Artificial Intelligence / Machine Learning Engineer

Role Overview

Global Pragmatic Solutions is seeking a highly skilled AI/ML Engineer to design, develop, and deploy production-grade machine learning models. You will be instrumental in building the “Intelligent Layer” for our clients, moving beyond proof-of-concepts to deliver AI solutions that are integrated into core business workflows. From NLP-driven automated assistants to predictive forecasting engines, you will turn data into a competitive advantage.

Key Responsibilities

1. Model Development: Design and train advanced ML models (Supervised, Unsupervised, and Deep Learning) to solve complex business problems like anomaly detection, demand forecasting, and churn prediction.
2. Generative AI & LLMs: Implement and fine-tune Large Language Models (LLMs) to enhance enterprise search, automated documentation, and intelligent customer support.
3. Data Pipeline Engineering: Collaborate with Data Engineers to build robust pipelines for data ingestion, cleaning, and preprocessing from Oracle Fusion and EBS sources.
4. AI Integration: Deploy models into cloud environments (OCI, AWS, or Azure) and integrate them with Oracle Cloud applications via REST APIs and OIC (Oracle Integration Cloud).
5. M LOps & Scalability: Establish MLOps best practices, including versioning (DVC), model monitoring, and automated retraining loops to ensure long-term model performance.
6. Ethical AI: Ensure all models are transparent, explainable, and compliant with global data privacy and security standards.

Technical Qualifications

1. Experience: 4+ years of professional experience in Machine Learning, Data Science, or AI Engineering.
2. Programming: Expert proficiency in Python or R, with deep knowledge of libraries such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
3. Cloud & Data: Hands-on experience with Oracle Cloud Infrastructure (OCI) AI Services, or equivalent services in AWS/Azure (Sagemaker/Azure ML).
4. Big Data: Experience with SQL, NoSQL, and big data processing frameworks like Apache Spark.
5. Deployment: Familiarity with containerization (Docker, Kubernetes) and CI/CD for ML (MLOps).

Preferred Skills

1. Advanced degree (Masters or PhD) in Computer Science, Mathematics, or a related field.
2. Experience with Oracle Analytics Cloud (OAC) or embedding AI into Oracle Fusion ERP/HCM.
3. Knowledge of Vector Databases (e.g., Pinecone, Milvus) for RAG (Retrieval-Augmented Generation) architectures.

What We Offer

1. Competitive salary and performance-linked bonuses.
2. High-performance computing (HPC) resources for training and experimentation.
3. A collaborative environment where your research translates directly into client-facing products.