MLOps Engineer – Portfolio Optimisation and Customer Analytics Platform (Banking

This is a remote position.

We are looking for an MLOps Engineer to support an enterprise analytics and optimisation platform within an international banking environment. The platform underpins pricing, capital allocation, and customer lifetime value decisions across multiple markets and product lines.It operates at scale with regular model retraining cycles and governed analytics processes. Analytical outputs feed both traditional reporting layers and LangChain and LangGraph based GenAI workflows that generate automated insights and scenario analysis. This role focuses on operationalising analytical models and ensuring stable, repeatable production workflows.

Responsibilities

Design and operate training and deployment pipelines for analytical and optimisation models

Automate model retraining, validation, and promotion processes

Ensure reproducibility and consistency across development, testing, and production environments

Support scalable analytical workloads across cloud platforms

Enable structured exposure of model outputs to LangChain and LangGraph workflows

Monitor performance, stability, and reliability of ML pipelines

Collaborate closely with data scientists and analytics teams to streamline experimentation to production

Requirements

Strong experience in MLOps or ML platform engineering

Solid Python skills for automation and tooling

Hands on experience with Docker and Kubernetes

Practical experience with MLflow or similar model lifecycle management tools

Experience with workflow orchestration tools such as Airflow

Hands on experience with CI/CD pipelines

Experience working with cloud data platforms

Strong understanding of reproducibility and environment management

Fluent English for professional collaboration

Nice to have

Experience integrating ML outputs with LangChain or LangGraph workflows

Exposure to banking, finance, or regulated environments

Experience with optimisation models or large scale analytical platforms

Understanding of data governance and audit requirements

Benefits

Solid, competitive salary

Work in a multinational environment on international projects

Comprehensive healthcare

Long-term B2B contract with a stable project pipeline

Remote work model

Originally posted on Himalayas