Machine Learning Contract Jobs in Phoenix, AZ (NOW HIRING)

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Job Description: Role Overview

We are seeking a Software Engineer with hands-on experience building and operating AI and data pipelines in a modern lakehouse environment. This role combines applied machine learning, data engineering, and analytics engineering, with strong emphasis on dbt Core, SQL, Databricks, and AWS.

You will own AI workflows end-to-end — from governed feature modeling through training, deployment, monitoring, and performance optimization — in a production environment.

This is a delivery-oriented role. You are expected to design solutions, write production-quality code, and improve platform reliability.

Core Responsibilities AI & Machine Learning Engineering

• Design and implement machine learning training and batch inference pipelines on Databricks using Spark and MLflow.
• Develop and deploy ML models (classification, regression, forecasting, or NLP-based workloads).
• Implement LLM-enabled solutions, including embedding pipelines, semantic search systems, and retrieval-augmented generation (RAG) workflows.
• Proven experience designing feature engineering pipelines that ensure consistency between offline training datasets and production inference workflows.
• Manage model lifecycle, including versioning, experiment tracking, evaluation, and deployment.
• Implement monitoring for model drift, data drift, and prediction stability.
• Diagnose and resolve production failures across training and inference pipelines.

dbt Core & Data Contract Ownership

• Architect and maintain dbt Core projects that serve as the transformation and contract layer for AI workloads.
• Design incremental models, snapshots, and historical datasets to support reproducible training.
• Enforce data contracts and schema stability for downstream ML pipelines.
• Implement automated testing, freshness validation, and CI pipelines for dbt projects.
• Collaborate with data engineers to ensure AI systems consume governed, high-quality datasets.

Databricks & Lakehouse Engineering

• Design and optimize bronze, silver, and gold pipelines using Delta Lake.
• Develop scalable Spark workloads for large datasets.
• Manage governance, access control, and lineage using Unity Catalog.
• Optimize compute performance and cost efficiency for AI workloads.
• Contribute to architectural decisions across data and AI infrastructure.

AWS Cloud Engineering

• Build and operate AI workflows in an AWS-based lakehouse environment.
• Work with Amazon S3, IAM roles and policies, and related AWS services supporting data pipelines.
• Design secure and scalable data access patterns across environments.
• Support deployment of models using containerized or managed services when required.
• Monitor and optimize cloud resource utilization.

Engineering Excellence & Reliability

• Implement CI/CD pipelines for dbt projects, ML code, and infrastructure.
• Write maintainable Python and SQL with appropriate documentation and testing.
• Conduct code reviews and provide guidance to junior engineers.
• Ensure production systems meet reliability, auditability, and governance standards.
• Partner with analytics and business stakeholders to translate requirements into scalable AI solutions.

Requirements/Qualifications: Required Qualifications

• 0-3 years of total professional experience.
• Professional experience in AI, ML, data engineering, or analytics engineering roles.
• Strong hands-on experience with dbt Core in production environments.
• Advanced SQL skills with performance tuning experience.
• Proven experience with Databricks (Spark, Delta Lake, MLflow).
• Experience building AI/ML pipelines on AWS.
• Proficiency in Python for ML and data processing workflows.
• Experience managing AI workloads end-to-end, including deployment and monitoring.

Preferred Qualifications

• Experience working with centralized, versioned feature datasets.
• Exposure to vector databases or LLM-based systems.
• Experience implementing model monitoring and drift detection frameworks.
• Experience supporting near-real-time AI systems.

Travel Time:

0% - 25%

Physical Attributes:

Hearing, Seeing, Talking, Works Alone, Works Around Others

Physical Requirements:

80% sitting, 10% standing, 10% walking, 100% inside.

Microchip Technology Inc is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.

For more information on applicable equal employment regulations, please refer to the Know Your Rights: Workplace Discrimination is Illegal Poster.

To all recruitment agencies: Microchip Technology Inc. does not accept unsolicited agency resumes. Please do not forward resumes to our recruiting team or other Microchip employees. Microchip is not responsible for any fees related to unsolicited resumes.