Senior Machine Learning Engineer, Platform
Coinbase
Senior Machine Learning Engineer, Platform
Job Description
Responsibilities
- Investigate and harness cutting-edge machine learning methodologies, including deep learning, large language models (LLMs), and graph neural networks, to address diverse challenges throughout the company. These challenges encompass areas such as fraud detection, feed ranking, recommendation systems, targeting, chatbots, and blockchain mining.
- Develop and deploy robust, low-maintenance applied machine learning solutions in a production environment.
- Create onboarding codelabs, tools, and infrastructure to democratize access to machine learning resources across Coinbase, fostering a culture of widespread ML utilization.
Required Qualifications
- 5+yrs of industry experience as a machine learning and software engineer
- Experience building backend systems at scale with a focus on data processing/machine learning/analytics.
- Experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.
- Working knowledge in one or more of the following: data mining, information retrieval, advanced statistics or natural language processing, computer vision.
- Exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder.
Preferred Qualifications
- BS, MS, PhD degree in Computer Science, Machine Learning, Data Mining, Statistics, or related technical field.
- Knowledge of Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, Hadoop, Hive.
- Experience with Python.
- Experience with model interpretability, responsible AI.
- Experience with data analysis and visualization.
Required Skills
- machine learning
- software engineering
- backend systems at scale
- data processing
- analytics
- LLMs
- GNN
- Deep Learning
- Logistic Regression
- Gradient Boosting trees
- data mining
- information retrieval
- advanced statistics
- natural language processing
- computer vision
- add positive energy
- communicate clearly
- be curious
- be a builder
- Apache Airflow
- Spark
- Flink
- Kafka/Kinesis
- Snowflake
- Hadoop
- Hive
- Python
- model interpretability
- responsible AI
- data analysis
- visualization
Locations
- Mumbai, Maharashtra, India, India, Maharashtra, United States (Remote)
Salary
Estimated Salary Rangemedium confidence
180,000 - 300,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- machine learningintermediate
- software engineeringintermediate
- backend systems at scaleintermediate
- data processingintermediate
- analyticsintermediate
- LLMsintermediate
- GNNintermediate
- Deep Learningintermediate
- Logistic Regressionintermediate
- Gradient Boosting treesintermediate
- data miningintermediate
- information retrievalintermediate
- advanced statisticsintermediate
- natural language processingintermediate
- computer visionintermediate
- add positive energyintermediate
- communicate clearlyintermediate
- be curiousintermediate
- be a builderintermediate
- Apache Airflowintermediate
- Sparkintermediate
- Flinkintermediate
- Kafka/Kinesisintermediate
- Snowflakeintermediate
- Hadoopintermediate
- Hiveintermediate
- Pythonintermediate
- model interpretabilityintermediate
- responsible AIintermediate
- data analysisintermediate
- visualizationintermediate
Required Qualifications
- 5+yrs of industry experience as a machine learning and software engineer (experience)
- Experience building backend systems at scale with a focus on data processing/machine learning/analytics. (experience)
- Experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc. (experience)
- Working knowledge in one or more of the following: data mining, information retrieval, advanced statistics or natural language processing, computer vision. (experience)
- Exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder. (experience)
Preferred Qualifications
- BS, MS, PhD degree in Computer Science, Machine Learning, Data Mining, Statistics, or related technical field. (experience)
- Knowledge of Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, Hadoop, Hive. (experience)
- Experience with Python. (experience)
- Experience with model interpretability, responsible AI. (experience)
- Experience with data analysis and visualization. (experience)
Responsibilities
- Investigate and harness cutting-edge machine learning methodologies, including deep learning, large language models (LLMs), and graph neural networks, to address diverse challenges throughout the company. These challenges encompass areas such as fraud detection, feed ranking, recommendation systems, targeting, chatbots, and blockchain mining.
- Develop and deploy robust, low-maintenance applied machine learning solutions in a production environment.
- Create onboarding codelabs, tools, and infrastructure to democratize access to machine learning resources across Coinbase, fostering a culture of widespread ML utilization.
