AI/ML Engineer

AI/ML Engineer (Contract)Location: Florida (Required) - No Relocation Duration: 6 Months (with possible extension)OverviewWe 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 ResponsibilitiesDesign, develop, and deploy machine learning models and AI solutions in production environmentsBuild and optimize LLM-based applications (e.g., RAG pipelines, prompt engineering, agent workflows)Develop and maintain data pipelines to support model training, evaluation, and inferenceImplement MLOps best practices, including model versioning, monitoring, and automated retrainingCollaborate with data engineers, product managers, and stakeholders to translate business requirements into technical solutionsEvaluate model performance and continuously improve accuracy, scalability, and efficiencyEnsure compliance with data governance, security, and responsible AI standardsRequired Qualifications6–7 years of experience in AI/ML engineering, data science, or related fieldStrong programming skills in Python (NumPy, Pandas, Scikit-learn)Hands-on experience with TensorFlow or PyTorchExperience 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 environmentPreferred QualificationsExperience with Databricks, Snowflake, or similar data platformsKnowledge 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)