Machine Learning Engineer (MLE) - Senior/Associate Lead

Hiring: Urgent immediate resources need for Machine Learning Engineer (MLE) - Senior/Associate Lead @ Bangalore, Hyderabad, Chennai, Pune, Mumbai, Gurgaon, Mohali (Punjab), Panchkula (Haryana), Exp: 5 - 12 Years

Dear Job Seekers,

We are looking for a Machine Learning Engineer (MLE) - Senior/Associate Lead @ Bangalore, Hyderabad, Chennai, Pune, Mumbai, Gurgaon, Mohali (Punjab), Panchkula (Haryana), Exp: 5 - 12 Years

Position: Machine Learning Engineer (MLE) - Senior/Associate Lead

Location: Bangalore, Hyderabad, Chennai, Pune, Mumbai, Gurgaon, Mohali (Punjab), Panchkula (Haryana)

Experience: 5 - 12 Years

Notice Period: Immediate joiners preferred

Job Description:

Must Have:

MLE - Senior/Associate Lead

Sr/ATA MLE

Must have skills: Understanding of financial products like loans, risk monitoring, fraud detection. anomaly detection.

MLE + GCP/AWS + NLP+DL/GenAI (GCP preferred), Bigquery, Python, SQL

Role Description:

Understanding of financial products like loans, risk monitoring, fraud detection.

Collect, clean, and prepare data for analysis.

Develop and implement machine learning models for a variety of tasks, including affordability calculation and fraud detection.

Build and maintain data pipelines.

Develop APIs to make data and models accessible to other teams.

Create reports and dashboards to communicate insights to stakeholders.

Build solutions to identify complex financial, risk & fraud detection models through data mining, analysis, and the development of sophisticated investigative tools

Requires experience documenting and driving solutioning and architecture for Financial Models, has participated in requirement gathering or design sessions and support documentation where applicable (business, functional, UI, usability, data, compliance, data migration, 3rd party tools/ products)

Developing and implementing best-in-class risk analytic solutions, inclusive of scoring and non-scoring models, utilizing Large Language Models (LLMs), Open Source, Machine Learning, and numerical programming frameworks, to build transformative solutions.

Develop and deploy monitoring solutions to track model performance, detect anomalies, and maintain model health; implement metrics to monitor and measure model and strategy impact

Work closely with product managers, DS Research teams, Engineering teams, and data scientists to build futuristic ML models.

Familiarity and/or experience with private and public cloud infrastructures and technologies such as Google Cloud Products (GCP).

In depth understanding and hands-on in MLOps Infrastructure and tooling, such as Containerization, ML Workflow specification as DAG and management with Scheduling/Orchestration frameworks, ML platform for feature and model store

Having experience in model validation is an added advantage.

Technology Stack

Python,

BigQuery

SQL

Rest APIs

GCP

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