AI/ML Engineer

AI/ML Engineer (Contract)

Location: Florida (Required) - No Relocation

Duration: 6 Months (with possible extension)

Overview

We are seeking an experienced AI/ML Engineer to support the design, development, and deployment of scalable machine learning and generative AI solutions. This role will focus on building production-ready models, optimizing data pipelines, and collaborating with cross-functional teams to deliver high-impact AI initiatives.

Key Responsibilities

• Design, develop, and deploy machine learning models and AI solutions in production environments
• Build and optimize LLM-based applications (e.g., RAG pipelines, prompt engineering, agent workflows)
• Develop and maintain data pipelines to support model training, evaluation, and inference
• Implement MLOps best practices , including model versioning, monitoring, and automated retraining
• Collaborate with data engineers, product managers, and stakeholders to translate business requirements into technical solutions
• Evaluate model performance and continuously improve accuracy, scalability, and efficiency
• Ensure compliance with data governance, security, and responsible AI standards

Required Qualifications

• 6–7 years of experience in AI/ML engineering, data science, or related field
• Strong programming skills in Python (NumPy, Pandas, Scikit-learn)
• Hands-on experience with TensorFlow or PyTorch
• Experience building and deploying LLM-based solutions (RAG, embeddings, vector databases)
• Solid understanding of data engineering concepts (ETL, data pipelines, distributed processing)
• Experience with cloud platforms (AWS, Azure, or Google Cloud)
• Familiarity with MLOps tools (e.g., MLflow, Airflow, Docker, CI/CD pipelines)
• Strong problem-solving skills and ability to work independently in a fast-paced environment

Preferred Qualifications

• Experience with Databricks , Snowflake , or similar data platforms
• Knowledge of vector databases (e.g., Pinecone, FAISS, Weaviate)
• Exposure to agentic AI frameworks (e.g., LangChain, LlamaIndex)
• Experience working in regulated environments (finance, healthcare, or government)
• Familiarity with AI governance frameworks (e.g., NIST AI RMF, Responsible AI practices)