Hybrid Full-Stack AI Engineer (Python/Java/Angular)

BURGEON IT SERVICES LLC; New York (NY); Hybrid; USD 68,000 - 97,000; Full time

Job summary

BURGEON IT SERVICES LLC is seeking an experienced AI/ML Engineer to design and develop advanced AI/ML solutions for financial services clients. The role focuses on end-to-end pipeline development, model deployment, and ongoing optimization using Python and leading ML libraries.

Ideal candidates will have 5+ years in AI/ML, experience with generative AI, and familiarity with data ecosystems, across Azure or AWS platforms. Hybrid work arrangement with 2–4 days in the office is offered.

Qualifications

• Minimum 5 years of relevant AI/ML experience.
• Strong programming in Python with ML libraries (Scikit-learn, TensorFlow, PyTorch, Hugging Face).
• Experience building AI/ML pipelines, data lakes/warehouses, ETL, and cloud deployment.
• Experience with MLOps, CI/CD, model governance, monitoring, and containers (Docker/Kubernetes).
• Familiarity with Azure or AWS AI services (Azure ML, SageMaker).

Responsibilities

• Design and develop AI/ML solutions for business challenges.
• Build Generative AI applications using LLMs, prompt engineering, fine-tuning, RAG, and AI agent frameworks.
• Develop end-to-end AI pipelines: ingestion, preprocessing, training, deployment, monitoring.
• Deploy AI models via APIs and microservices integrated with enterprise systems.
• Collaborate with stakeholders to translate requirements into scalable AI solutions.

Skills

AI

Python

Tools

TensorFlow

PyTorch

Scikit-learn

Hugging Face

SpaCy

NLTK

Spark

Databricks

Microsoft Fabric

Job description

BURGEON IT SERVICES LLC is seeking an experienced AI/ML Engineer to design and develop advanced AI/ML solutions for financial services clients. The role focuses on end-to-end pipeline development, model deployment, and ongoing optimization using Python and leading ML libraries.

Ideal candidates will have 5+ years in AI/ML, experience with generative AI, and familiarity with data ecosystems, across Azure or AWS platforms. Hybrid work arrangement with 2–4 days in the office is offered.