Principal AI/ML Engineer

About us:

Intuitive.AI is one of the fastest-growing (INC 5000, CRN) Cloud & SDx solution and services companies supporting enterprise customers on a global scale. Intuitive is an "Engineering Company" delivering measurable value and key business outcomes.

Intuitive Superpowers:

• DataOps & AI/ML

• Cloud Native, AppSecOps, DevSecOps

• Cloud Migration & Transformation

• Cloud FinOps

• Cybersecurity (App/Data/Infra) & GRC

• SDx & Digital Workspace

We are proud to partner with some of the world's leading enterprises and serve 200+ customers across different industry verticals. We have achieved many milestones along the way, including being recognized as a top-10 fast-growth 150 IT company in the Americas by CRN in 2022 and being named one of America's fastest-growing private companies by INC 5000 in 2022. That’s not all! Even CIO Review awarded us as the Most Promising Cloud Migration Company and Artificial Intelligence Solutions Provider in 2022.

About the job:

Title – Principal AI/ML Engineer

Start date: Immediate

Position Type: Contract

Location: Remote across USA or Canada (Candidate should be open to travel to Houston, TX for 3-4 days every alternate week, all expenses paid)

Hiring Manager Notes:

• This AI/ML role has to be someone at Principal level, who can operate independently with authority and has done this kind of work multiple times.
• Ideal candidate - Sagemaker + time series forecasting. Proficiency in time-series forecasting (LSTM, Prophet, XGBoost, ensemble methods)

Role Summary

As a Senior Consultant (L6), you are an experienced individual contributor who independently drives one or more AI/ML workstreams end-to-end. You own delivery outcomes for your assigned workstream, make key technical decisions, and interface directly with customer technical leads and stakeholders. You mentor L4 (Associate) and L5 (Staff) consultants on the team, providing technical guidance and reviewing their deliverables. You bring deep expertise in ML Ops and time-series forecasting to architect and implement scalable solutions on AWS.

Key Responsibilities

• Design, develop, and deploy machine learning models for latent capacity prediction across pipeline systems (weather, gas turbine HP, compressor flow, line pack, equipment performance)
• Build and maintain ML Ops infrastructure on AWS SageMaker including model registry, versioning, CI/CD pipelines, and multi-environment endpoints (Dev, Pre-Prod, Prod)
• Conduct exploratory data analysis and feature engineering for time-series forecasting of pipeline operational data (SCADA, performance curves, hydraulic models)
• Develop ensemble model strategies combining LSTM, Prophet, and XGBoost for improved prediction accuracy of latent capacity
• Build automated model deployment workflows, training/evaluation pipelines, and retraining frameworks
• Design real-time and batch inference architectures with API Gateway integration and model monitoring
• Collaborate with data engineering team on feature stores and data pipeline integration from Bronze/Silver/Gold data lakehouse layers
• Support hydraulic model integration with Engineering NextGen software for automated scenario generation
• Independently own delivery of assigned ML workstream, driving technical decisions and ensuring quality
• Mentor L4/L5 team members on ML best practices, code reviews, and architectural patterns
• Interface directly with customer technical leads to align on requirements, review progress, and resolve technical blockers

Required Skills & Qualifications

• Strong experience with AWS SageMaker, including SageMaker Pipelines, Model Registry, and Feature Store
• Proficiency in time-series forecasting (LSTM, Prophet, XGBoost, ensemble methods)
• Experience with ML Ops practices: CI/CD for ML, model monitoring, automated retraining
• Python (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch)
• Experience with real-time and batch inference architectures
• Knowledge of data lakehouse architectures (S3, Glue, Redshift)
• Understanding of industrial/operational data (SCADA, IoT sensors) is a plus
• Experience in Energy & Utilities domain preferred
• Demonstrated ability to independently lead technical workstreams and make architectural decisions
• Experience mentoring junior engineers or consultants
• Strong communication skills for customer-facing interactions