Company:Qualcomm Technologies, Inc.

Job Area:Engineering Group, Engineering Group > Software Engineering

General Summary:

We are seeking a highly skilled and experienced MLOps Engineer to join our team and contribute to the development and maintenance of our ML platform both on premises and AWS Cloud. As a MLOps Engineer, you will be responsible for architecting, deploying, and optimizing the ML & Data platform that supports training of Machine Learning Models using NVIDIA DGX clusters and the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana. Your expertise in AWS services such as EKS, EC2, VPC, IAM, S3, and EFS will be crucial in ensuring the smooth operation and scalability of our ML infrastructure.

You will work closely with cross-functional teams, including data scientists, software engineers, and infrastructure specialists, to ensure the smooth operation and scalability of our ML infrastructure. Your expertise in MLOps, DevOps, and knowledge of GPU clusters will be vital in enabling efficient training and deployment of ML models.

Responsibilities will include:

·       Architect, develop, and maintain the ML platform to support training and inference of ML models.

·       Design and implement scalable and reliable infrastructure solutions for NVIDIA clusters both on premises and AWS Cloud.

·       Collaborate with data scientists and software engineers to define requirements and ensure seamless integration of ML and Data workflows into the platform.

·       Optimize the platform’s performance and scalability, considering factors such as GPU resource utilization, data ingestion, model training, and deployment.

·       Monitor and troubleshoot system performance, identifying and resolving issues to ensure the availability and reliability of the ML platform.

·       Implement and maintain CI/CD pipelines for automated model training, evaluation, and deployment using technologies like ArgoCD and Argo Workflow.

·       Implement and maintain monitoring stack using Prometheus and Grafana to ensure the health and performance of the platform.

·       Manage AWS services including EKS, EC2, VPC, IAM, S3, and EFS to support the platform.

·       Implement logging and monitoring solutions using AWS CloudWatch and other relevant tools.

·       Stay updated with the latest advancements in MLOps, distributed computing, and GPU acceleration technologies, and proactively propose improvements to enhance the ML platform.

What are we looking for:

·       Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

·       Proven experience as an MLOps Engineer or similar role, with a focus on large-scale ML and/or Data infrastructure and GPU clusters.

·       Strong expertise in configuring and optimizing NVIDIA DGX clusters for deep learning workloads.

·       Proficient in using the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana.

·       Solid programming skills in languages like Python, Go and experience with relevant ML frameworks (e.g., TensorFlow, PyTorch).

·       In-depth understanding of distributed computing, parallel computing, and GPU acceleration techniques.

·       Familiarity with containerization technologies such as Docker and orchestration tools.

·       Experience with CI/CD pipelines and automation tools for ML workflows (e.g., Jenkins, GitHub, ArgoCD).

·       Experience with AWS services such as EKS, EC2, VPC, IAM, S3, and EFS.

·       Experience with AWS logging and monitoring tools.

·       Strong problem-solving skills and the ability to troubleshoot complex technical issues.

·       Excellent communication and collaboration skills to work effectively within a cross-functional team.

We would love to see:

·       Experience with training and deploying models.

·       Knowledge of ML model optimization techniques and memory management on GPUs.

·       Familiarity with ML-specific data storage and retrieval systems.

·       Understanding of security and compliance requirements in ML infrastructure.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.

• 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

 

Pay range and Other Compensation & Benefits:

$134,800.00 - $202,200.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm.  We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus).  In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link.

If you would like more information about this role, please contact Qualcomm Careers.