AI Engineer

ACCENTURE PTE LTD; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Accenture is seeking an AI Engineer (Consultant) in Singapore to design and build AI-powered applications, ML models, and data pipelines for production systems. You will translate business requirements into technical specifications and work within delivery teams under senior guidance. Travel may be required.

The role emphasizes hands-on coding, model serving, and continuous learning in a fast-evolving AI landscape.

Qualifications

• Hands-on engineer building AI pipelines, AI-powered apps, and data-driven solutions.

Responsibilities

• AI Application Development: design and build AI-powered applications, APIs, and frontend interfaces to production standards.
• Machine Learning Development: build, train, deploy ML models using PyTorch, TensorFlow, scikit-learn, and LightGBM; select models and tune hyperparameters.
• Data Engineering & Pipelines: design and implement data pipelines for ingestion, transformation, and enrichment at scale.
• Model & System Integration: integrate models into production with robust error handling and monitoring.
• MLOps & Production Excellence: maintain CI/CD for model code, training scripts, and infra with testing and deployment strategies.
• Continuous Learning: stay updated with ML frameworks and contribute to knowledge sharing.

Skills

Python programming

ML engineering

Data pipelines

Tools

PyTorch

TensorFlow

scikit-learn

LightGBM

Job description

About Accenture Data & AI

The beginning of a new Data & AI decade that will reshape work and society is underway. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimise and reinvent their businesses with data and AI - backed by a $3 billion investment and a commitment to industry-defining work.

With over 45,000 professionals dedicated to Data & AI, Accenture's Data & AI organisation brings together Experienced Innovation, Strategic Investment, Exceptional Talent, and a Power Ecosystem to deliver outcomes at the frontier of what is possible.

About the Role

The AI Engineer (Consultant) is a hands-on engineer at the core of Accenture's AI delivery capability. This role is for those who build intelligent systems - machine learning pipelines, AI-powered applications, data-driven solutions, and AI integrations - and who want to do that work at the frontier of enterprise AI. Consultants work within delivery teams, turning business requirements into production-grade AI solutions under the guidance of technical leads and managers.

The expectation is active, daily engineering: writing code, building machine learning models, designing AI pipelines, implementing integrations, and maintaining the MLOps and DevOps practices that keep production systems running. Consultants on this team are also expected to invest continuously in learning - AI is evolving rapidly, and staying current is a professional responsibility, not optional.

Position Responsibilities

AI Application Development

• Design and build AI-powered applications - Python backends, REST and event-driven APIs, and frontend interfaces - to production engineering standards
• Implement AI application workflows: model serving, prediction pipelines, real-time inference, and integration with business systems
• Translate business requirements into technical specifications; work with managers and clients to clarify scope, surface ambiguities, and deliver against agreed outcomes

Machine Learning Development

• Build, train, and deploy machine learning models using established frameworks (PyTorch, TensorFlow, scikit-learn, LightGBM): feature engineering, model selection, hyperparameter tuning, and lifecycle management
• Implement appropriate ML techniques for different use cases: supervised learning, unsupervised learning, time series forecasting, classification, and regression
• Design and maintain model versioning, experimentation tracking, and reproducible training pipelines using MLOps tools

Data Engineering & Pipelines

• Design and implement data pipelines: ingestion, transformation, enrichment, and preparation at scale
• Build ETL/ELT workflows connecting data sources to ML training and inference systems
• Implement data quality checks, validation, and monitoring to ensure data integrity throughout the pipeline

Model & System Integration

• Integrate trained models into production systems with robust error handling, monitoring, and rollback capabilities
• Design and implement model serving architectures: batch prediction, real-time APIs, and edge deployment where required
• Build ML monitoring and observability: prediction drift detection, model performance tracking, and automated retraining triggers

MLOps & Production Excellence

• Maintain CI/CD pipelines for model code, training scripts, and infrastructure - including automated testing and deployment strategies
• Instrument ML systems with production observability: latency tracking, prediction profiling, model performance logging, and anomaly detection
• Build model testing suites: unit tests, integration tests, and validation against held-out datasets; implement data drift detection and model decay alerting

Continuous Learning

• Maintain active, current knowledge of ML frameworks, tooling, and research - testing new approaches and bringing relevant innovations into the team's engineering practice
• Contribute to internal knowledge sharing: documenting patterns, building reusable components, and supporting capability development within the team

Travel may be required for this role. The extent of travel will vary from 0% to 100% depending on client requirements and business need.

Why This Role

This team builds some of the most technically advanced AI systems in enterprise technology today. For an engineer at the start of their career in AI, there is no better environment to learn fast, work on hard problems, and build the depth and breadth that will define the next decade of enterprise AI. The work ships. The feedback loop is tight. The team is exceptional.

Accenture is an Equal Opportunity Employer.

All employment decisions shall be made without regard to age, race, creed, colour, religion, sex, national origin, disability, or any other basis protected by applicable law.

Core Pillars

Hands-On Builder | ML Engineering | Production Excellence | Continuous Learner

Core Requirements

3+ years of software engineering in production - Python, data engineering, or