Design, develop, and deploy AI/ML models to enhance our platform’s capabilities
Work with Agents, Prompt Engineering, Swarms, Transformers, Retrieval-Augmented Generation (RAG) systems, and other advanced AI concepts
Leverage AWS SageMaker, Databricks (Lakehouse), and ETL pipelines to build, train, and deploy robust end-to-end machine learning pipelines
Implement NLP models for processing both structured and unstructured data
Optimize and fine-tune machine learning models to achieve high accuracy, low latency, and efficient resource utilization
Stay current with leading AI frameworks and communities
Deploy AI models within cloud-based environments
Ensure seamless integration of AI solutions with our existing applications
Ensure AI applications adhere to HIPAA and SOC 2 compliance requirements
Collaborate with cross-functional teams to continuously improve AI development and deployment processes

Requirements

Proven experience as an AI Engineer or Machine Learning Engineer
Able to work efficiently with Python and popular AI frameworks like LangGraph/LangChain
Proficiency in TensorFlow, PyTorch, or similar ML frameworks
Experience with AWS SageMaker, Lambda, Kubernetes (EKS), and CI/CD pipelines
Strong understanding of NLP, deep learning, and model optimization techniques
Experience supporting development teams using React, .NET, SQL Server, and Databricks
Knowledge of version control systems like GitHub and CI/CD automation
Strong problem-solving skills and ability to work in a fast-paced environment

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI/ML modelsNLPPythonTensorFlowPyTorchmodel optimizationETL pipelinesdeep learningAWS SageMakerKubernetes

Soft Skills

problem-solvingcollaborationadaptability