Job Description

Join to apply for the AI/ML Solutions Architect role at JPS Tech Solutions

Job Category: Architect

Job Type: Onsite

Job Location: District of Columbia Washington

Compensation: Depends on Experience

W2: W2-Contract Only; Kindly note that applications on a C2C basis will not be considered for this role.

Job Description

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

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