Posted:
8/29/2024, 1:52:01 AM
Location(s):
Sunnyvale, California, United States ⋅ California, United States
Experience Level(s):
Junior ⋅ Mid Level ⋅ Senior
Field(s):
AI & Machine Learning ⋅ DevOps & Infrastructure ⋅ Software Engineering
Position: Software Engineer III
Location: 860 W. California Avenue, Sunnyvale, CA 94086
Duties: Analyze and carry out data processing on annotated image datasets using Voxel FiftyOne APIs. Automate and scale Machine Learning Operations (MLOps) tasks using GCP services such as Vertex AI Pipelines and Dataflow Jobs to process data and train Machine Learning (ML) models. Maintain existing Kubeflow pipelines and regularly improve and update pipeline Software Development Kits (SDKs) through internal tooling. Create Kubeflow pipeline templates for easy usage and deployment of training pipelines. Develop reusable Kubeflow components for easy plug and play across different pipelines to carry out isolated cacheable tasks in pipelines. Develop new pipelines and new tooling repos as needed for ML tasks such as image recognition, instance segmentation, object detection, and object tracking. Record and relay information for usage of developed tools and pipelines to AI Engineers through well described usage documents. Incorporate Weights and Biases into Kubeflow components to record model and data artifacts to track creation, usage, and other metadata across time in Kubeflow pipelines. Track system metrics such as GPU, CPU, memory, and network usage during training or other data processing tasks through Weights and Biases. Maintain code bases on GitHub and add necessary documentation to repos for usage. Ensure code builds are up and running for any production or dev GitHub repos. Debug issues with CI/CD pipelines across Jenkins builds. Debug issues for any failing production Vertex AI pipelines with AI Engineers to ensure quick recovery. Use fail safe mechanisms such as caching so that large scale data pipelines can be restarted from point of failure. Use ML libraries like PyTorch, TensorFlow, and ONNX to interact and query ML models. Implement tools to utilize data science frameworks like Pandas, Numpy, and SciPy for algorithms and calculations. Use CUDA to allow components, containers, and code packages that utilize GPU to speed up large scale data processing. Containerize Kubeflow components in Docker containers to allow easy dependency resolution and create lightweight standalone packages. Use data science libraries like NumPy, SciPy, and Pandas to process and analyze data in Python. Carry out the unit testing of components, integration testing of pipelines, and regression testing of automated systems to ensure failure is avoided in production.
Minimum education and experience required: Master’s degree or equivalent in Computer Science, Engineering (any), or a related field. Position does not require specific years of experience but requires listed skills.
Skills Required: Experience with backend server design, API development, and testing using Python. Experience with backend server design, API development, and testing using Java. Experience with backend server and publish-subscribe messaging using TypeScript. Experience with RESTful architecture, client-server models, and messaging system paradigms. Experience with SQL databases including MySQL, PostgreSQL AWS RDS, and AWS RedShift. Experience with NoSQL databases including MongoDB, Cassandra, and DynamoDB. Experience with app containerization and orchestration tools including Docker, Kubernetes, and Kubeflow. Experience with machine learning libraries including TensorFlow, Keras, PyTorch, and ONNX. Experience with data science libraries including Numpy, SciPy, and Pandas. Experience with big data processing including Apache Spark, MapReduce, Hadoop, and Kafka. Experience with Cloud Services and APIs including AWS kinesis, and AWS Lambda. Employer will accept any amount of professional experience with the required skills.
Salary Range: $117,000/year to $234,000/year. Additional compensation includes annual or quarterly performance incentives. Additional compensation for certain positions may also include: Regional Pay Zone (RPZ) (based on location) and Stock equity incentives.
Benefits: At Walmart, we offer competitive pay as well as performance-based incentive awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty and voting. Other benefits include short-term and long-term disability, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For information about benefits and eligibility, see One.Walmart.com.
Wal-Mart is an Equal Opportunity Employer.
#LI-DNI #LI-DNP
Website: http://www.walmart.com/
Headquarter Location: Bentonville, Arkansas, United States
Employee Count: 10001+
Year Founded: 1962
IPO Status: Public
Last Funding Type: Post-IPO Debt
Industries: E-Commerce ⋅ Grocery ⋅ Retail ⋅ Retail Technology ⋅ Shopping