Product Leader- MLOps Platform

Feb 25, 2024
Santa Clara, Cuba
... Not specified
... Intermediate
Full time
... Office work


WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. 

AMD together we advance_




THE ROLE:  

We seek a technically savvy machine learning platform product manager to set the vision and strategy for our model operationalization ecosystem, leveraging hands-on Kubernetes, CI/CD, and GPU training expertise to make high-level decisions enabling robust and scalable MLOps.

 

As member of the Data Center GPU Business Unit, your influence will be broad and long-lasting and be able to drive change in the growing space of ML/AI and HPC. Our goal is to build industry-leading solutions valued and loved by customers and partners who depend on high performance computing platforms to do their work. AMD will depend on you to define, build, and position GPU computing solutions to meet their needs.   

 

THE PERSON: 

We seek a machine learning platform product manager to set the end-to-end strategic vision for our model operationalization ecosystem. Leveraging hands-on expertise with MLOps components, you will make high-level platform decisions enabling robust, scalable deployments. Our ideal candidate has proven experience balancing innovation speed and reliability while managing systems supporting business-critical workloads. You will drive architectural direction and product roadmaps, using your own technical insights around infrastructure optimization. We want someone who has been in the trenches shoring up GPU training jobs while also coordinating cross-functional leadership for MLOps. Additionally, you will gather customer requirements and triangulate insights into executive presentations to align stakeholder vision.

 

KEY RESPONSIBILITIES: 

  • Lead requirements analysis by deeply understanding partner and customer needs for MLOps and ML infrastructure on AMD hardware.
  • Work closely with AMD engineering teams and leverage internal technical insights around AMD GPU optimization to translate requirements into product capabilities and roadmaps.
  • Foster partnerships with key MLOps platform vendors to enhance support for AMD GPU integration, ensuring efficient pipelines for development to production.
  • Conduct benchmarking and performance analysis of various MLOps solutions on AMD Instinct across metrics like time-to-train, cost efficiency, ease of use to drive recommendations.
  • Identify emerging MLOps solution companies to nurture partnerships with to fill enterprise software gaps on top of AMD hardware advancements.
  • Maintain pulse on latest innovations from AMD hardware, compilers, drivers relevant to ML training, deployment, inference - bridge communication across engineering orgs.

 PREFERRED EXPERIENCE: 

  • Experience building, deploying, and managing machine learning systems at scale with MLOps methodologies.
  • Working knowledge of Kubernetes and container orchestration - experience deploying models and jobs on Kubernetes.
  • Launching and monitoring large scale distributed jobs (batch processing, stream processing, graph analytics).
  • Background in Infrastructure-as-code tools (Terraform, Ansible, CloudFormation) to programmatically manage cluster environments.  
  • Container platforms like Docker, Kubernetes, OpenShift.
  • ML development environments such as MLflow, Kubeflow.
  • Monitoring, metrics, and logging for model performance and data pipelines (Prometheus, Grafana, etc.).
  • Cloud platforms (AWS, GCP, Azure) including services like managed Kubernetes.

ACADEMIC CREDENTIALS: 

  • Computer Science or Computer Engineering degree required. 

#LI-EV1

#LI-HYBRID 




At AMD, your base pay is one part of your total rewards package.  Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

 

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.   We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

At AMD, your base pay is one part of your total rewards package.  Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

 

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.   We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

THE ROLE:  

We seek a technically savvy machine learning platform product manager to set the vision and strategy for our model operationalization ecosystem, leveraging hands-on Kubernetes, CI/CD, and GPU training expertise to make high-level decisions enabling robust and scalable MLOps.

 

As member of the Data Center GPU Business Unit, your influence will be broad and long-lasting and be able to drive change in the growing space of ML/AI and HPC. Our goal is to build industry-leading solutions valued and loved by customers and partners who depend on high performance computing platforms to do their work. AMD will depend on you to define, build, and position GPU computing solutions to meet their needs.   

 

THE PERSON: 

We seek a machine learning platform product manager to set the end-to-end strategic vision for our model operationalization ecosystem. Leveraging hands-on expertise with MLOps components, you will make high-level platform decisions enabling robust, scalable deployments. Our ideal candidate has proven experience balancing innovation speed and reliability while managing systems supporting business-critical workloads. You will drive architectural direction and product roadmaps, using your own technical insights around infrastructure optimization. We want someone who has been in the trenches shoring up GPU training jobs while also coordinating cross-functional leadership for MLOps. Additionally, you will gather customer requirements and triangulate insights into executive presentations to align stakeholder vision.

 

KEY RESPONSIBILITIES: 

  • Lead requirements analysis by deeply understanding partner and customer needs for MLOps and ML infrastructure on AMD hardware.
  • Work closely with AMD engineering teams and leverage internal technical insights around AMD GPU optimization to translate requirements into product capabilities and roadmaps.
  • Foster partnerships with key MLOps platform vendors to enhance support for AMD GPU integration, ensuring efficient pipelines for development to production.
  • Conduct benchmarking and performance analysis of various MLOps solutions on AMD Instinct across metrics like time-to-train, cost efficiency, ease of use to drive recommendations.
  • Identify emerging MLOps solution companies to nurture partnerships with to fill enterprise software gaps on top of AMD hardware advancements.
  • Maintain pulse on latest innovations from AMD hardware, compilers, drivers relevant to ML training, deployment, inference - bridge communication across engineering orgs.

 PREFERRED EXPERIENCE: 

  • Experience building, deploying, and managing machine learning systems at scale with MLOps methodologies.
  • Working knowledge of Kubernetes and container orchestration - experience deploying models and jobs on Kubernetes.
  • Launching and monitoring large scale distributed jobs (batch processing, stream processing, graph analytics).
  • Background in Infrastructure-as-code tools (Terraform, Ansible, CloudFormation) to programmatically manage cluster environments.  
  • Container platforms like Docker, Kubernetes, OpenShift.
  • ML development environments such as MLflow, Kubeflow.
  • Monitoring, metrics, and logging for model performance and data pipelines (Prometheus, Grafana, etc.).
  • Cloud platforms (AWS, GCP, Azure) including services like managed Kubernetes.

ACADEMIC CREDENTIALS: 

  • Computer Science or Computer Engineering degree required. 

#LI-EV1

#LI-HYBRID 

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