Senior AI Engineer

Opentext

6 - 8 years

13 - 17 Lacs

bengaluru

Posted:11 hours ago| Platform:

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Skills Required

continuous integration numpy data engineering pandas aws kubernetes natural language processing neural networks ci/cd microsoft azure artificial intelligence java data science gcp oops ml

Work Mode

Work from Office

Job Type

Full Time

Job Description

YOUR IMPACT:

Data Engineer

WHAT THE ROLE OFFERS:

Architect and deploy
enterprise-grade data pipelines
that integrate
Generative AI
and
Machine Learning models
to solve business problems.
Conduct research on the latest innovations in AI/ML and
quickly build proof-of-concepts (PoCs)
to validate new ideas.
Apply advanced
Data Science fundamentals
to ensure data quality, feature engineering, and model interpretability.
Design and optimize data infrastructure (batch/real-time) for performance, reliability, and scalability.
Implement
MLOps practices
to automate model training, deployment, and monitoring.
Mentor junior engineers and drive best practices in coding, testing, and system design.
Stay updated with emerging trends in AI/ML, data engineering, and cloud technologies.

WHAT YOU NEED TO SUCCEED:

6-8 years of hands-on experiencein data engineering, with a focus onenterprise-ready data science projects.
Expertise inGenerative AItools/frameworks (e.g. AI Agentic frameworks) and their integration into production systems.
Ability to research emerging AI/ML trends, rapidly develop proof-of-concepts (PoCs) & drive innovation.
Strong foundation inMachine Learning(supervised/unsupervised learning, NLP, neural networks) andData Science concepts(statistics, data modeling).
Proficiency inPythonand libraries (Pandas, NumPy, TensorFlow/PyTorch, scikit-learn).
Prior experience in AI model deployment, fine-tuning, and optimization.
Experience withprogramming best practices(OOP, version control, CI/CD) and distributed systems.
Knowledge of cloud platforms (AWS/Azure/GCP)
Strong analytical, problem-solving, and communication skills.
Experience buildingmicroservicesand orchestrating them viaDocker/Kubernetes.
Familiarity withMLOps tools(MLflow, Kubeflow) and monitoring frameworks.
Background in theIT domain(e.g., fintech, healthcare, e-commerce).
Familiarity with APIs and real-time data processing frameworks.
Good to have experience in Java programming.

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