Tags & Categories
Senior Machine Learning Engineer, Platform
Coinbase
Senior Machine Learning Engineer, Platform
Job Description
Responsibilities
- Investigate and harness cutting-edge machine learning methodologies, including deep learning, large language models (LLMs), and graph neural networks, to address diverse challenges throughout the company. These challenges encompass areas such as fraud detection, feed ranking, recommendation systems, targeting, chatbots, and blockchain mining.
- Develop and deploy robust, low-maintenance applied machine learning solutions in a production environment.
- Create onboarding codelabs, tools, and infrastructure to democratize access to machine learning resources across Coinbase, fostering a culture of widespread ML utilization.
Required Qualifications
- 5+yrs of industry experience as a machine learning and software engineer
- Experience building backend systems at scale with a focus on data processing/machine learning/analytics.
- Experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.
- Working knowledge in one or more of the following: data mining, information retrieval, advanced statistics or natural language processing, computer vision.
- Exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder.
Preferred Qualifications
- BS, MS, PhD degree in Computer Science, Machine Learning, Data Mining, Statistics, or related technical field.
- Knowledge of Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, Hadoop, Hive.
- Experience with Python.
- Experience with model interpretability, responsible AI.
- Experience with data analysis and visualization.
Required Skills
- machine learning
- software engineering
- backend systems at scale
- data processing
- analytics
- LLMs
- GNN
- Deep Learning
- Logistic Regression
- Gradient Boosting trees
- data mining
- information retrieval
- advanced statistics
- natural language processing
- computer vision
- add positive energy
- communicate clearly
- be curious
- be a builder
- Apache Airflow
- Spark
- Flink
- Kafka/Kinesis
- Snowflake
- Hadoop
- Hive
- Python
- model interpretability
- responsible AI
- data analysis
- visualization
Locations
- Mumbai, Maharashtra, India, India, Maharashtra, United States (Remote)
Salary
Estimated Salary Rangemedium confidence
180,000 - 300,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- machine learningintermediate
- software engineeringintermediate
- backend systems at scaleintermediate
- data processingintermediate
- analyticsintermediate
- LLMsintermediate
- GNNintermediate
- Deep Learningintermediate
- Logistic Regressionintermediate
- Gradient Boosting treesintermediate
- data miningintermediate
- information retrievalintermediate
- advanced statisticsintermediate
- natural language processingintermediate
- computer visionintermediate
- add positive energyintermediate
- communicate clearlyintermediate
- be curiousintermediate
- be a builderintermediate
- Apache Airflowintermediate
- Sparkintermediate
- Flinkintermediate
- Kafka/Kinesisintermediate
- Snowflakeintermediate
- Hadoopintermediate
- Hiveintermediate
- Pythonintermediate
- model interpretabilityintermediate
- responsible AIintermediate
- data analysisintermediate
- visualizationintermediate
Required Qualifications
- 5+yrs of industry experience as a machine learning and software engineer (experience)
- Experience building backend systems at scale with a focus on data processing/machine learning/analytics. (experience)
- Experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc. (experience)
- Working knowledge in one or more of the following: data mining, information retrieval, advanced statistics or natural language processing, computer vision. (experience)
- Exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder. (experience)
Preferred Qualifications
- BS, MS, PhD degree in Computer Science, Machine Learning, Data Mining, Statistics, or related technical field. (experience)
- Knowledge of Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, Hadoop, Hive. (experience)
- Experience with Python. (experience)
- Experience with model interpretability, responsible AI. (experience)
- Experience with data analysis and visualization. (experience)
Responsibilities
- Investigate and harness cutting-edge machine learning methodologies, including deep learning, large language models (LLMs), and graph neural networks, to address diverse challenges throughout the company. These challenges encompass areas such as fraud detection, feed ranking, recommendation systems, targeting, chatbots, and blockchain mining.
- Develop and deploy robust, low-maintenance applied machine learning solutions in a production environment.
- Create onboarding codelabs, tools, and infrastructure to democratize access to machine learning resources across Coinbase, fostering a culture of widespread ML utilization.
Tags & Categories