineer - Risk AI/ML
Coinbase
Senior Staff Machine Learning Engineer - Risk AI/ML
Job Description
Responsibilities
- Lead Strategic AI/ML Initiatives: Drive the end-to-end design and deployment of AI/ML models and systems that scale to millions of users. You will investigate and harness cutting-edge methodologies (e.g., large-scale deep learning, LLMs, GNNs, reinforcement learning) to address diverse challenges like fraud detection, recommender systems, feed ranking, and risk assessment.
- Architect Scalable Models & Systems: Architect and build production-grade AI/ML models & pipelines, that enable low-latency, high-reliability predictions. You will develop and deploy robust, low-maintenance applied AI/ML solutions
- Drive Execution & Collaboration: Deliver high-quality, measurable results while managing ambiguity, prioritizing technical debt, and ensuring systems evolve with business growth. You must have solid communication skills to collaborate with and influence stakeholders with various technical and non-technical backgrounds.
- Elevate AI/ML & Engineering Excellence, Mentorship: Provide technical guidance and mentorship, elevating engineering excellence across the organization. You will help democratize access to AI/ML by creating onboarding codelabs, tools, and infrastructure to foster a culture of widespread AI/ML across the team, org and Coinbase.
Required Qualifications
- 10+ years of professional experience in software engineering and/or AI/ML, including significant experience deploying AI/ML systems into production.
- Passion & Values: A passion for building an open financial system that connects the world and a strong desire to protect good users from bad actors. You are motivated by the challenges of fighting fraud, detecting scams, preventing account takeovers, and generally thwarting "baddies." You exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder.
- Deep AI/ML Expertise: Expertise in one or more areas of applied AI/ML (e.g., Risk ML, Gradient Boosting trees, large-scale deep learning, NLP/LLMs, computer vision, recommender systems, reinforcement learning, GNNs).
- Strong Technical & Coding Skills: Strong coding skills (e.g., Python) with deep experience in AI/ML frameworks (TensorFlow, PyTorch, etc). Experience building backend systems at scale with a focus on data processing, AI/ML, or analytics.
- Technical Leadership: Demonstrated ability to lead complex, cross-team technical initiatives and deliver impactful AI/ML solutions at scale.
- Strategic Communication: Strong communication and leadership skills, with experience influencing technical direction across engineering, product, and leadership teams.
- Mentorship: A proven track record of mentoring senior engineers and raising the technical bar on engineering teams.
Preferred Qualifications
- Master’s or PhD in Computer Science, AI/ML, Data Mining, Statistics, or related technical field.
- Knowledge of modern data and AI/ML infrastructure (e.g., Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, Hadoop, Hive).
- Familiarity with MLOps best practices, including monitoring, retraining, and continuous improvement of production models.
- Experience with model interpretability and responsible AI.
- Experience with data analysis and visualization.
Required Skills
- software engineering
- AI/ML
- deploying AI/ML systems into production
- Python
- AI/ML frameworks (TensorFlow, PyTorch)
- building backend systems at scale
- data processing
- analytics
- technical leadership
- communication
- mentorship
- Risk ML
- Gradient Boosting trees
- large-scale deep learning
- NLP/LLMs
- computer vision
- recommender systems
- reinforcement learning
- GNNs
Benefits
- bonus eligibility
- equity eligibility
- benefits (including medical, dental, vision and 401(k))
Salary Range
$262650 - $309000 USD
Locations
- USA, United States (Remote)
Salary
262,650 - 309,000 USD / yearly
Skills Required
- software engineeringintermediate
- AI/MLintermediate
- deploying AI/ML systems into productionintermediate
- Pythonintermediate
- AI/ML frameworks (TensorFlow, PyTorch)intermediate
- building backend systems at scaleintermediate
- data processingintermediate
- analyticsintermediate
- technical leadershipintermediate
- communicationintermediate
- mentorshipintermediate
- Risk MLintermediate
- Gradient Boosting treesintermediate
- large-scale deep learningintermediate
- NLP/LLMsintermediate
- computer visionintermediate
- recommender systemsintermediate
- reinforcement learningintermediate
- GNNsintermediate
Required Qualifications
- 10+ years of professional experience in software engineering and/or AI/ML, including significant experience deploying AI/ML systems into production. (experience)
- Passion & Values: A passion for building an open financial system that connects the world and a strong desire to protect good users from bad actors. You are motivated by the challenges of fighting fraud, detecting scams, preventing account takeovers, and generally thwarting "baddies." You exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder. (experience)
- Deep AI/ML Expertise: Expertise in one or more areas of applied AI/ML (e.g., Risk ML, Gradient Boosting trees, large-scale deep learning, NLP/LLMs, computer vision, recommender systems, reinforcement learning, GNNs). (experience)
