ML Engineer - Sales Data Science Capabilities
Ikrux · Bengaluru · onsite · Posted 34d ago
Undisclosed6–11 yrsfulltimeSourced from
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About this role
Job Category: AI/ML Model Development & Deployment Data Storytelling & Stakeholder Communication GenAI/LLM Experience Model Monitoring & Production ML Maintenance SQL & Python
Job Type: Full Time
Job Location: India
Experience: 6+ years
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.
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.
Good to Have
- Experience developing GenAI and/or LLM-based models.
- Experience working in Sales, Marketing, Product, Customer Support, Web, Strategy, or CRM domains.
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
data qualitydata extractionCustomer Supportcrmml engineerDiagnosticsfeature engineeringCustomer SegmentationML modelsLarge Language Models (LLMs)deploymentData EngineeringBacktestingCommunication SkillsmaintenancemarketingData ScienceArtificial IntelligenceMachine Learning