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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying machine learning models and AI-powered solutions, with a strong focus on LLM applications and real-time deployment. Proven ability to manage the modeling lifecycle and effectively communicate technical results to business stakeholders.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython ProgrammingSQL ProficiencyLLM-Powered SolutionsStakeholder Collaboration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningFeature EngineeringModel EvaluationModel Drift ManagementTuning TechniquesReal-Time InferencePandasScikit-LearnXGBoostLightGBM
Soft Skills
Presentation SkillsCollaborationProject Leadership
Tools & Technologies
OracleSAPWorkday
Industry Keywords
Financial ServicesCredit RiskFraudConsumer CompaniesB2B Companies
Tech Stack
Tools & technologiesOraclePandasPythonScikit-LearnSQL
About the role
Key responsibilities & impact- Build machine learning models and AI-powered solutions for business-critical use cases
- Manage the end-to-end modeling lifecycle, including data extraction, feature engineering, model evaluation, retraining, and real-time deployment
- Design and develop production-ready LLM applications, including RAG systems and multi-agent architectures
- Diagnose model performance issues and select appropriate approaches for each problem
- Lead initiatives from research and scope definition through delivery
- Collaborate with stakeholders and engineering teams across the US and India
- Lead projects or MVPs end to end, including requirements definition and stakeholder alignment
- Present technical work to US clients
- Build dashboards and communicate results to business audiences
Requirements
What you’ll need- Senior-level experience
- Strong Python and SQL skills
- Hands-on use of the ML ecosystem, including pandas, scikit-learn, XGBoost, LightGBM or similar
- Proven experience taking ML models to production, including real-time or low-latency inference
- Experience handling model drift and iterating on models already in production
- Hands-on experience with tuning and feature selection techniques, such as Optuna and backward selection
- Strong experience building LLM-powered solutions, including agents, multi-agent architectures, RAG systems, and API integrations
- Experience leading a project or MVP end to end, including requirements/PRD and stakeholder alignment
- Advanced/fluent English and comfort presenting technical work to US clients
- Familiarity with enterprise platforms such as Oracle, SAP, or Workday and their data models is nice to have
- Experience in financial services, credit risk, fraud, or large consumer/B2B companies is nice to have
- Experience building dashboards and communicating results to business audiences is nice to have
Benefits
Comp & perks- People-first company culture
- Supportive, trusted, and empowered work environment
- Collaboration and teamwork culture
- Opportunity to work on meaningful products and lasting partnerships
- Exposure to strong engineering, design, strategy, and AI projects
- Remote work arrangement