Machine Learning Software Engineer II

Remotedxb; Dubai; On-site; AED 350,000 - 550,000; Full time

Job summary

Cambium Learning Group in Dubai seeks an ML Engineer to transition prototypes into scalable production systems, crafting robust ML solutions that run in the cloud.

You will optimize PyTorch models to ONNX, design CI/CD pipelines on AWS, and work with data scientists and engineers to deploy scoring or analytics workloads. This role emphasizes hands-on coding in Python/C++/Java, experience with Docker, and a commitment to reliable, well-documented software.

Qualifications

• 2–5 years of industry experience in ML engineering, software engineering, or data science.
• Proven track record of deploying models to production.
• Hands-on experience with AWS ECS and AWS Lambda.
• Proficiency in Python, C++, or Java.
• Experience with Docker and event-driven architectures.
• Hands-on experience with PyTorch, Scikit-Learn, or TensorFlow.
• Understanding of model optimization including ONNX Runtime and Flash Attention.
• Experience with large-scale computing frameworks and relational/non-relational databases.

Responsibilities

• Lead the transition of ML models from theoretical prototypes into scalable, high-performance production systems.
• Architect and deploy ML solutions utilizing AWS ECS and AWS Lambda.
• Optimize PyTorch models for production deployment using ONNX formats and advanced inference techniques.
• Establish reliable CI/CD pipelines and ensure robust deployments across the AWS ecosystem.
• Design and evaluate algorithms that generate insights from structured and unstructured data.
• Write clean, efficient, and well-tested code with rigorous testing and documentation.
• Collaborate with mathematicians, computer scientists, and statisticians to build tailored scoring solutions.

Skills

2-5 yrs exp ML/DS/SE

Model deployment to production

Python

C++

Java

PyTorch

Scikit-Learn

TensorFlow

ONNX Runtime

AWS ECS

AWS Lambda

NLP

LLMOps

LoRA/qLoRA

Terraform

CloudFormation

Model monitoring

Tools

Docker

Job description

Responsibilities

• Lead the transition of machine learning models from theoretical prototypes into scalable, high-performance production systems
• Architect and deploy ML solutions utilizing AWS ECS and AWS Lambda
• Optimize PyTorch models for production deployment using ONNX formats and advanced inference techniques
• Establish reliable CI/CD pipelines and ensure robust deployments across the AWS ecosystem
• Design and evaluate algorithms that generate insights from structured and unstructured data
• Write clean, efficient, and well-tested code with rigorous testing and documentation
• Collaborate with mathematicians, computer scientists, and statisticians to build tailored scoring solutions

Requirements

• 2–5 years of industry experience in Machine Learning Engineering, Software Engineering, or Data Science
• Proven track record of architecting and deploying models to production
• Hands‑on experience with AWS ECS and AWS Lambda
• Proficiency in Python, C++, or Java
• Experience with Docker and event‑driven architectures
• Hands‑on experience with PyTorch, Scikit‑Learn, or TensorFlow
• Understanding of model optimization including ONNX Runtime and Flash Attention
• Experience with large‑scale computing frameworks and relational/non‑relational databases

Preferred Qualifications

• Experience with AWS SageMaker for managed model training and hosting
• Expertise in LLMOps including LoRA and qLoRA fine‑tuning methods
• Experience building autonomous AI agents to automate workflows
• Deep learning expertise in Natural Language Processing (NLP)
• Experience implementing Infrastructure as Code (IaC) using Terraform or CloudFormation
• Ability to set up model monitoring systems for data and concept drift detection

About the Company

Cambium Learning® Group is an award‑winning educational technology solutions leader dedicated to helping all students reach their potential through individualized and differentiated instruction.