BlackRock is a global leader in investment management, risk management, and advisory services, with a presence in over 100 countries. Renowned for its innovative approach to financial technology and commitment to excellence, BlackRock serves a diverse range of clients including institutions, financial professionals, and individual investors. The company emphasizes sustainability, technological advancement, and client-centric solutions to maintain its position at the forefront of the financial industry.
About The Role
We are seeking a highly skilled and motivated AI Platform Engineer to join BlackRock's AI Platform Engineering team within the Aladdin Engineering division. This role offers an exceptional opportunity to influence the future of financial technology by designing and building scalable AI infrastructure that supports the firm's investment management and risk assessment platforms. As part of this team, you will be instrumental in shaping the AI ecosystem across the organization, ensuring seamless integration of AI models, and enabling advanced analytics capabilities. The ideal candidate will have extensive experience in cloud-native platform development, container orchestration, and AI/ML deployment, with a passion for innovation and excellence in engineering practices.
Qualifications
B.S. or M.S. degree in Computer Science, Engineering, or a related field.
Over 10 years of experience in software and platform engineering.
Proven expertise in designing scalable APIs, microservices, and cloud infrastructure.
Strong proficiency in Kubernetes, including Helm, Kustomize, and CRDs.
Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
Familiarity with containerization technologies like Docker and containerd.
Experience with CI/CD tools such as Jenkins, GitHub Actions, and ArgoCD.
Solid understanding of infrastructure as code (Terraform, CloudFormation), networking, security policies, and API gateways.
Programming proficiency in languages like Rust and C++.
Familiarity with data science tools such as PyTorch, Jax, and Python.
Experience working within Agile teams.
Responsibilities
Design, develop, and maintain the next-generation scalable AI platform to support BlackRock's investment management technologies.
Implement and manage Kubernetes clusters for deploying and scaling AI models efficiently.
Build platform abstractions to manage cloud-native infrastructure across AWS, GCP, or Azure environments.
Create and maintain automated CI/CD pipelines for continuous training, testing, and deployment of machine learning models.
Ensure the security, compliance, and reliability of the AI platform.
About The Company
BlackRock is a global leader in investment management, risk management, and advisory services, with a presence in over 100 countries. Renowned for its innovative approach to financial technology and commitment to excellence, BlackRock serves a diverse range of clients including institutions, financial professionals, and individual investors. The company emphasizes sustainability, technological advancement, and client-centric solutions to maintain its position at the forefront of the financial industry.
About The Role
We are seeking a highly skilled and motivated AI Platform Engineer to join BlackRock's AI Platform Engineering team within the Aladdin Engineering division. This role offers an exceptional opportunity to influence the future of financial technology by designing and building scalable AI infrastructure that supports the firm's investment management and risk assessment platforms. As part of this team, you will be instrumental in shaping the AI ecosystem across the organization, ensuring seamless integration of AI models, and enabling advanced analytics capabilities. The ideal candidate will have extensive experience in cloud-native platform development, container orchestration, and AI/ML deployment, with a passion for innovation and excellence in engineering practices.
Qualifications
B.S. or M.S. degree in Computer Science, Engineering, or a related field.
Over 10 years of experience in software and platform engineering.
Proven expertise in designing scalable APIs, microservices, and cloud infrastructure.
Strong proficiency in Kubernetes, including Helm, Kustomize, and CRDs.
Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
Familiarity with containerization technologies like Docker and containerd.
Experience with CI/CD tools such as Jenkins, GitHub Actions, and ArgoCD.
Solid understanding of infrastructure as code (Terraform, CloudFormation), networking, security policies, and API gateways.
Programming proficiency in languages like Rust and C++.
Familiarity with data science tools such as PyTorch, Jax, and Python.
Experience working within Agile teams.
Responsibilities
Design, develop, and maintain the next-generation scalable AI platform to support BlackRock's investment management technologies.
Implement and manage Kubernetes clusters for deploying and scaling AI models efficiently.
Build platform abstractions to manage cloud-native infrastructure across AWS, GCP, or Azure environments.
Create and maintain automated CI/CD pipelines for continuous training, testing, and deployment of machine learning models.
