Job Description

Client Name: TekSystems

End Client Name: Walmart

Job Title: Machine Learning Engineer

Location: Candidates have to sit in Sunnyvale, CA, or Bentonville, AR

Work Type: Hybrid

Job Type: Contract 4- 6+ Months

Rate: $55/hour on W2

Team: Data Ventures, Customer Voice Product Area

LinkedIn is a MUST

Notes:

We need a Walmart former with machine learning/data science experience.

Job Description:

Walmart is seeking a Machine Learning Engineer (MLE) to join our Data Ventures team, focusing on the Customer Voice product area. This role involves deploying, scaling, and integrating machine learning models into our products. The contract is for 4-6 months, with the possibility of extension based on project needs.

Roles and Responsibilities:

• Deployment and Scaling: Take built models and put them into production, building out production pipelines.
• Integration: Integrate ML models into products, creating inference layers.
• Infrastructure: Utilize Docker/Kubernetes for scaling systems and batch pipelines.
• MLOps: Implement ML flow or similar tools for continuous model monitoring and lifecycle management.
• API Development: Deploy applications with APIs around them using Flask or FastAPI.
• Platform Utilization: Work with Walmart's homegrown platform, similar to SageMaker/Vertex AI, for model scaling.

Required Skills:

• Experience: Extensive experience in building ML pipelines, ML architecture design, and taking ML systems to production.
• Technical Skills: Proficiency in Docker/Kubernetes, ML flow, Flask/FastAPI, and scaling models.
• Knowledge: Familiarity with Walmart's homegrown platform and cloud layers (Google/MS).
• Interview Process: Screening by Vinay Artham and Anindya Dey, followed by coding and systems design interviews with team MLEs.

Qualifications:

• Engineering Mindset: Exposure to software engineering principles, Agile methodologies, CICD, and distributed systems.
• Technical Proficiency: Strong knowledge of Machine Learning, MLOps, MLflow, Kubeflow, Python/R, Pytorch, SQL, Big Data, GCP, Shell scripting.
• Infrastructure Scaling: Experience in scaling infrastructure for high-throughput data-intensive applications using Scala/PySpark/GPU.
• Web Services Integration: Worked on integrating ML models with web services using FastAPI or Flask.

Immediate Need:

This position is urgently needed to support ongoing projects and ensure timely delivery of machine learning solutions.

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