On-Site AI Data Engineer: ML Pipelines & MLOps

Tech Junction Ltd; Arizona; On-site; USD 120,000 - 180,000; Full time

Job summary

Tech Junction Ltd is seeking an experienced AI Data Engineer to design and operate scalable data pipelines, feature stores, and MLOps tooling across cloud platforms. This on-site C2C contract requires strong Python/SQL expertise and hands-on ML data workflows.

You will work with data scientists to productionize models, implement data governance, and optimize ingestion with Spark, Ray, or Dask on AWS/Azure/GCP. Local onsite presence in Scottsdale, AZ is required.

Qualifications

• Required: Bachelor's or Master's in CS/AI/Data Eng or related field.
• 5+ years in software/data engineering and AI/ML data pipelines.
• Strong Python and SQL for data manipulation.
• Experience with cloud data platforms (AWS/Azure/GCP) and Spark.

Responsibilities

• Design scalable data pipelines and ingestion frameworks for AI/ML workloads.
• Develop and manage feature stores and data preprocessing workflows.
• Collaborate with data scientists to productionize models.
• Implement MLOps for data validation, retraining triggers, and monitoring.
• Use Spark, Ray, or Dask for large-scale data processing in cloud environments.
• Ensure data quality, lineage tracking, and governance across AI data stores.
• Troubleshoot ingestion bottlenecks and pipeline failures in production.
• Create documentation and runbooks for data architectures and pipelines.

Skills

Python

SQL

Cloud platforms

Spark

MLOps

Data pipelines

Feature stores

Distributed systems

Education

Bachelor's or Master's degree in Computer Science, AI, Data Engineering

Tools

Docker

Kubernetes

LangChain

LlamaIndex

Pinecone

Milvus

Job description

Tech Junction Ltd is seeking an experienced AI Data Engineer to design and operate scalable data pipelines, feature stores, and MLOps tooling across cloud platforms. This on-site C2C contract requires strong Python/SQL expertise and hands-on ML data workflows.

You will work with data scientists to productionize models, implement data governance, and optimize ingestion with Spark, Ray, or Dask on AWS/Azure/GCP. Local onsite presence in Scottsdale, AZ is required.