Why Gegidze?
Gegidze - Business consulting and full stack services.
Everything that you need to grow and sustain your business. End-to-end digital solutions for Startups & SMEs.
We are transforming Georgia and the Caucasus region into the new tech hub.
Our services: HR Tech, Design, Legal, Finance & Tax and Sales & Marketing
Since 2017, we have delivered success to the leading Startups and SMBs across 16 countries worldwide.
Success in Numbers:
• 100+ remote teams built
• 200+ projects accomplished
• $ 50M+ earned for our customers
At our agency, with 6 locations in Tbilisi, Yerevan, Berlin, Dublin, Warsaw and Tallinn, we work with great passion daily to build and innovate great brands.
About the role
Currently, we are looking for a Python Engineer – ML/Data Pipelines (Kubeflow, GCP) for a key client, an innovative company specializing in data-driven solutions. Focused on leveraging technology, people, and processes, the company develops and optimizes software, data infrastructure, and AI-powered tools for businesses across industries. With a collaborative, agile environment, it emphasizes continuous learning, career growth, and remote work flexibility.
We are looking for a skilled Software Engineer to build and maintain Kubeflow Pipelines on Google Cloud, ensuring seamless machine learning model integration into production. This role involves operationalizing Proof of Concept (PoC) solutions, optimizing performance, and transforming Python-based functionalities into scalable ML pipeline components.
A team of Data Scientists are creating some POC projects about online marketing segmentation or attribute enrichment, which are then “operationalized” by the team converting these to unified Kubeflow pipelines. Some testing, optimization on performance or memory usage are additionally implemented.
Size of the team: 5 consisting of project lead, 3 data/software engineers, 1 QA.
Your duties
As a Python Engineer – ML/Data Pipelines (Kubeflow, GCP), you will be responsible for:
- Developing and maintaining Kubeflow Pipelines on Google Cloud for efficient machine learning model deployment
- Collaborating with data scientists to understand and implement their requirements into production-grade pipeline components
- Analyzing and adapting Python-based data science scripts and functionalities to align with pipeline architecture
- Optimizing pipelines for scalability, performance, and reliability
- Debugging, monitoring, and troubleshooting pipeline issues in production
- Contributing to continuous improvement efforts for pipeline development processes and tools
Requirements
- 4+ years of experience with Python
- Strong knowledge and familiarity with data analysis processes Experience with Kubeflow Pipelines and/or similar workflow orchestration tools
- Strong understanding of machine learning concepts and workflows
- Proficiency in Google Cloud Platform (GCP) and cloud-based deployment
- Knowledge of machine learning concepts and data science workflows
- Strong debugging, problem-solving, and communication skills
- Strong communication and teamwork skills for effective collaboration with cross-functional teams
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field
- English language upper intermediate (B2) is a must
Nice to have:
- Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Experience with containerization and orchestration tools (e.g., Docker, Kubernetes)
- Knowledge of CI/CD pipelines and DevOps practices
- Experience working with databases, particularly Snowflake, and integrating them into machine learning pipelines
- Exposure to SQL and database optimization techniques for efficient data retrieval and processing
Benefits
Join us
If that sounds just like you, simply apply with your CV: talent@gegidze.com or press the button “Apply Now.”
Our hiring process:
After you hit the button “Apply Now” and upload the resume, our HR team will review your profile.
If the skills and experiences mentioned in your resume match the requirements, you will have:
1. Quick introduction call with our HR team
2. Technical/soft skill interview with client
3. Introduction call with the end client
After receiving positive feedback from the client we will circulate the job offer to you.
Wish you good luck and hope to see you in our incredible team of top digital talents!
