Aviation / Automotive
1-3
Mid / Senior
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 with Databricks or AWS SageMaker, or strong willingness to deepen expertise in one of these platforms
- Experience deploying and operating ML systems preferably on cloud platforms (Azure or AWS)
- Experience with model monitoring, observability, and performance tracking
- Strong problem-solving skills and ability to work independently in fast-paced environments
- Fluency in English and Polish both written and spoken
Nice to have
- PhD degree in Computer Science, Data Engineering, AI, or a related field (completed or in progress)
- Experience with containerized ML workloads using Docker and Kubernetes
- Experience with infrastructure-as-code (Terraform, CloudFormation, or similar)
Recruitment owner
Klaudia Jazowska
ML / MLOps Engineer
apply now
Benefits
Employee referral
Knowledge platforms
Equipment
Integration activities
Employee referral
Knowledge platforms
Equipment
Integration activities
Lunch & Learn
In-house Tech Up
Language lessons
Lunch & Learn
In-house Tech Up
Language lessons
Conferences & training
Development plan
Feedback sessions
Business travel opportunities
Conferences & training
Development plan
Feedback sessions
Business travel opportunities
Check out the next steps of your recruitment process
Application
Send us your CV through the application form.
HR & technical interview
Let’s talk about your experience and expectations.
Meeting with the Manager
Learn more about the project you could be involved in.
Offer
We’re excited to welcome you onboard! Let’s discuss the details.
Feedback
If you’re not lucky this time, we’ll tell you what you can improve to join us in the future.