BlackRock is a global leader in investment management, risk management, and advisory services, with a presence in over 100 countries. Renowned for its innovative approach to financial technology and commitment to excellence, BlackRock serves a diverse range of clients including institutions, financial professionals, and individual investors. The company emphasizes sustainability, technological advancement, and client-centric solutions to maintain its position at the forefront of the financial industry.
About The Role
We are seeking a highly skilled and motivated AI Platform Engineer to join BlackRock's AI Platform Engineering team within the Aladdin Engineering division. This role offers an exceptional opportunity to influence the future of financial technology by designing and building scalable AI infrastructure that supports the firm's investment management and risk assessment platforms. As part of this team, you will be instrumental in shaping the AI ecosystem across the organization, ensuring seamless integration of AI models, and enabling advanced analytics capabilities. The ideal candidate will have extensive experience in cloud-native platform development, container orchestration, and AI/ML deployment, with a passion for innovation and excellence in engineering practices.
Qualifications
B.S. or M.S. degree in Computer Science, Engineering, or a related field.
Over 10 years of experience in software and platform engineering.
Proven expertise in designing scalable APIs, microservices, and cloud infrastructure.
Strong proficiency in Kubernetes, including Helm, Kustomize, and CRDs.
Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
Familiarity with containerization technologies like Docker and containerd.
Experience with CI/CD tools such as Jenkins, GitHub Actions, and ArgoCD.
Solid understanding of infrastructure as code (Terraform, CloudFormation), networking, security policies, and API gateways.
Programming proficiency in languages like Rust and C++.
Familiarity with data science tools such as PyTorch, Jax, and Python.
Experience working within Agile teams.
Responsibilities
Design, develop, and maintain the next-generation scalable AI platform to support BlackRock's investment management technologies.
Implement and manage Kubernetes clusters for deploying and scaling AI models efficiently.
Build platform abstractions to manage cloud-native infrastructure across AWS, GCP, or Azure environments.
Create and maintain automated CI/CD pipelines for continuous training, testing, and deployment of machine learning models.
Ensure the security, compliance, and reliability of the AI platform.
About The Company
BlackRock is a global leader in investment management, risk management, and advisory services, with a presence in over 100 countries. Renowned for its innovative approach to financial technology and commitment to excellence, BlackRock serves a diverse range of clients including institutions, financial professionals, and individual investors. The company emphasizes sustainability, technological advancement, and client-centric solutions to maintain its position at the forefront of the financial industry.
About The Role
We are seeking a highly skilled and motivated AI Platform Engineer to join BlackRock's AI Platform Engineering team within the Aladdin Engineering division. This role offers an exceptional opportunity to influence the future of financial technology by designing and building scalable AI infrastructure that supports the firm's investment management and risk assessment platforms. As part of this team, you will be instrumental in shaping the AI ecosystem across the organization, ensuring seamless integration of AI models, and enabling advanced analytics capabilities. The ideal candidate will have extensive experience in cloud-native platform development, container orchestration, and AI/ML deployment, with a passion for innovation and excellence in engineering practices.
Qualifications
B.S. or M.S. degree in Computer Science, Engineering, or a related field.
Over 10 years of experience in software and platform engineering.
Proven expertise in designing scalable APIs, microservices, and cloud infrastructure.
Strong proficiency in Kubernetes, including Helm, Kustomize, and CRDs.
Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
Familiarity with containerization technologies like Docker and containerd.
Experience with CI/CD tools such as Jenkins, GitHub Actions, and ArgoCD.
Solid understanding of infrastructure as code (Terraform, CloudFormation), networking, security policies, and API gateways.
Programming proficiency in languages like Rust and C++.
Familiarity with data science tools such as PyTorch, Jax, and Python.
Experience working within Agile teams.
Responsibilities
Design, develop, and maintain the next-generation scalable AI platform to support BlackRock's investment management technologies.
Implement and manage Kubernetes clusters for deploying and scaling AI models efficiently.
Build platform abstractions to manage cloud-native infrastructure across AWS, GCP, or Azure environments.
Create and maintain automated CI/CD pipelines for continuous training, testing, and deployment of machine learning models.
