AI/ML Engineer

IVTEX Corporate Solutions Private Limited; Khordha; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Ivtex Corporate Solutions Private Limited is seeking an AI/ML Engineer in Bhubaneswar, Odisha. The role covers end-to-end ML lifecycle, data wrangling, model development, evaluation, and deployment with API integration. You may work on Generative AI, NLP, CV, and GenAI tasks as needed.

The candidate should have 2–5 years of experience, a CS/IT/DS/AI/ML degree, and strong Python with ML frameworks. Collaboration with cross-functional teams and a focus on scalable, production-ready solutions is

Qualifications

• B.Tech/B.E./M.Tech/MCA/M.Sc. in CS/IT/DS/AI/ML or related field.
• 2–5 years of relevant AI/ML experience and product exposure.
• Strong Python and ML framework proficiency; model deployment exposure.

Responsibilities

• Design, develop, train, and deploy ML/DL models for business use cases.
• Preprocess data, build features, and evaluate model performance.
• Develop REST APIs for AI/ML models using FastAPI/Flask; production deployment.
• Collaborate with software engineers, data engineers, and PMs; ensure reliability.

Skills

Strong analytical ability

Problem solving

Effective communication

Cross-functional collaboration

Education

B.Tech/B.E./M.Tech/MCA/M.Sc. in CS/IT/DS/AI/ML

Tools

Python

SQL

Scikit-learn

Pandas

NumPy

XGBoost

LightGBM

PyTorch

TensorFlow

Keras

FastAPI

Flask

REST APIs

MySQL

PostgreSQL

Docker

Git

CI/CD

AWS

Azure

GCP

OpenCV

HuggingFace

Job description

Company Description

Ivtex Corporate Solutions Private Limited delivers high-quality, technology-driven solutions tailored to clients’ evolving business needs. The organization specializes in AI, Data Analytics, Consulting, Emerging Technologies, and Cybersecurity, helping companies stay competitive in an increasingly digital world. Ivtex collaborates with organizations across diverse industries to design robust, scalable, and future-ready solutions. Its focus on efficiency, innovation, and measurable outcomes creates a dynamic environment for professionals interested in advanced technology and applied AI.

Job Description – AI/ML Engineer

Position: AI/ML Engineer

Department: Technology / AI & Data Science

Employment Type: Full-Time

Location: Bhubaneswar, Odisha

Reporting To: Technical Lead / Project Manager

Experience: 2–5 Years

Qualification: B.Tech/B.E./M.Tech/MCA/M.Sc. in Computer Science, IT, Data Science, Artificial Intelligence, Machine Learning, or related field

Role Overview

We are looking for a skilled and motivated AI/ML Engineer to design, develop, deploy, and maintain Artificial Intelligence and Machine Learning solutions for real-world business applications.

The candidate will be responsible for the complete ML lifecycle, including data preparation, model development, evaluation, deployment, API integration, performance monitoring, and optimization. The role may also involve Generative AI, Large Language Models (LLMs), computer vision, NLP, and intelligent automation depending on project requirements.

Key Responsibilities

• Design, develop, train, test, and deploy Machine Learning and Deep Learning models.
• Analyze and preprocess structured and unstructured datasets for model development.
• Perform data cleaning, feature engineering, feature selection, and exploratory data analysis.
• Develop predictive models, classification models, recommendation systems, forecasting solutions, and other ML-based applications.
• Build solutions using Python and ML frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or equivalent technologies.
• Develop and integrate Generative AI and LLM-based applications, where required.
• Work with LLM APIs and open-source models for applications such as chatbots, document intelligence, summarization, information extraction, and knowledge assistants.
• Implement RAG (Retrieval-Augmented Generation) pipelines, embeddings, vector search, and prompt engineering for GenAI applications.
• Work on NLP and/or Computer Vision solutions based on project requirements.
• Develop REST APIs using frameworks such as FastAPI or Flask for AI/ML model integration.
• Deploy ML models into production environments and integrate them with web/mobile/backend applications.
• Optimize models for accuracy, latency, scalability, and computational efficiency.
• Establish model evaluation metrics and conduct validation, testing, and performance benchmarking.
• Monitor deployed models for performance degradation, data drift, model drift, and other production issues.
• Maintain proper model versioning, experiment tracking, documentation, and reproducibility.
• Collaborate with software developers, data engineers, business analysts, QA teams, and project managers.
• Convert business requirements into technically feasible AI/ML solutions.
• Research emerging AI/ML technologies and evaluate their applicability to organizational projects.
• Follow data privacy, information security, and responsible AI practices.

