Remote Senior ML Engineer – Production AI & MLOps

Smart Working; Islamabad; Remote; PKR 4,200,000 - 6,800,000; Full time

Job summary

Smart Working is seeking a Senior ML Engineer to build and modernise an AI platform, focusing on productionising NLP and generative AI systems. The role combines Applied AI, MLOps and backend engineering to create observable, reliable ML capabilities for global teams.

You will develop production ML applications, deploy and evaluate ML models, and implement guardrails for safe AI outputs while enabling scalable ML workflows in a remote-first environment.

Qualifications

• 6+ years of professional AI/ML experience.
• 5+ years of professional MLOps experience.
• 2+ years of real Applied AI experience.
• Strong Python experience and productionising AI/ML apps.
• Experience with generative AI/LLMs and evaluation such as grounding.

Responsibilities

• Refactor, modernise and productionise existing ML models and Applied AI capabilities.
• Build new ML components and modular production-ready systems.
• Develop production ML applications and services using Python.
• Build and maintain ML pipelines for integration, evaluation, deployment and operation.
• Design and automate model evaluation pipelines with golden datasets and quality gates.
• Evaluate models using metrics for generative AI, classification and other use cases.
• Implement guardrails for grounding and hallucinations in outputs.
• Apply Applied AI techniques including RAG where appropriate.
• Design provenance for models, prompts and input data.
• Build infrastructure supporting shadow testing, A/B testing and safe deployment.
• Support labeling and curation of golden datasets for evaluation.

Skills

Python

Applied AI

MLOps

Production ML

NLP/Gen AI

Model evaluation

Observability

Backend engineering

Data provenance

Tools

FastAPI

Docker

Kubernetes

Argo Workflows

AWS

Azure

GCP

Job description

Smart Working is seeking a Senior ML Engineer to build and modernise an AI platform, focusing on productionising NLP and generative AI systems. The role combines Applied AI, MLOps and backend engineering to create observable, reliable ML capabilities for global teams.

You will develop production ML applications, deploy and evaluate ML models, and implement guardrails for safe AI outputs while enabling scalable ML workflows in a remote-first environment.