ML/MLOps Engineer
Offer summary

(Summary generated by AI based on the full job description)

The project focuses on building advanced Data & Analytics platforms for the automotive and aviation sectors to support production machine learning and AI use cases. Practical experience with Python, PyTorch, TensorFlow, scikit-learn and platforms like Databricks or AWS SageMaker is required. Responsibilities include productionizing ML models, designing infrastructure, maintaining CI/CD pipelines, and implementing MLOps best practices including model monitoring and performance optimization.

newyou can start ASAP

ML/MLOps Engineer

Company: Grape Up Sp. z o.o.

from: 29 June 2026
to: 29 July 2026
18 000 - 25 000net (+ VAT)/ mth.B2B contract (full-time)
15 000 - 21 000gross/ mth.contract of employment
Salary details
basic salary
Offer parameters
level:senior • expert
working mode:remote • hybrid • full office
Kraków, Grzegórzki
Kraków, GrzegórzkiStanisława Żółkiewskiego 17aView on map

Requirements

Expected technologies

PyTorch
TensorFlow
scikit-learn
AWS
Python
Databricks

Optional technologies

MLFlow
Docker
Kubernetes
CloudFormation
Terraform

Operating system

Windows
macOS

Our 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

Optional

  • 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)

Your 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

About the project

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.

This is how we organize our work

This is how we work

at the client's siteyou focus on a single project at a timeyou have influence on the technological solutions appliedyou have influence on the productagilescrum

Team members

backend developerfullstack developertechnical leaderdevOpsproduct ownerproject manager

This is how we work on a project

  • Clean Code
  • code quality measures
  • code review
  • pair programming
  • TDD
  • architect / technical leader support
  • Continuous Deployment
  • Continuous Integration
  • DevOps
  • documentation
  • issue tracking tools
  • test automation
  • testing environments
Company

Development opportunities we offer

  • assistance in preparation to public speeches
  • external training
  • industry-specific e-learning platforms
  • substantive support from technological leaders
  • support of IT events
  • technical knowledge exchange within the company

What we offer

  • Non-corporate work environment among experienced engineers
  • Individual growth & development plan supported by cyclical feedback sessions
  • Access to knowledge platforms (e.g. Pluralsight)
  • Equipment of your choice
  • Financing of conferences, external trainings, and certifications
  • Language lessons (English, German and Polish for foreigners)
  • LuxMed private medical care
  • Weekly Lunch & Learn where we meet up in the office, lunch together, and share our knowledge
  • Employee referral program
  • Rewards for the success of the month and year awarded by our employees
  • Special rewards for your years with us (G-Man)
  • Integration activities

Benefits

  • private medical care
  • sharing the costs of foreign language classes
  • sharing the costs of professional training & courses
  • remote work opportunities
  • flexible working time
  • fruits
  • integration events
  • corporate library
  • no dress code
  • video games at work
  • coffee / tea
  • drinks
  • parking space for employees
  • leisure zone
  • extra social benefits
  • baby layette
  • employee referral program
  • charity initiatives

Recruitment stages

  • 1.
    Application
  • 2.
    HR + technical interview
  • 3.
    Meeting with the Manager
  • 4.
    Offer
  • 5.
    Feedback

Grape Up Sp. z o.o.

Hi, we are Grape Up!
Our company provides technology consulting and modern software development services for mission-critical products. We specialize in delivering innovative solutions powered by cloud and AI.

This is how we work

ML/MLOps Engineer
15k–21k zł / mth. (CoE), 18k–25k zł / mth. (B2B)
I apply to:
Grape Up Sp. z o.o.
Kraków, Grzegórzki
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