ML / MLOps Engineer

About this role

Industry

Aviation / Automotive

Team size

1-3

Seniority

Mid / Senior

Department

Software Engineering

## Tech stack

Python

SQL

MLflow

PyTorch or TensorFlow

Databricks / AWS SageMaker

At Grape Up, we transform businesses by unlocking the potential of AI and data through innovative software solutions.

We partner with industry leaders in the automotive and aviation to build sophisticated Data & Analytics platforms that support production machine learning and AI use cases. Our solutions provide comprehensive capabilities spanning data storage, management, advanced analytics, machine learning, enabling enterprises to accelerate innovation and make trusted, data-driven decisions.

## Responsibilities

• Partner with Data Science teams to productionize models and work across the ML lifecycle – from experimentation and training to deployment, monitoring, and continuous improvement
• Design and implement scalable ML infrastructure, with the opportunity to take ownership of architecture and deployment decisions
• Build and maintain CI/CD pipelines for model development, testing, and deployment on Databricks or AWS SageMaker
• Establish MLOps best practices: experiment tracking, model versioning, feature stores, and governance (MLflow, Unity Catalog, or SageMaker ecosystem)
• Monitor and optimize ML infrastructure for performance, cost efficiency, and reliability
• Work on real-world ML systems running in production – not just experimental models

## Requirements

• Master’s degree in computer science, Machine Learning, Data Engineering, or a related field
• 3+ years of professional experience in ML Engineering, MLOps, or DevOps, with hands-on exposure to production ML systems
• Strong Python programming skills and proficiency with ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with key parts of the ML lifecycle: experiment tracking (e.g. MLFlow), workflow orchestration, model deployment, and production operations
• Hands-on experience ...