Machine Learning Architect - Contract to Hire

Job Title: ML Architect Contractor

Location: Remote (United States)
Duration: 4 Months (Contract to Hire)
Start Date: Immediate

Key Responsibilities:

• Architect and design a scalable AI/automation solution to streamline manual processes within the companys internal operations.
• Lead the endtoend solution design including data pipelines model lifecycle management and system integration ensuring the architecture is optimized for performance scalability and maintainability.
• Leverage advanced techniques such as constrained optimization to improve resource allocation and replace manual processes with an intelligent automation system.
• Collaborate closely with SMEs and business stakeholders to understand operational requirements and design an AI/ML system that reflects their expertise while ensuring it integrates seamlessly into broader enterprise systems.
• Define the architectural standards and best practices for the deployment of machine learning models working closely with ML Engineers and Data Engineers to ensure alignment with business and technical objectives.
• Establish frameworks for automated resource allocation data processing and model orchestration optimizing operational efficiency and service quality.

Required Qualifications:

• Proven experience as an ML Architect with a track record of designing and implementing largescale machine learning and AI systems in production environments.
• Deep expertise in machine learning algorithms AI models and frameworks (e.g. TensorFlow PyTorch) with an ability to guide the design and implementation of complex systems.
• Extensive experience in architecting data pipelines and working with large datasets with strong proficiency in SQL and cloudbased data warehouse solutions (e.g. Azure preferred).
• Expertise in architecting AIdriven automation solutions with a focus on resource allocation scheduling optimization and efficient system orchestration.
• Handson experience with cloud platforms (preferably Azure) for deploying machine learning models managing data storage and building data infrastructures.
• Strong programming skills in Python with additional expertise in languages like Java Scala or C for designing productionlevel architectures.
• Experience in architecting RESTful APIs and microservices for integrating machine learning models into enterprise systems.
• Advanced knowledge of algorithms data structures and distributed systems for building highly efficient and scalable ML solutions.
• Experience with DevOps practices including Git CI/CD pipelines containerization (Docker Kubernetes) and model lifecycle management.
• Excellent communication and leadership skills with the ability to work crossfunctionally with SMEs data engineers ML engineers and other stakeholders.