AI / ML Solutions Architect

The AI / ML Solutions Architect will be instrumental in designing and implementing end-to-end artificial intelligence and machine learning solutions for a key Randstad client in the DC area. This role requires an expert-level blend of advanced AI / ML model development (including Generative AI / LLMs, deep learning, and traditional ML), modern software engineering practices, and robust MLOps principles. The Architect will drive platform adoption using Databricks , ensure models are securely deployed via cloud platforms (AWS / Azure) using Docker / Kubernetes and FastAPI , and serve as a technical leader and mentor to junior team members, ultimately enabling self-service capabilities and accelerating the business adoption of scalable AI / ML solutions.

Responsibilities

• Architect and Develop AI / ML Solutions : Design, implement, and deploy advanced supervised and unsupervised models (regression, classification, clustering, time-series forecasting, boosting methods) and complex neural networks (CNNs, RNNs, LSTMs).
• Lead Generative AI Initiatives : Develop and integrate solutions powered by LLMs and open-source foundation models, applying expertise in prompt engineering, fine-tuning techniques ( LoRA, PEFT ), and model optimization for performance, latency, and cost.
• Implement MLOps and Deployment Pipelines : Manage the full model lifecycle and deployment strategy, including model serialization (Pickle, Joblib, ONNX), containerization with Docker and Kubernetes , and building secure, scalable endpoints using FastAPI and serverless functions.
• Champion Platform Enablement : Drive adoption and utilization of the Databricks platform to accelerate use case development, promote model automation, facilitate AutoML, and create reusable template-based solutions.
• Adhere to Software Engineering Excellence : Write highly efficient, maintainable Python code (advanced Python skills required), utilizing tools like JupyterLab and VSCode, and enforce Git version control and best practices for testing and quality assurance.
• Develop User-Facing AI Applications : Build front-end tools and prototypes using Streamlit alongside standard front-end technologies (HTML / CSS / JavaScript) to demonstrate AI capabilities to business users.
• Provide Technical Leadership & Mentorship : Collaborate effectively with cross-functional teams, mentor junior engineers and data scientists, and establish governance standards for data quality, solution accessibility, and business adoption of AI / ML practices.

Qualifications

Required Skills :

Basic Qualification :

Additional Skills :

Background Check : No

Drug Screen : No