- Strong Technical & Coding Skills: Strong coding skills (e.g., Python) with deep experience in AI/ML frameworks (TensorFlow, PyTorch, etc). Experience building backend systems at scale with a focus on data processing, AI/ML, or analytics. (experience)
- Technical Leadership: Demonstrated ability to lead complex, cross-team technical initiatives and deliver impactful AI/ML solutions at scale. (experience)
- Strategic Communication: Strong communication and leadership skills, with experience influencing technical direction across engineering, product, and leadership teams. (experience)
- Mentorship: A proven track record of mentoring senior engineers and raising the technical bar on engineering teams. (experience)
Preferred Qualifications
- Master’s or PhD in Computer Science, AI/ML, Data Mining, Statistics, or related technical field. (experience)
- Knowledge of modern data and AI/ML infrastructure (e.g., Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, Hadoop, Hive). (experience)
- Familiarity with MLOps best practices, including monitoring, retraining, and continuous improvement of production models. (experience)
- Experience with model interpretability and responsible AI. (experience)
- Experience with data analysis and visualization. (experience)
Responsibilities
- Lead Strategic AI/ML Initiatives: Drive the end-to-end design and deployment of AI/ML models and systems that scale to millions of users. You will investigate and harness cutting-edge methodologies (e.g., large-scale deep learning, LLMs, GNNs, reinforcement learning) to address diverse challenges like fraud detection, recommender systems, feed ranking, and risk assessment.
- Architect Scalable Models & Systems: Architect and build production-grade AI/ML models & pipelines, that enable low-latency, high-reliability predictions. You will develop and deploy robust, low-maintenance applied AI/ML solutions
- Drive Execution & Collaboration: Deliver high-quality, measurable results while managing ambiguity, prioritizing technical debt, and ensuring systems evolve with business growth. You must have solid communication skills to collaborate with and influence stakeholders with various technical and non-technical backgrounds.
- Elevate AI/ML & Engineering Excellence, Mentorship: Provide technical guidance and mentorship, elevating engineering excellence across the organization. You will help democratize access to AI/ML by creating onboarding codelabs, tools, and infrastructure to foster a culture of widespread AI/ML across the team, org and Coinbase.
Benefits
- general: bonus eligibility
- general: equity eligibility
- general: benefits (including medical, dental, vision and 401(k))
Tags & Categories
Senior Staff Machine Learning Engineer - Risk AI/ML
Coinbase
Senior Staff Machine Learning Engineer - Risk AI/ML
Job Description
Responsibilities
- Lead Strategic AI/ML Initiatives: Drive the end-to-end design and deployment of AI/ML models and systems that scale to millions of users. You will investigate and harness cutting-edge methodologies (e.g., large-scale deep learning, LLMs, GNNs, reinforcement learning) to address diverse challenges like fraud detection, recommender systems, feed ranking, and risk assessment.
- Architect Scalable Models & Systems: Architect and build production-grade AI/ML models & pipelines, that enable low-latency, high-reliability predictions. You will develop and deploy robust, low-maintenance applied AI/ML solutions
- Drive Execution & Collaboration: Deliver high-quality, measurable results while managing ambiguity, prioritizing technical debt, and ensuring systems evolve with business growth. You must have solid communication skills to collaborate with and influence stakeholders with various technical and non-technical backgrounds.
- Elevate AI/ML & Engineering Excellence, Mentorship: Provide technical guidance and mentorship, elevating engineering excellence across the organization. You will help democratize access to AI/ML by creating onboarding codelabs, tools, and infrastructure to foster a culture of widespread AI/ML across the team, org and Coinbase.
Required Qualifications
- 10+ years of professional experience in software engineering and/or AI/ML, including significant experience deploying AI/ML systems into production.
- Passion & Values: A passion for building an open financial system that connects the world and a strong desire to protect good users from bad actors. You are motivated by the challenges of fighting fraud, detecting scams, preventing account takeovers, and generally thwarting "baddies." You exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder.
- Deep AI/ML Expertise: Expertise in one or more areas of applied AI/ML (e.g., Risk ML, Gradient Boosting trees, large-scale deep learning, NLP/LLMs, computer vision, recommender systems, reinforcement learning, GNNs).
- Strong Technical & Coding Skills: Strong coding skills (e.g., Python) with deep experience in AI/ML frameworks (TensorFlow, PyTorch, etc). Experience building backend systems at scale with a focus on data processing, AI/ML, or analytics.
- Technical Leadership: Demonstrated ability to lead complex, cross-team technical initiatives and deliver impactful AI/ML solutions at scale.
- Strategic Communication: Strong communication and leadership skills, with experience influencing technical direction across engineering, product, and leadership teams.
