Senior Python AI/ML Engineer

Kforce has a client that is seeking a Senior Python AI/ML Engineer in Coppell, TX. Duties Include:

• Design, develop, test, and deploy machine learning and Generative AI solutions for enterprise use cases
• Build and optimize end-to-end AI/ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
• Develop Retrieval-Augmented Generation (RAG) solutions and integrate large language models into enterprise applications
• Perform model evaluation, performance tuning, prompt optimization, and ongoing solution improvement

• Develop scalable backend services, microservices, and RESTful APIs using Python
• Create reusable frameworks, libraries, and integration components
• Write clean, secure, maintainable, and production-quality code using modern engineering standards
• Implement unit, integration, regression, and performance testing

• Design data pipelines for structured and unstructured data processing
• Integrate AI/ML models with internal and external enterprise systems through APIs and event-driven patterns
• Work with cloud data platforms such as Snowflake, Databricks, or comparable technologies
• Collaborate with data engineering teams to support data quality, lineage, governance, and security requirements

• Build and maintain CI/CD pipelines for application, infrastructure, and model deployments
• Automate build, test, code-quality checks, security scanning, deployment, and release processes
• Implement MLOps practices including model versioning, experiment tracking, monitoring, drift detection, and retraining
• Use tools such as Jenkins, GitHub Actions, Azure DevOps, Bitbucket Pipelines, Docker, and Kubernetes

• Design and deploy cloud-native solutions using AWS, Azure, or GCP
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent professional experience
• 8-12 years of software engineering experience, including substantial hands-on Python development
• Production experience designing, deploying, and supporting AI/ML solutions
• Strong understanding of machine learning algorithms, model lifecycle management, and MLOps principles
• Experience developing RESTful APIs, microservices, and system integrations
• Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP
• Demonstrated experience creating and maintaining CI/CD pipelines and applying DevOps practices
• Experience with Docker, Kubernetes, SQL, Git, automated testing, debugging, and production support
• Strong analytical, communication, stakeholder-management, and problem-solving skills

• Experience with Generative AI, large language models, prompt engineering, RAG, embeddings, and vector databases
• Hands-on knowledge of frameworks such as LangChain, LlamaIndex, Semantic Kernel, scikit-learn, TensorFlow, or PyTorch
• Experience with Snowflake, Databricks, Spark, PySpark, MLflow, Kubeflow, or Airflow
• Experience building cloud-native applications using FastAPI or Flask
• Experience in financial services, audit, risk, compliance, or another highly regulated enterprise environment
• Knowledge of responsible AI, model governance, data privacy, security, and enterprise control requirements