We are looking for a Senior AI/ML Engineer / Data Scientist with strong hands-on expertise in Classical Machine Learning, Statistical Modelling, Statistics, and Optimization , along with working knowledge of LLMs and Generative AI .

The role will primarily focus on ML modelling, statistical analysis and optimization solutions for complex business problems. GenAI/LLM will be a secondary component.

Skill focus: 70% Classical ML / Statistics / Optimization | 30% LLM / GenAI Key Responsibilities

- Translate complex business problems into ML, statistical and optimization solutions.
- Design, develop and implement classical machine learning models.
- Perform statistical analysis, predictive modelling and optimization.
- Apply appropriate ML algorithms based on business objectives and data characteristics.
- Perform data exploration, feature engineering, model development and validation.
- Develop optimization models for business decision-making and operational problems.
- Evaluate and improve model accuracy, robustness and scalability.
- Build prototypes and convert successful analytical solutions into production-ready solutions.
- Apply LLM and Generative AI techniques to selected business use cases.
- Work with LLM APIs, prompt engineering and basic RAG/GenAI architectures.
- Collaborate with Data Engineers, Backend Engineers and Frontend Engineers on end-to-end solutions.
- Support model deployment, testing, documentation and client handover.
- Present technical approaches, analytical findings and recommendations to business stakeholders.
- Adapt ML solutions based on changing business requirements.

Required Skills

- 6+ years of experience in Data Science, Machine Learning, AI/ML Engineering or related areas.
- Robust hands-on experience in Classical Machine Learning.
- Strong understanding of statistics,



mathematics and statistical modelling.
- Hands-on experience with optimization techniques and modelling.
- Advanced Python programming skills.
- Strong experience with Pandas, NumPy and Scikit-learn.
- Experience with supervised and unsupervised learning.
- Strong understanding of feature engineering, model selection, evaluation and validation.
- Proven experience solving real-world business problems using ML/statistical techniques.
- Working knowledge of LLMs and Generative AI.
- Experience with LLM APIs and prompt engineering.
- Strong analytical, problem-solving and communication skills.

Good to Have
- Azure or other cloud platform experience.
- Azure ML or similar ML platforms.
- Time-series modelling and forecasting.
- Operations Research / Decision Science experience.
- RAG and vector database exposure.
- Experience integrating ML models into applications.
- Consulting or client-facing experience.
- Experience developing optimization/business decision-support solutions.

Not Mandatory
- MCP Server
- Deep Agentic AI
- Multi-Agent orchestration
- Extensive LLM architecture experience

Ideal Candidate The ideal candidate is a Senior Data Scientist / ML Engineer who is strong in traditional Machine Learning, Statistics, Statistical Modelling and Optimization , with sufficient GenAI knowledge to contribute to the LLM component. Candidates who are primarily LLM/GenAI developers without strong Classical ML and Optimization experience should not be prioritized. Interview Focus

- Machine Learning fundamentals
- Statistics and statistical modelling
- Optimization techniques
- Python and ML implementation
- Real-world ML problem solving
- Model selection and evaluation
- Business problem → ML solution approach
- LLM/GenAI fundamentals
- Productionization of ML solutions
- Client/stakeholder communication

Skills: llm,machine learning,optimization

📌 Senior AI/ML Engineer – Machine Learning, Optimization & GenAI (Ahmedabad)
🏢 Zorba AI
📍 Ahmedabad