Software Engineer / Sr. Software Engineer (AI/ML)

Vt-Netzwelt-Private-Limited; Mohali; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Vt-Netzwelt-Private-Limited is seeking a hands-on AI/ML Engineer with strong expertise in machine learning, applied data science and production ML systems. You will drive the full ML lifecycle from data exploration and preprocessing to model development, evaluation, optimisation, deployment and monitoring.

While ML is the focus, you will also work with modern AI technologies such as LLMs, RAG, embeddings and AI-powered applications, enabling contributions across a broad range of AI/ML projects.

Qualifications

• 3–5 years hands-on experience in Machine Learning, Data Science or AI/ML Engineering.
• End-to-end ML lifecycle experience from data exploration to deployment and monitoring.
• Exposure to LLMs, RAG, embeddings and AI-powered applications.

Responsibilities

• Design, develop and optimise ML models for real-world problems.
• Perform data exploration, preprocessing and feature engineering across datasets.
• Build solutions using regression, classification, clustering, forecasting and deep learning.
• Develop ML solutions involving NLP, computer vision, time-series or recommender systems.
• Evaluate algorithms and establish evaluation metrics for ML problems.
• Tune hyperparameters, validate models and monitor performance in production.
• Create scalable batch and real-time inference pipelines.
• Maintain MLOps pipelines for training, deployment, versioning and retraining.

Skills

Machine Learning

Data Science

MLOps

NLP

Computer Vision

Deep Learning

PyTorch

TensorFlow

REST APIs

Docker

CI/CD

AWS

GCP

Tools

scikit-learn

Pandas

NumPy

PyTorch

TensorFlow

Docker

FastAPI

REST APIs

Hugging Face Transformers

AWS

GCP

Azure

Job description

3-5 Years

Full-Time

Job Title: Software Engineer/ Sr Software Engineer

Employment Type: Full Time

Experience Required: 3-5 years

Working Model: Work From Office

Role Summary

We are looking for a hands-on AI/ML Engineer with strong expertise in Machine Learning, applied Data Science and production ML systems.

The ideal candidate should be capable of working across the complete ML lifecycle - from data exploration, preprocessing and feature engineering to model development, evaluation, optimisation, deployment and monitoring.

While Machine Learning is the primary focus of this role, the candidate should also have practical exposure to modern AI technologies such as LLMs, RAG, embeddings and AI-powered applications, enabling them to contribute across a broad range of AI/ML projects.

Key Responsibilities

• Design, develop and optimise machine learning and predictive models for real-world business problems.


• Perform data exploration, preprocessing, feature engineering and feature selection across structured and unstructured datasets.


• Build solutions using regression, classification, clustering, ensemble methods, forecasting and deep learning.


• Develop ML solutions involving NLP, Computer Vision, recommendation systems or time-series data based on project requirements.


• Select appropriate algorithms and defi ne evaluation strategies and metrics for different ML problems.


• Perform hyperparameter tuning, model optimisation, validation and error analysis.


• Build scalable batch and real-time inference pipelines.


• Build and maintain MLOps pipelines covering training, deployment, model versioning, retraining, CI/CD and


• monitoring.


• Monitor model accuracy, data/model drift, latency, cost and production reliability.


• Work with cloud platforms and modern ML infrastructure to deploy scalable solutions.


• Contribute to LLM/Generative AI applications, including RAG, embeddings, semantic search and AI integrations where required.


• Collaborate with clients, Product, Data Engineering and Software Engineering teams to translate business problems into practical AI/ML solutions.


• Evaluate new AI/ML technologies and rapidly build POCs to validate proposed approaches.


• 3–5 years of hands-on experience in Machine Learning, Data Science or AI/ML Engineering.


• Strong understanding of supervised and unsupervised Machine Learning.


• Hands-on experience with scikit-learn, Pandas and NumPy.


• Practical experience with algorithms such as Linear/Logistic Regression, Random Forest, XGBoost/LightGBM, SVM and clustering techniques.


• Strong understanding of feature engineering, feature selection, model validation, cross-validation, hyperparameter tuning and model optimisation.


• Good understanding of ML evaluation metrics for classification, regression and ranking/prediction problems.


• Hands-on experience with PyTorch and/or TensorFlow.


• Good understanding of neural networks and Transformer architectures.


• Experience with at least one area such as NLP, Computer Vision, time-series/forecasting or recommendation systems.


• Strong working knowledge of SQL and experience working with large or messy real-world datasets.


• Experience exposing ML models through REST APIs/FastAPI or similar frameworks.


• Experience deploying and maintaining ML models in production.


• Working experience with Docker, Git and CI/CD.


• Experience with at least one cloud platform - AWS, Azure or GCP.


• Understanding of MLOps, model monitoring, versioning, logging and data/model drift.

Preferred Skills

• AI Agents and agentic workflows.


• Graph RAG or advanced retrieval techniques.


• Hugging Face Transformers.


• Snowflake, Databricks or modern data platforms.


• FAISS, pgvector, Pinecone, Qdrant or similar vector stores.


• LLM/ML evaluation and observability.


• Experience working directly with clients and participating in technical discovery.

About the Team

Our AI team focuses on building practical, purpose-driven solutions that integrate seamlessly into real-world business environments. We design and deploy generative AI systems that are technically robust, scalable, and aligned with business needs—enhancing efficiency without disrupting existing workflows. From identifying the right use cases to developing and refining solutions, we emphasize responsible innovation and delivering long-term value.

Why Join Us

• Opportunity to work on impactful projects for global clients


• Collaborative, growth-oriented, and learning-driven work environment


• Strong focus on career development and continuous upskilling


• Exposure to modern technologies, tools, and best practices