About us

GetInData | Part of Xebia is a leading data company working for international Clients, delivering innovative projects related to Data, AI, Cloud, Analytics, ML/LLM, and GenAI. The company was founded in 2014 by data engineers and today brings together 120 Data & AI experts. Our Clients are both fast-growing scaleups and large corporations that are industry leaders. In 2022, we joined forces with Xebia Group to broaden our horizons and bring new international opportunities.

What about the projects we work with?

We run a variety of projects in which our sweepmasters can excel. Advanced Analytics, Data Platforms, Streaming Analytics Platforms, Machine Learning Models, Generative AI and more. We like working with top technologies and open-source solutions for Data & AI and ML/AI. In our portfolio, you can find Clients from many industries, e.g., media, e-commerce, retail, fintech, banking, and telcos, such as Truecaller, Spotify, ING, Acast, Volt, Play, and Allegro. You can read some customer stories here.

What else do we do besides working on projects?

We conduct many initiatives like Guilds and Labs and other knowledge-sharing initiatives. We build a community around Data & AI, thanks to our conference Big Data Technology Warsaw Summit, meetup Warsaw Data Tech Talks, Radio Data podcast, and DataPill newsletter.

Data & AI projects that we run and the company's philosophy of sharing knowledge and ideas in this field make GetInData | Part of Xebia not only a great place to work but also a place that provides you with a real opportunity to boost your career.

If you want to be up to date with the latest news from us, please follow up on our LinkedIn profile.

About role

MLOps Engineers are responsible for streamlining machine learning project lifecycles by designing and automating workflows, implementing CI/CD pipelines, ensuring reproducibility, and providing reliable experiment tracking. They collaborate with stakeholders and platform engineers to set up infrastructure, automate model deployment, monitor models, and scale training. MLOps Engineers possess a wide range of technical skills, including knowledge of orchestration, storage, containerization, observability, SQL, programming languages, cloud platforms, and data processing. Their expertise covers various ML algorithms and distributed training in environments like Spark. MLOps Engineers are essential for optimizing and maintaining efficient ML processes in organizations.

Responsibilities

• Data analysis tasks, e.g., comparing model results, optimizing training time, suggesting improvements to diminish the number of false positives (autoencoder, XGboost)
• ML pipeline maintenance (monitoring stability metrics, fixing problems, restarting failing ML jobs, migrating to a new data source used in models)
• Tasks aiming to stabilize the environment, fix issues, integrate with the CI process, oversee deployments
• Collaborating with stakeholders to understand the main points and inefficiencies of Machine Learning project lifecycles within the company
• Collaborating with Platform Engineers to set the infrastructure required to run MLOps processes efficiently

Job requirements

• Proficiency in Python and SQL
• Knowledge of Lakehouse platforms - Databricks
• Experience working with Spark
• Familiarity with AWS
• Familiarity with Version Control Systems, particularly GIT
• Ability to work independently, including helping customers to define the scope of tasks
• Familiarity with Scala is a plus
• Experience with cybersecurity and fraud detection is a plus

We offer

• Salary: 160 - 200 PLN net + VAT/h B2B (depending on knowledge and experience)
• 100% remote work
• Flexible working hours
• Possibility to work from the office located in the heart of Warsaw
• Opportunity to learn and develop with the best Big Data experts
• International projects
• Possibility of conducting workshops and training
• Certifications
• Co-financing sport card
• Co-financing health care
• All equipment needed for work