Required Technical Skills

Programming:

Python, SQL

Machine Learning:

Scikit-learn, Pandas, NumPy, XGBoost/LightGBM, feature engineering, supervised and unsupervised learning, model evaluation and optimization

Deep Learning:

PyTorch and/or TensorFlow/Keras, neural networks, CNNs, Transformers

Generative AI / LLM:

LLMs, prompt engineering, embeddings, RAG, vector databases, LLM APIs and/or open-source models

NLP:

Text preprocessing, classification, information extraction, semantic search, transformers

Computer Vision – Preferred:

OpenCV, object detection, image classification, OCR and related vision models

API Development:

FastAPI / Flask / REST API integration

Databases:

MySQL/PostgreSQL and exposure to NoSQL databases

MLOps / Deployment:

Docker, Git, CI/CD fundamentals, model versioning, experiment tracking and production model monitoring

Cloud – Preferred:

AWS / Microsoft Azure / Google Cloud Platform

Preferred Tools & Technologies

Exposure to some of the following will be advantageous:

• Hugging Face Transformers
• LangChain / LlamaIndex or similar frameworks
• FAISS / Pinecone / Weaviate / Chroma or other vector databases
• MLflow / Weights & Biases
• Jupyter Notebook
• Git/GitHub/GitLab
• Docker
• Kubernetes
• Apache Airflow
• OpenCV
• ONNX
• Cloud-based AI/ML services

Required Knowledge

The candidate should have a strong understanding of:

• Machine Learning algorithms
• Statistics and probability
• Linear algebra fundamentals
• Data preprocessing and feature engineering
• Model selection and hyperparameter tuning
• Classification, regression and clustering
• Deep Learning architectures
• Transformers and modern AI architectures
• Model evaluation metrics
• Data structures and algorithms
• ML deployment and inference pipelines
• API-based model integration
• Data security and privacy principles

Key Competencies

• Strong analytical and problem-solving ability
• Ability to independently troubleshoot technical issues
• Strong coding and debugging skills
• Research-oriented approach to emerging AI technologies
• Ability to understand business problems and translate them into AI solutions
• Good documentation skills
• Effective communication and cross-functional collaboration
• Ability to manage multiple development tasks and project deadlines

Preferred Candidate Profile

Preference will be given to candidates who have:

• Developed and deployed at least one production-level AI/ML application.
• Hands-on experience taking an ML project from data preparation → model development → deployment → monitoring.
• Experience developing GenAI/LLM applications using RAG or similar architectures.
• Experience integrating AI models with existing software applications.
• Experience working with large datasets and production databases.
• A strong GitHub portfolio or demonstrable AI/ML projects.
• Experience working on government, enterprise, smart-city, surveillance, analytics, or large-scale technology projects will be an added advantage.

Selection Process

Candidates may be evaluated through:

• Resume/Profile Screening
• Technical Interview
• Practical AI/ML Assignment or Coding Test
• Project/Model Demonstration
• Final Technical/Management Discussion

During the technical evaluation, candidates should be prepared to explain one AI/ML project end-to-end, including the business problem, dataset, preprocessing, model selection, evaluation metrics, deployment architecture, challenges faced, and final results.

Expected Deliverables

The selected AI/ML Engineer will be expected to deliver reliable and production-ready AI solutions, maintain appropriate technical documentation, support deployment and integration, monitor model performance, and continuously improve AI/ML systems based on business and project requirements.