AI Engineers

Infosys; Bengaluru; On-site; INR 1,000,000 - 2,000,000; Full time

Job summary

Infosys in Bengaluru is looking for a talented engineer to join their Data Analytics Unit. The role involves designing, developing, and deploying machine learning and AI models while collaborating with data engineers and product teams.

Ideal candidates should have relevant qualifications such as a Bachelor of Engineering or equivalent, with strong skills in MLOps, cloud services, and data processing. This is a fantastic opportunity to work on cutting-edge technologies in a dynamic environment.

Qualifications

• Proven experience in designing, developing, and deploying machine learning and AI models.
• Competent in building and maintaining data pipelines for training and inference.
• Familiarity with supervised and unsupervised learning algorithms.

Responsibilities

• Design, develop, and deploy machine learning and AI models.
• Build and maintain data pipelines for training and inference.
• Collaborate with product teams to enhance model accuracy and performance.

Skills

Machine Learning

AI Models

Data Pipelines

NLP

Computer Vision

Deep Learning

MLOps

Docker

Kubernetes

Cloud Services

API Development

Education

Bachelor of Engineering

BTech

BSc

BCA

MCA

MTech

MSc

Tools

MLflow

Kubeflow

Airflow

Spark

PySpark

Job description

Educational Requirements

Bachelor of Engineering, BTech, BSc, BCA, MCA, MTech, MSc

Service Line

Data Analytics Unit

Responsibilities

• Design, develop, and deploy machine learning and AI models
• Build and maintain data pipelines for training and inference
• Work on supervised and unsupervised learning algorithms
• Implement NLP, Computer Vision, or Deep Learning solutions
• Optimize models for performance, scalability, and accuracy
• Collaborate with data engineers, analysts, and product teams
• Deploy models using cloud platforms (AWS/Azure/GCP)
• Monitor model performance and perform continuous improvements
• Conduct data preprocessing, feature engineering, and model evaluation
• Document models, processes, and experiments

Additional Responsibilities

• Experience with Generative AI / LLMs (GPT, LangChain, Hugging Face)
• Knowledge of MLOps tools (MLflow, Kubeflow, Airflow)
• Experience with Docker and Kubernetes
• Familiarity with Big Data tools (Spark, PySpark)
• Experience with REST APIs and microservices architecture
• Knowledge of cloud AI services (AWS SageMaker, Azure ML, GCP AI)
• Understanding of vector databases and embeddings (FAISS, Pinecone)
• Exposure to CI/CD pipelines and DevOps practices

Technical and Professional Requirements

• Primary skills: Domain: Turbomachinery – Steam Turbine – Rotor

Preferred Skills

• Technology: AI-AI Engineering – AI/ML Solution Architecture and Design