Experience: 6+ years
Location: India (WFO 2 days/week from any Persistent office)
Interview Process: CI (Client Interview)

Overview
We are looking for a hands-on ML Engineer to partner closely with the Sales Data Science Capabilities team, supporting the development, maintenance, monitoring, and continuous improvement of AI/ML models and LLM-enabled applications. This is a highly execution-oriented role focused on translating business and data science requirements into scalable, reliable, and well-monitored model solutions.

Key Responsibilities

- Develop, enhance, and maintain AI/ML models supporting Sales use cases — lead scoring, product recommendation, seller prioritization, customer segmentation, next-best-action, and seller productivity.
- Support development of LLM and GenAI-enabled applications, including prompt experimentation, model evaluation, retrieval workflows, and quality measurement.
- Partner with the DS Capabilities team to translate business problems into model development plans, analytical approaches, and technical implementation.
- Build and maintain model training, scoring, validation, and monitoring pipelines in collaboration with data engineering and platform teams.
- Monitor model performance, data quality, drift, stability, and business impact; proactively identify issues and recommend improvements.




- Conduct model refreshes, feature updates, backtesting, performance diagnostics, and enhancement analyses to improve model accuracy and business relevance.
- Support experimentation and measurement for AI/ML capabilities — preparing datasets, defining model-level diagnostics, and analyzing treatment/control or pre/post-performance.
- Write clean, scalable, well-documented SQL and Python code for data extraction, feature engineering, modeling, evaluation, and reporting.
- Create technical documentation covering model logic, assumptions, features, performance metrics, monitoring dashboards, and operational handoff.

Required Qualifications

- 5+ years of hands-on experience developing and deploying AI/ML models.
- Experience with model monitoring, model refreshes, performance tracking, data quality checks, and production ML maintenance.
- High proficiency in SQL, Python, and data storytelling.
- Strong communication skills — able to explain model performance, risks, and tradeoffs to both technical and non-technical stakeholders.

Valuable to Have

- Experience developing GenAI and/or LLM-based models.
- Experience working in Sales, Marketing, Product, Customer Support, Web, Strategy, or CRM domains.

📌 ML Engineer – Sales Data Science Capabilities (India)
🏢 iKrux
📍 India