Avature
Graph Engineer
Avature, Washington, District of Columbia, us, 20022
The Carlyle Group is a prestigious global private equity firm seeking to strengthen its data science capabilities. A key step in this initiative is the development of Carlyle’s internal knowledge graph to ensure an accurate, comprehensive dataset foundation for various analysis and prediction use cases. Carlyle is currently seeking a highly skilled Graph Engineer with extensive expertise in graph technologies, distributed computing, knowledge graphs, and machine learning applications.Responsibilities
Work with stakeholders to ideate, capture and design solutions to meet the business requirements.Supervise and coach junior team members to tackle challenging engineering tasks as a team.Lead the design, implementation, and maintenance of our internal knowledge graph, ensuring accuracy and comprehensiveness to serve as a robust foundation for analytical and predictive applications.Develop and deploy advanced graph algorithms and machine learning models, with a particular focus on solving problems such as entity alignment using technologies like Neo4j, PySpark, PyTorch, and Graph Neural Networks.Work closely with data scientists and data engineers to incrementally and securely build out knowledge graph-driven AI solutions.Collaborate with product management and development teams to translate customer data and requirements into actionable product and solution insights.Maintain stringent SLAs for datasets and processes running in production.Research and experiment with emerging technologies and tools in the graph and AI domains, ensuring Carlyle’s solutions stay ahead of the curve.Establish and reinforce disciplined software engineering processes and best practices within the team and broader organization.Qualifications
Education & CertificatesConcentration in Computer Science, Math, Physics or other engineering related field, preferredMasters or PhD in STEM field, preferredProfessional ExperienceMinimum of 6 years’ of hands-on Graph Engineering, Data Science and/or Machine Learning experience, requiredMinimum of 2 years of being at a leadership role (staff manager, technical lead or equivalent), requiredExperience in the financial services or private equity industry, preferredStrong algorithm, data structures, and coding background with Python.Proficiency in SQL, hands-on experience with industrial RDBMS (like Snowflake, SparkSQL).Proficiency with data pipeline and workflow management tools like DBT, Apache Airflow and stream-processing systems like Spark Streaming, Apache Kafka.Robust knowledge and experience in implementing graph analytics solutions in distributed systems, including community detection/understanding, pattern matching, sub-graph extraction, and importance ranking.Experience with knowledge graph stores such as Neo4j (or its equivalent TigerGraph, Neptune, etc.), and surrounding semantic technology (OWL, RDF, SWRL, SPARQL, JSON-LD) is a significant plus.Deep understanding of modern vector/embedding-based graph representation techniques with proven experience in designing and implementing algorithms for their generation.Mastery of Pytorch frameworks for implementing and optimizing deep learning algorithms for both training quality and serving performance.Experience working with massive datasets (billion level of entities and edges).Excellent communication skills required, both verbal and written.Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by The Carlyle Group.Company Information
The Carlyle Group (NASDAQ: CG) is a global investment firm with $385 billion of assets under management and more than half of the AUM managed by women, across 562 investment vehicles as of June 30, 2023. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,200 professionals operating in 29 offices in North America, South America, Europe, the Middle East, Asia and Australia. Carlyle places an emphasis on development, retention and inclusion as supported by our internal processes and seven Employee Resource Groups (ERGs). Carlyle's purpose is to invest wisely and create value on behalf of its investors, which range from public and private pension funds to wealthy individuals and families to sovereign wealth funds, unions and corporations. Carlyle invests across three segments - Global Private Equity, Global Credit and Investment Solutions - and has expertise in various industries, including: aerospace, defense & government services, consumer & retail, energy, financial services, healthcare, industrial, real estate, technology & business services, telecommunications & media and transportation. At Carlyle, we know that diverse teams perform better, so we seek to create a community where we continually exchange insights, embrace different perspectives and leverage diversity as a competitive advantage. That is why we are committed to growing and cultivating teams that include people with a variety of perspectives, people who provide unique lenses through which to view potential deals, support and run our business.
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Work with stakeholders to ideate, capture and design solutions to meet the business requirements.Supervise and coach junior team members to tackle challenging engineering tasks as a team.Lead the design, implementation, and maintenance of our internal knowledge graph, ensuring accuracy and comprehensiveness to serve as a robust foundation for analytical and predictive applications.Develop and deploy advanced graph algorithms and machine learning models, with a particular focus on solving problems such as entity alignment using technologies like Neo4j, PySpark, PyTorch, and Graph Neural Networks.Work closely with data scientists and data engineers to incrementally and securely build out knowledge graph-driven AI solutions.Collaborate with product management and development teams to translate customer data and requirements into actionable product and solution insights.Maintain stringent SLAs for datasets and processes running in production.Research and experiment with emerging technologies and tools in the graph and AI domains, ensuring Carlyle’s solutions stay ahead of the curve.Establish and reinforce disciplined software engineering processes and best practices within the team and broader organization.Qualifications
Education & CertificatesConcentration in Computer Science, Math, Physics or other engineering related field, preferredMasters or PhD in STEM field, preferredProfessional ExperienceMinimum of 6 years’ of hands-on Graph Engineering, Data Science and/or Machine Learning experience, requiredMinimum of 2 years of being at a leadership role (staff manager, technical lead or equivalent), requiredExperience in the financial services or private equity industry, preferredStrong algorithm, data structures, and coding background with Python.Proficiency in SQL, hands-on experience with industrial RDBMS (like Snowflake, SparkSQL).Proficiency with data pipeline and workflow management tools like DBT, Apache Airflow and stream-processing systems like Spark Streaming, Apache Kafka.Robust knowledge and experience in implementing graph analytics solutions in distributed systems, including community detection/understanding, pattern matching, sub-graph extraction, and importance ranking.Experience with knowledge graph stores such as Neo4j (or its equivalent TigerGraph, Neptune, etc.), and surrounding semantic technology (OWL, RDF, SWRL, SPARQL, JSON-LD) is a significant plus.Deep understanding of modern vector/embedding-based graph representation techniques with proven experience in designing and implementing algorithms for their generation.Mastery of Pytorch frameworks for implementing and optimizing deep learning algorithms for both training quality and serving performance.Experience working with massive datasets (billion level of entities and edges).Excellent communication skills required, both verbal and written.Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by The Carlyle Group.Company Information
The Carlyle Group (NASDAQ: CG) is a global investment firm with $385 billion of assets under management and more than half of the AUM managed by women, across 562 investment vehicles as of June 30, 2023. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,200 professionals operating in 29 offices in North America, South America, Europe, the Middle East, Asia and Australia. Carlyle places an emphasis on development, retention and inclusion as supported by our internal processes and seven Employee Resource Groups (ERGs). Carlyle's purpose is to invest wisely and create value on behalf of its investors, which range from public and private pension funds to wealthy individuals and families to sovereign wealth funds, unions and corporations. Carlyle invests across three segments - Global Private Equity, Global Credit and Investment Solutions - and has expertise in various industries, including: aerospace, defense & government services, consumer & retail, energy, financial services, healthcare, industrial, real estate, technology & business services, telecommunications & media and transportation. At Carlyle, we know that diverse teams perform better, so we seek to create a community where we continually exchange insights, embrace different perspectives and leverage diversity as a competitive advantage. That is why we are committed to growing and cultivating teams that include people with a variety of perspectives, people who provide unique lenses through which to view potential deals, support and run our business.
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