AI/ML Engineer

We are seeking an experienced AI/ML Engineer for a contract position with our client, based in Santa Clara, CA. In this role, you will design, develop, and scale machine learning models and workloads on modern cloud ML platforms. You will collaborate closely with Product and Engineering teams to support the ML portion of the DT GoToMarket strategy, ensuring all deployment processes are automated, optimized, and compliant with enterprise architecture policies. Core Responsibilities

• Model Development: Design and develop scalable ML models and workloads on cloud ML platforms such as Azure ML Studio, AWS, or Google Cloud Platform.

• Pipeline Orchestration: Facilitate and participate in the preparation of ML models and their scoring processes.

• API & Microservices: Develop and support the ML portion of the DT GoToMarket strategy to maximize the distribution of ML predictions and recommendations by publishing microservices and APIs.

• MLOps Automation: Incorporate workflows into ML Model Engineering processes to automate, monitor, and produce alerts.

• Optimization: Implement performance tuning and model optimization across systems.

• Cross-Functional Collaboration: Partner with Product and Engineering team members to follow documented architecture, design, and deployment processes to ensure full compliance with internal policies.

• Innovation: Stay current on emerging ML platforms and technologies, recommending solutions that enhance current implementations.

• Education: Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field.
• Experience: 5+ years of professional experience working as an AI/ML Engineer.
• Cloud & Data Platforms: Hands-on experience with Databricks (including Unity Catalog) and cloud ML platforms like Azure ML Studio, AWS, or Google Cloud Platform.
• Core Engineering: Proven experience building and scaling end-to-end ML systems, ETL/ELT pipelines, and data workflows using Python, NumPy, Pandas, and SQL.
• API Development: Strong background building scalable APIs and microservices using FastAPI alongside Snowflake or equivalent data warehouse technologies.
• Foundational Knowledge: Solid foundation in probability, statistics, and machine learning principles.
• Soft Skills: Excellent written, presentation, and verbal communication skills; ability to work independently with minimal direction or collaborate effectively within a team environment.