Data Scientist

Job Title: Data Scientist / AI & ML Engineer (Gen AI & LLM)

Location: Indore, India (On-Site/Hybrid as needed)

Employment Type: Full-Time, Immediate Joiner

Experience: 1- 4 Years

Company Overview

Hvantage Tech Solutions Pvt. Ltd. is a leader in AI and data-driven solutions across multiple industries. We deliver innovative, scalable machine-learning and generative AI (Gen AI) applications that solve complex business problems and drive digital transformation.

Position Overview

We are seeking an enthusiastic Data Scientist / AI & ML Engineer with hands-on experience in Large Language Models (LLMs) and Gen AI. You will design, develop, and deploy AI/ML solutions for real-world use cases, leveraging state-of-the-art LLMs and classic machine-learning techniques. This role requires a strong foundation in data science, proficiency in Python, and the ability to drive projects from prototype to production.

Key Responsibilities

1. Gen AI & LLM Development

2. Evaluate, fine-tune, and deploy pre-trained LLMs (e.g., OpenAI GPT, LLaMA, BERT) for tasks such as summarization, question answering, and conversational AI.

3. Customize Gen AI model pipelines using frameworks like Hugging Face Transformers, LangChain, or RLHF techniques.

4. Machine-Learning Engineering

5. Develop and maintain end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, and deployment.

6. Implement classical ML algorithms (regression, classification, clustering) in scikit-learn, XGBoost, or LightGBM.

7. Data Preparation & Analysis

8. Acquire and preprocess structured and unstructured data from various sources (text, logs, APIs).

9. Perform EDA, statistical analysis, and data visualization using Pandas, NumPy, Matplotlib, and Seaborn.

10. Model Deployment & MLOps

11. Containerize models with Docker and orchestrate with Kubernetes or AWS SageMaker.

12. Build CI/CD for ML with MLflow, Kubeflow, or Azure ML pipelines to ensure reproducibility and monitoring.

13. Performance Monitoring & Optimization

14. Monitor model performance in production: drift detection, periodic retraining, and performance logging.

15. Optimize model latency and throughput for real-time inference.

16. Collaboration & Communication

17. Collaborate with cross-functional teams (product managers, engineers, UX) to gather requirements and integrate AI/ML features.

18. Translate complex technical concepts into clear insights for stakeholders and business users.

19. Research & Innovation

20. Stay current with AI/ML research, evaluate new architectures, and pilot PoCs for emerging technologies.

21. Present findings and best practices in internal knowledge-sharing sessions.

Required Skills & Qualifications

• Experience:

• 1-4 years of professional experience in data science, AI/ML engineering, or related roles.

• Hands-on experience with LLMs and Gen AI frameworks (e.g., Hugging Face, LangChain).

• Technical Expertise:

• Proficiency in Python and libraries: PyTorch, TensorFlow, scikit-learn.

• Practical experience in fine-tuning LLMs and building NLP pipelines.
• Strong grasp of ML fundamentals: supervised/unsupervised learning, feature engineering, evaluation metrics.

• Experience with data processing tools: Pandas, NumPy, SQL.

• MLOps & Deployment:

• Familiarity with containerization (Docker) and orchestration (Kubernetes).

• Exposure to cloud ML platforms (AWS SageMaker, Azure ML, GCP AI Platform).

• Knowledge of ML lifecycle management: versioning, tracking, and monitoring (MLflow, Kubeflow).

• Soft Skills:

• Excellent verbal and written communication.

• Strong analytical and problem-solving abilities.
• Ability to work independently and in agile teams.
• Rapid learner passionate about AI/ML innovation.

Preferred Qualifications

• Advanced degree (MS/PhD) in Computer Science, Data Science, or related field.
• Familiarity with reinforcement learning or vision-language models.
• Experience deploying conversational AI (chatbots) in production.
• Certification in cloud or ML (AWS, Azure, Google Cloud).

What We Offer

• Competitive salary and performance bonuses.
• Flexible work arrangements and remote-first culture.
• Learning stipend for conferences and certifications.
• Collaborative environment with global AI experts.

How to Apply

If you're an immediate joiner with hands-on LLM and data science experience, please submit your resume and a brief cover letter to Or can reach out to us over Whatsapp at We look forward to accelerating innovation with you