Lead AI/ML Engineer
New York, New York, United States of America
Contract
1 day ago
$70 USD
Key skills
PythonSQLNoSQLAIMachine LearningMLDeep LearningAgenticMLOpsAWSAzureCommunicationCollaborationPresentation Skills
About this role
Senior AI/ML Engineer
Contract
Remote
The Senior AI/ML Engineer will architect and build agentic AI frameworks for web and mobile platforms, with a focus on MCP development and orchestration logging. This role requires excellent presentation and communication skills, as the engineer will represent AI-led automation delivery and champion an AI-first approach.
Key Responsibilities:
Qualifications & Skills:
Contract
Remote
The Senior AI/ML Engineer will architect and build agentic AI frameworks for web and mobile platforms, with a focus on MCP development and orchestration logging. This role requires excellent presentation and communication skills, as the engineer will represent AI-led automation delivery and champion an AI-first approach.
Key Responsibilities:
- Data Preparation & Governance: Gather, clean, and prepare structured and unstructured data, apply data governance standards, and manage large datasets using SQL, NoSQL, and distributed technologies.
- Model Development: Design, train, and validate machine learning models using AutoML, deep learning, and reinforcement learning, optimizing for scalability and performance through feature engineering and rigorous evaluation.
- AI Architecture & Deployment: Support AI/ML architectural design and deploy models into production using APIs, microservices, and containerized environments.
- MLOps & Cloud Platforms: Implement MLOps practices and leverage cloud services such as AWS and Azure for scalable, reliable, and secure AI deployments.
- Agentic Frameworks & Orchestration: Build and evolve agentic AI frameworks, focusing on MCP development, orchestration workflows, and comprehensive logging and observability.
- Cross-Functional Collaboration: Collaborate closely with data engineers, analysts, and business stakeholders to deliver AI-driven automation and decisioning capabilities.
- Documentation & Knowledge Sharing: Maintain thorough documentation of workflows, architectures, and design decisions to support knowledge sharing and long-term maintainability.
Qualifications & Skills:
- Proven experience building and deploying AI/ML systems in production environments.
- Strong experience with Python and modern ML frameworks, including deep learning and AutoML toolchains.
- Experience working with SQL, NoSQL, and distributed data platforms.
- Strong understanding of MLOps, model lifecycle management, and cloud platforms such as AWS and Azure.
- Experience designing and deploying microservices and containerized applications for ML workloads.
- Excellent communication and presentation skills with the ability to represent AI-led solutions to technical and business stakeholders.