- Mentorship: A proven track record of mentoring senior engineers and raising the technical bar on engineering teams.
Preferred Qualifications
- Master’s or PhD in Computer Science, AI/ML, Data Mining, Statistics, or related technical field.
- Knowledge of modern data and AI/ML infrastructure (e.g., Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, Hadoop, Hive).
- Familiarity with MLOps best practices, including monitoring, retraining, and continuous improvement of production models.
- Experience with model interpretability and responsible AI.
- Experience with data analysis and visualization.
Required Skills
- software engineering
- AI/ML
- deploying AI/ML systems into production
- Python
- AI/ML frameworks (TensorFlow, PyTorch)
- building backend systems at scale
- data processing
- analytics
- technical leadership
- communication
- mentorship
- Risk ML
- Gradient Boosting trees
- large-scale deep learning
- NLP/LLMs
- computer vision
- recommender systems
- reinforcement learning
- GNNs
Benefits
- bonus eligibility
- equity eligibility
- benefits (including medical, dental, vision and 401(k))
Salary Range
$262650 - $309000 USD
Locations
- USA, United States (Remote)
Salary
262,650 - 309,000 USD / yearly
Skills Required
- software engineeringintermediate
- AI/MLintermediate
- deploying AI/ML systems into productionintermediate
- Pythonintermediate
- AI/ML frameworks (TensorFlow, PyTorch)intermediate
- building backend systems at scaleintermediate
- data processingintermediate
- analyticsintermediate
- technical leadershipintermediate
- communicationintermediate
- mentorshipintermediate
- Risk MLintermediate
- Gradient Boosting treesintermediate
- large-scale deep learningintermediate
- NLP/LLMsintermediate
- computer visionintermediate
- recommender systemsintermediate
- reinforcement learningintermediate
- GNNsintermediate
Required Qualifications
- 10+ years of professional experience in software engineering and/or AI/ML, including significant experience deploying AI/ML systems into production. (experience)
- Passion & Values: A passion for building an open financial system that connects the world and a strong desire to protect good users from bad actors. You are motivated by the challenges of fighting fraud, detecting scams, preventing account takeovers, and generally thwarting "baddies." You exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder. (experience)
- Deep AI/ML Expertise: Expertise in one or more areas of applied AI/ML (e.g., Risk ML, Gradient Boosting trees, large-scale deep learning, NLP/LLMs, computer vision, recommender systems, reinforcement learning, GNNs). (experience)
- Strong Technical & Coding Skills: Strong coding skills (e.g., Python) with deep experience in AI/ML frameworks (TensorFlow, PyTorch, etc). Experience building backend systems at scale with a focus on data processing, AI/ML, or analytics. (experience)
- Technical Leadership: Demonstrated ability to lead complex, cross-team technical initiatives and deliver impactful AI/ML solutions at scale. (experience)
- Strategic Communication: Strong communication and leadership skills, with experience influencing technical direction across engineering, product, and leadership teams. (experience)
- Mentorship: A proven track record of mentoring senior engineers and raising the technical bar on engineering teams. (experience)
Preferred Qualifications
- Master’s or PhD in Computer Science, AI/ML, Data Mining, Statistics, or related technical field. (experience)
- Knowledge of modern data and AI/ML infrastructure (e.g., Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, Hadoop, Hive). (experience)
- Familiarity with MLOps best practices, including monitoring, retraining, and continuous improvement of production models. (experience)
- Experience with model interpretability and responsible AI. (experience)
- Experience with data analysis and visualization. (experience)
Responsibilities
- Lead Strategic AI/ML Initiatives: Drive the end-to-end design and deployment of AI/ML models and systems that scale to millions of users. You will investigate and harness cutting-edge methodologies (e.g., large-scale deep learning, LLMs, GNNs, reinforcement learning) to address diverse challenges like fraud detection, recommender systems, feed ranking, and risk assessment.
- Architect Scalable Models & Systems: Architect and build production-grade AI/ML models & pipelines, that enable low-latency, high-reliability predictions. You will develop and deploy robust, low-maintenance applied AI/ML solutions
- Drive Execution & Collaboration: Deliver high-quality, measurable results while managing ambiguity, prioritizing technical debt, and ensuring systems evolve with business growth. You must have solid communication skills to collaborate with and influence stakeholders with various technical and non-technical backgrounds.
- Elevate AI/ML & Engineering Excellence, Mentorship: Provide technical guidance and mentorship, elevating engineering excellence across the organization. You will help democratize access to AI/ML by creating onboarding codelabs, tools, and infrastructure to foster a culture of widespread AI/ML across the team, org and Coinbase.
Benefits
- general: bonus eligibility
- general: equity eligibility
- general: benefits (including medical, dental, vision and 401(k))
Tags & Categories