AI/ML Architect - Dallas
10 hours ago
Job description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Photon interactive UK limited, is seeking the following. Apply via Dice todayAI/ML Sr. Architect
Level:
Senior years' experience)
Industry:
Fintech
About The Role
We are seeking a highly experienced AI / ML Engineer/Architect to design, develop, and deploy machinelearning solutions that power key analytics and intelligent automation across our fintech ecosystem.
This role focuses on delivering productiongrade ML systems spanning classical ML, deep learning, and LLMbased applications while ensuring scalability, reliability, and regulatory compliance.
The engineer will own endtoend model development, from data preparation through deployment and monitoring, and will work closely with engineering, product, and data teams to implement impactful AI capabilities.
Key ResponsibilitiesBuild, train, and evaluate ML and deep learning models for classification, prediction, anomaly detection, and NLP use cases.
Implement scalable ML pipelines for data processing, feature engineering, and inference.
Develop and integrate LLMbased capabilities including embeddings, RAG workflows, and finetuned models.
Deploy models to production using containerized and cloudnative infrastructures (Docker, Kubernetes, Azure/AWS).
Implement MLOps practices including CI/CD integration, experiment tracking, model registries, and monitoring.
Ensure highquality data pipelines and automate preprocessing for structured and unstructured data.
Apply model explainability (SHAP, LIME) and Responsible AI principles to ensure transparency and safe use.
Required Qualifications
Deep handson experience building and deploying ML models (supervised, unsupervised, deep learning, NLP).
Strong Python skills (NumPy, Pandas, Scikitlearn, PyTorch or TensorFlow).
Experience with SQL and dataengineering workflows (Spark or Airflow).
Practical experience with LLMs, vector databases, embeddings, and RAG systems.
Familiarity with production ML deployment using Docker, Kubernetes, CI/CD pipelines, and GPU acceleration.
Experience with cloud AI tooling (Azure, AWS, or Google Cloud Platform) and scalable inference pipelines.
Strong understanding of model monitoring, drift detection, and retraining strategies.
Ability to create clear model explanations and apply interpretability tools.
Nice to Have
Experience in fintech or other regulated industries with compliance requirements (SOC 2, PCI-DSS, FedRAMP)
Background with LangChain, multiagent frameworks, or advanced vector search architectures.
Experience implementing governance, safety guardrails, or Responsible AI frameworks.
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