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Aman Jaiswal

@amanjaiswal

I am an ML engineer building production-grade AI and scalable data infrastructure for fintech and e-commerce.

India
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What I'm looking for

I am seeking a remote ML engineering role (Europe time zones) focused on production AI, scalable data infrastructure, team mentorship, and measurable business impact.

I have 6+ years of experience in machine learning, big data, and backend engineering, currently solving ML challenges at petabyte scale at CRED. I build production-grade ML systems and scalable data infrastructure across fintech, retail, e‑commerce, and finance.

At CRED I optimized general risk models and short-term risk prediction systems, extending predictive horizons to 24 months and improving bad-loan recall by ~9%. I improved personalized reward recommendations, lifting look-to-click conversions by ~10%, and designed an AI engineering stack that reduced ops time ~40–45% and improved MTTR/MTTA by 20%.

Previously at Walmart I built ML systems that removed manual work (99% reduction) and delivered multi-million dollar annual savings (register loss recovery, returns analytics). I have led large-scale data migrations, built custom ingestion frameworks, and implemented robust model monitoring and serving pipelines.

I contribute to open source, write technical posts, and mentor junior engineers. I am seeking a remote ML role in Europe where I can apply production AI expertise, scalable data engineering, and a strong focus on measurable business impact.

Experience

Work history, roles, and key accomplishments

CRED logoCR
Current

Software Engineer, Machine Learning

CRED

Nov 2023 - Present (2 years 7 months)

Optimized enterprise-wide risk and short-term default models, improving bad-loan recall by ~9% and extending predictive horizons to 24 months; improved personalized reward recommendations, boosting look-to-click by ~10% and reducing ops time ~40-45% via an AI engineering stack.

Walmart logoWA

Software Engineer III, Data & ML

Walmart

Oct 2021 - Nov 2023 (2 years 1 month)

Built ML-powered systems that cut manual invoice processing by 99% and developed register loss/recovery pipelines saving $2–5M/year; implemented regression and MLflow pipelines to analyze store returns, saving ~$3M/year.

Education

Degrees, certifications, and relevant coursework

Aman hasn't added their education

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