Senior MLOps Engineer

GetInData sp. z o.o. sp. k.; Warszawa; On-site; Full time

Job summary

Firma GetInData, część Xebia, szuka MLOps Engineera do optymalizacji procesów uczenia maszynowego. Osoba na tym stanowisku będzie odpowiedzialna za automatyzację workflow, wdrażanie pipelines CI/CD i monitorowanie modeli w chmurze. Jeśli masz doświadczenie w GCP, Pythonie i CI/CD oraz chcesz rozwijać swoją karierę w dziedzinie Data & AI, to jest miejsce dla Ciebie.

Benefits

Możliwość pracy z biura w Warszawie

Szansa na naukę od najlepszych ekspertów Big Data

Międzynarodowe projekty

Możliwość prowadzenia warsztatów i szkoleń

Qualifications

• Znajomość przynajmniej jednego narzędzia do orkiestracji i harmonogramowania.
• Doświadczenie na platformach GCP i BigQuery.
• Praktyczna znajomość Kubeflow i Vertex AI.

Responsibilities

• Tworzenie i zarządzanie zasobami GCP i K8s.
• Konfiguracja i zarządzanie Kubeflow oraz jego komponentami.
• Praca z danymi i infrastrukturą ML w środowisku GCP.

Skills

Python

Bash

PowerShell

Airflow

MLFlow

Docker

Kubernetes

Job description

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 DATA Pill 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 Engineer is 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 also covers various ML algorithms and distributed training in environments like Spark, PyTorch, TensorFlow, Dask, and Ray. MLOps Engineers are essential for optimizing and maintaining efficient ML processes in organizations.

Responsibilities

Creating, configuring, and managing GCP and K8s resources

Managing Kubeflow and/or Vertex AI and its various components

Collaborating and contributing to various GitHub repositories: infrastructure, pipelines, Python apps, and libraries

Containerization and orchestration of Python DS/ML applications: Data/Airflow and ML/Kubeflow pipelines

Setting up logging, monitoring, and alerting

Scaling, configuring, and reconfiguring all the components based on metrics

Working with Data (BigQuery, GCS, Airflow), ML (Kubeflow/Vertex), and GCP infrastructure

Streamlining processes and making the Data Scientists' work more effective

Job requirements

Proficiency in Python, as well as experience with scripting languages like Bash or PowerShell

Knowledge of at least one orchestration and scheduling tool, for example, Airflow, Prefect, Dagster, etc

Understanding of ML algorithms and distributed training, e.g., Spark / PyTorch / TensorFlow / Dask / Ray

Experience with GCP andBigQuery DWH platform

Hands-on experience with Kubeflow andVertex AI

Familiarity with tools like MLFlow from the operations perspective

Experience with containerization technologies like Docker and knowledge of container orchestration platforms like Kubernetes

Understanding of continuous integration and continuous deployment (CI/CD) practices

Ability to identify and analyze problems in the workflow (in all the teams involved), propose solutions, and navigate complex technical challenges

We offer

Salary: 160 - 200 PLN net + VAT/h B2B (depending on knowledge and experience)

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