AI, Data & Analytics

Ishita Mehta

Machine Learning Engineer

Reproducible model training and monitored serving workflows.

Ahmedabad, India

Fictional sample · Not a verified candidate record

Professional profile

Machine Learning Engineer with an illustrative 11-year career focused on reproducible model training and monitored serving workflows. Brings together python, pytorch and feature pipelines with practical delivery experience. Selected work below shows the problem, my contribution and the handover material rather than unsupported performance claims.

Professional experience

Jul 2022 - Present

Machine Learning Engineer

Asterline Applied Intelligence Lab

Responsible for scoped reproducible model training and monitored serving workflows work, coordinating the relevant reviewers and delivery partners.

  • Versioned shared transformations and introduced a reproducible training-to-serving package.
  • Created a held-out evaluation harness and documented rollback triggers with the product owner.
  • Maintained evaluation protocol and made unresolved questions visible before handover.
Jul 2018 - Jun 2022

Machine Learning Engineer

Northmere Applied Intelligence Lab

Supported progressively more complex work in reproducible model training and monitored serving workflows, with a defined review process.

  • Used python and mlflow on assigned work; recorded decisions so colleagues could understand the approach.
  • Prepared experiment registry and release checklist and incorporated specialist feedback before closing the workstream.
Jul 2015 - Jun 2018

Junior Data Specialist

Cedarfield Applied Intelligence Lab

Built foundations through supported assignments, observation and practical feedback.

  • Assisted with pytorch and containerisation, checking work with an experienced reviewer.
  • Kept organised work records and developed clear handover habits through supervised practice.
02-02 · D01 / Signature / BalancedFictional sample · 1 / 2
Ishita MehtaMachine Learning Engineer / Continued

Core capabilities

01Python02PyTorch03Feature pipelines04MLflow05Containerisation06Drift monitoring

Experiments & evaluations

01Dataset provenance

Demand model service

The challenge

Training and serving used different feature calculations.

My contribution

Versioned shared transformations and introduced a reproducible training-to-serving package.

Deliverable Model package and feature contract

02Evaluation protocol

Model release gates

The challenge

New models lacked consistent comparison criteria.

My contribution

Created a held-out evaluation harness and documented rollback triggers with the product owner.

Deliverable Experiment registry and release checklist

Education

2013 - 2015

M.Tech in Machine Learning

Asterbridge Institute of Professional Studies

Specialist study with a practice focus on python and pytorch.

2009 - 2013

Bachelor of Technology / Science in the relevant discipline

Cedarhaven College of Applied Studies

Foundation study, practical assignments and supervised learning. Fictional institution and qualification record.

Continuing development

2024

Python - advanced practice workshop

Scenario exercises and peer review in reproducible model training and monitored serving workflows.

2025

MLflow - reflective practice seminar

Applied learning reviewed through a bounded example and a written reflection.

Practice notes

Work focus
Reproducible model training and monitored serving workflows
Evidence status
Illustrative work descriptions; no source artefacts attached
Contribution scope
Owned the stated workstream, not all team outcomes

Languages

English - professional working / Hindi - professional working