AI/ML Lead Engineer

Role: AI/ML Lead Engineer

Location: Orlando, FL

Duration: 6+ months

Job Summary

We are looking for an experienced AI/ML Lead Engineer to lead the design, development, and deployment of scalable machine learning and artificial intelligence solutions. The ideal candidate will have strong hands-on experience in machine learning, deep learning, generative AI, MLOps, and cloud technologies, along with the ability to lead technical teams and drive AI initiatives from concept to production.

Key Responsibilities

• Lead the architecture, development, and implementation of end-to-end AI/ML solutions.
• Design and develop machine learning models for classification, prediction, recommendation, NLP, computer vision, or other business use cases.
• Lead the development and integration of Generative AI, LLM, RAG, and agent-based solutions where applicable.
• Evaluate and select appropriate ML algorithms, frameworks, tools, and technologies.
• Develop scalable ML pipelines for data preparation, model training, validation, deployment, and monitoring.
• Establish and implement MLOps best practices for model lifecycle management, CI/CD, automation, and production monitoring.
• Work with cloud platforms such as AWS, Azure, or Google Cloud Platform to build and deploy AI/ML solutions.
• Lead technical discussions, architecture reviews, and proof-of-concept initiatives.
• Mentor and guide junior and senior engineers, promoting engineering best practices.
• Collaborate with data engineers, software engineers, product managers, and business stakeholders to translate business requirements into technical solutions.
• Monitor model performance, reliability, scalability, and cost in production environments.

Required Qualifications

• Bachelor s or master s degree in computer science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field.
• 8+ years of experience in software engineering, machine learning, data science, or related areas, with significant hands-on AI/ML experience.
• Strong programming skills in Python and experience with software engineering best practices.
• Strong knowledge of machine learning and deep learning concepts, algorithms, and statistical techniques.
• Hands-on experience with frameworks such as PyTorch, TensorFlow, Scikit-learn, or similar.
• Experience building and deploying production-grade