Tecksight's AI practice is expanding and we are seeking an experienced AI & Machine Learning Engineer to design, build, and operationalise AI and ML solutions for enterprise clients across Oracle Cloud, Salesforce, and custom cloud data platforms.

You will work on a mix of predictive ML models, generative AI applications, RAG pipelines, and AI-powered analytics — embedded into enterprise workflows and governed to production-grade standards.

Design, train, evaluate, and deploy ML models for enterprise use cases including demand forecasting, anomaly detection, risk scoring, churn prediction, and classification.

Build and maintain Retrieval-Augmented Generation (RAG) pipelines and GenAI applications on enterprise data — including vector store management, embedding pipelines, and LLM integration.

Implement MLOps practices including model versioning, automated retraining pipelines, monitoring, and drift detection.

Integrate AI models with Oracle Cloud and Salesforce data sources through secure, governed API layers.

Design and document AI governance frameworks including explainability, bias monitoring, access controls, and audit logging.

Collaborate with data engineers on feature engineering and data readiness for AI workloads.

Present model outputs, performance metrics, and business impact to client stakeholders.

4+ years of ML engineering experience including model development, deployment, and production monitoring.

Strong Python skills with hands-on experience in scikit-learn, XGBoost, PyTorch, or equivalent ML frameworks.

Hands-on experience building RAG pipelines and GenAI applications using LangChain, LlamaIndex, or similar frameworks.

Experience with cloud ML platforms — OCI Data Science, Azure ML, AWS SageMaker, or Vertex AI.

Understanding of enterprise data governance, security, and AI explainability requirements.