Artificial Intelligence Engineer

AI/ML Development Specialist

Pay Range: $59.35hr - $77.03hr

Requirement/Must Have:

• 8–12 years of relevant experience in AI/ML development or 12–15 years of related work experience without a degree.
• Proficiency in Python and AI frameworks (TensorFlow, PyTorch).
• Experience with cloud platforms (Azure AI stack, Databricks).
• Knowledge of MLOps, containerization (Docker/Kubernetes), and CI/CD pipelines.
• Understanding of engineering and construction workflows is a plus.
• Strong problem-solving, communication, and collaboration skills.

Responsibilities:

• Design, build, and implement AI/ML models for predictive analytics, generative design, and automation.
• Convert prototypes into production-ready applications using frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Collaborate with data engineers to develop robust data pipelines and architectures.
• Apply ETL techniques and big-data tools to cleanse, organize, and transform data for AI models.
• Deploy AI models on cloud platforms (Azure AI/ML, Databricks) and integrate with the organization’s digital ecosystem.
• Implement MLOps practices for lifecycle management, monitoring, and continuous improvement.
• Work with cross-functional teams (engineering, IT, project controls) to align AI solutions with business objectives.
• Communicate complex AI concepts to non-technical stakeholders.
• Ensure AI solutions adhere to the organization’s security, ethics, and compliance standards.
• Maintain documentation for models, processes, and decision-making.
• Stay current with emerging AI technologies (e.g., agentic AI, multimodal systems).
• Contribute to the organization’s AI Center of Excellence initiatives and innovation programs.
• Work under minimal supervision with latitude for independent judgment.
• Handle issues of diverse scope within defined parameters.
• Act as a technical lead on small projects or initiatives.

Nice to Have:

• Familiarity with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Experience with knowledge graphs, agent-based AI systems, and predictive analytics.

Skills:

• Python.
• TensorFlow.
• PyTorch.
• Azure AI stack.
• Databricks.
• MLOps.
• Docker.
• Kubernetes.
• CI/CD pipelines.
• Generative AI.
• Large Language Models (LLMs).
• Retrieval-Augmented Generation (RAG).
• Knowledge graphs.
• Agent-based AI systems.
• Predictive analytics.

Qualification And Education:

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
• Master’s degree preferred.