AI Engineer – Data Science & Generative AI

Zerozilla Infotech Private limited; Bengaluru; In loco; INR 1.500.000 - 2.600.000; Tempo pieno

Descrizione del lavoro

Zerozilla Infotech Private Limited in Bengaluru seeks an AI Engineer with a strong Data Science background and 4-6 years of experience to translate research into production AI solutions. You will design, deploy, and optimize AI/ML models, including Generative AI, LLMs, and RAG-based applications, and collaborate with product teams to deliver scalable capabilities.

The role emphasizes building robust pipelines, MLOps, prompt engineering, and governance, with focus on real‑world NLP,

Competenze

• 4-6 years of relevant experience in AI Engineering, Machine Learning, Data Science, or related roles.
• Strong proficiency in Python.
• Hands-on experience with Scikit-learn, Pandas, NumPy, TensorFlow, and/or PyTorch.
• Strong understanding of machine learning algorithms, deep learning, and statistical modeling.
• Practical experience with LLMs, Agentic AI, LangGraph, multi-agent frameworks, MCP, RAG, and A2A protocols.
• Strong understanding of prompt engineering and context engineering.
• Hands-on experience building RAG applications using embeddings, chunking, retrieval techniques, and vector databases.
• Experience in data preprocessing, feature engineering, model training, and evaluation.
• Experience with MLOps tools and model deployment frameworks.
• Working knowledge of SQL and structured/unstructured data.
• Strong analytical, problem-solving, and communication skills.

Mansioni

• Design, develop, deploy, and optimize AI/ML models for real-world business problems.
• Translate business requirements into data science and AI solutions.
• Build and optimize machine learning pipelines for training, evaluation, and inference.
• Work on NLP, recommendation systems, and predictive analytics use cases.
• Develop LLM-powered applications using RAG, Agentic AI, and multi-agent frameworks.
• Implement AI workflows using LangGraph, MCP, and A2A protocols.
• Apply prompt engineering and context engineering to improve LLM performance and response quality.
• Build RAG-based applications using chunking, embeddings, retrieval techniques, and vector databases.
• Perform exploratory data analysis, feature engineering, model selection, and evaluation.
• Develop scalable APIs and microservices for AI model deployment.
• Implement model monitoring, retraining, and performance optimization in production environments.
• Collaborate with product managers, data engineers, software developers, and business stakeholders.
• Ensure data quality, model explainability, and compliance with AI governance standards.
• Stay updated with advancements in AI, machine learning, and Generative AI technologies.

Conoscenze

Python

Scikit-learn

Pandas

NumPy

TensorFlow

PyTorch

LLMs

Agentic AI

LangGraph

MCP

RAG

A2A protocols

prompt engineering

context engineering

embeddings

vector databases

MLOps

SQL

data preprocessing

feature engineering

model training

evaluation

Formazione

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics

Strumenti

MLflow

Airflow

Kubeflow

Amazon SageMaker

Amazon Bedrock

Descrizione del lavoro

About the Role

We are looking for a skilled AI Engineer with a strong Data Science background and 4-6 years of relevant experience to join our team. The ideal candidate should have hands‑on experience in developing, deploying, and optimizing AI/ML models, along with practical expertise in Generative AI, Large Language Models (LLMs), RAG, Agentic AI, and multi‑agent frameworks.The candidate should be capable of translating data science research and business requirements into scalable, production‑ready AI solutions.

Key Responsibilities

• Design, develop, deploy, and optimize AI/ML models for real‑world business problems.
• Translate business requirements into data science and AI solutions.
• Build and optimize machine learning pipelines for training, evaluation, and inference.
• Work on NLP, recommendation systems, and predictive analytics use cases.
• Develop LLM‑powered applications using RAG, Agentic AI, and multi‑agent frameworks.
• Implement AI workflows using LangGraph, MCP, and A2A protocols.
• Apply prompt engineering and context engineering to improve LLM performance and response quality.
• Build RAG‑based applications using chunking, embeddings, retrieval techniques, and vector databases.
• Perform exploratory data analysis, feature engineering, model selection, and evaluation.
• Develop scalable APIs and microservices for AI model deployment.
• Implement model monitoring, retraining, and performance optimization in production environments.
• Collaborate with product managers, data engineers, software developers, and business stakeholders.
• Ensure data quality, model explainability, and compliance with AI governance standards.
• Stay updated with advancements in AI, machine learning, and Generative AI technologies.

Key Performance Indicators (KPIs)

• Accuracy, reliability, and performance of AI/ML models.
• Successful development and deployment of production‑ready AI solutions.
• Quality and effectiveness of RAG and LLM‑based applications.
• Efficiency of model training, evaluation, and inference pipelines.
• Performance optimization and reliability of deployed models.
• Quality of data preprocessing, feature engineering, and model evaluation.
• Effective collaboration with cross‑functional teams.
• Adherence to AI governance and responsible AI practices.

Mandatory Skills & Qualifications

• 4-6 years of relevant experience in AI Engineering, Machine Learning, Data Science, or related roles.
• Strong proficiency in Python.
• Hands‑on experience with Scikit‑learn, Pandas, NumPy, TensorFlow, and/or PyTorch.
• Strong understanding of machine learning algorithms, deep learning, and statistical modeling.
• Practical experience with LLMs, Agentic AI, LangGraph, multi‑agent frameworks, MCP, RAG, and A2A protocols.
• Strong understanding of prompt engineering and context engineering.
• Hands‑on experience building RAG applications using embeddings, chunking, retrieval techniques, and vector databases.
• Experience in data preprocessing, feature engineering, model training, and evaluation.
• Experience with MLOps tools and model deployment frameworks.
• Working knowledge of SQL and structured/unstructured data.
• Strong analytical, problem‑solving, and communication skills.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.
• Previous experience as a Data Scientist transitioning into AI Engineering or ML Engineering.
• Experience with MLflow, Airflow, Kubeflow, Amazon SageMaker, Amazon Bedrock, or similar platforms.
• Knowledge of model explainability, fairness, and responsible AI practices.
• Experience delivering end‑to‑end AI solutions from experimentation to production.
• Exposure to Generative AI, LLM integration, prompt engineering, and vector databases.

What We're Looking For

• A strong analytical thinker with a product‑oriented mindset.
• Someone who can move beyond experimentation and build production‑ready AI systems.
• A professional with hands‑on experience in modern GenAI and agentic architectures.
• A collaborative individual who can work effectively in a fast‑paced, innovation‑driven environment.

About Zerozilla

Zerozilla is a global software development and digital marketing partner delivering technology and performance‑driven digital marketing solutions to businesses seeking scalable growth. Its broader capabilities span software development, cloud applications, UI/UX, software modernization, technology integrations, digital marketing, website development, SEO, content, graphic design, and video editing.