JPS Tech Solutions
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
#J-18808-Ljbffr
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
#J-18808-Ljbffr