AI / ML Engineer

Role Overview

The AI/ML Engineer is the intelligence core of the AI Ops platform. You will design, build, train, and deploy the predictive models that drive autonomous infrastructure management - including failure forecasting, anomaly detection, capacity modelling, and root cause analysis. Beyond model development, you will own the MLOps pipeline, the agentic decision engine, the continuous learning loop, and the model registry - ensuring the platform's AI capabilities improve with every resolved incident and learned pattern.

Key Responsibilities

• Design and train the Failure Forecast model targeting 94%+ accuracy at a 6-hour prediction horizon
• Build the Anomaly Detection model targeting 97%+ precision for real-time infrastructure signal classification
• Develop the Capacity Model for 24-hour resource demand forecasting at 91%+ accuracy
• Build and tune the Root Cause AI model targeting 89%+ average confidence on incident attribution
• Design and implement the agentic decision engine - the Detect Predict Decide Heal loop that drives auto-remediation
• Build and maintain the MLOps pipeline: data ingestion, feature engineering, model training, validation, and deployment
• Implement the Continuous Learning module: automated retraining triggers, knowledge base indexing, and runbook auto-generation
• Develop the model registry API layer exposing real-time accuracy scores and model metadata to the platform
• Integrate AI outputs with the Incident Control backend for root cause enrichment and resolution recommendation
• Design the Digital Twin data model for real-time infrastructure state representation
• Monitor model performance in production and implement drift detection and alerting
• Collaborate with Backend Engineers on inference API design for sub-100ms prediction latency

Expectations

• Achieve and maintain model accuracy targets: 94% (Failure Forecast), 97% (Anomaly), 91% (Capacity), 89% (Root Cause)
• Deliver a fully operational agentic loop processing 47,600+ AI decisions per day from go-live
• Ensure model inference endpoints respond within 100ms on p95 for all production predictions
• Keep human escalation rate below 2.5% through high-confidence autonomous decision-making
• Implement a continuous learning pipeline that indexes and learns from every resolved incident
• Produce explainable AI outputs with confidence scores on all predictions surfaced in the UI
• Document all model architectures, training datasets, evaluation metrics, and retraining schedules

Technical Skills

• Deep expertise in supervised and unsupervised machine learning: anomaly detection, classification, regression, time-series forecasting
• Proficiency in Python ML stack: scikit-learn, XGBoost, LightGBM, PyTorch or TensorFlow
• Time-series modelling: LSTM, Transformer-based models, Prophet, or ARIMA for infrastructure metric forecasting
• MLOps platform experience: MLflow, Kubeflow, Weights & Biases, or equivalent for experiment tracking and model management
• Feature engineering from infrastructure telemetry data: metrics, logs, traces, and events
• Experience building and deploying inference APIs at low-latency production scale
• Knowledge of LLM integration for runbook generation and knowledge base indexing
• GPU compute management for model training on cloud platforms (AWS SageMaker, Azure ML, or GCP Vertex AI)
• Familiarity with reinforcement learning or agentic AI patterns for autonomous remediation design
• Statistical proficiency: hypothesis testing, confidence intervals, distribution analysis

Functional & Soft Skills

• Ability to translate complex model behaviour into clear, confidence-scored outputs for operations teams
• Strong experimental mindset - rigorous about evaluation metrics and avoiding overfitting
• Collaborative engineering partner to Backend and DevOps engineers on pipeline integration
• Clear documentation practices for model cards, training pipelines

About Accenture

Accenture is a leading global professional services company that helps the world's leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world's leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Equal Employment Opportunity

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. Bring your incredible skills and join our global team of innovators. We come together from different backgrounds across the world and work with the latest technologies to create value and growth for our clients. With us, you'll continue to learn and grow so you can advance in your career. Your personal dreams and ambitions are just as important to us; that's why we offer support any way we can—when you thrive, we all thrive.