We are looking for a Senior Machine Learning (Cloud Data/MLOps) Engineer to join an engineering team in this fast-growing scale-up.
You can now RELOCATE to one of the best countries for ex-pats: the living standard is high and living costs are much lower than in Western Europe! This is a great location if you’d like to travel around Europe as well.
Would you like to work at one of the leading TravelTech companies in Central Europe?
Our client provides innovative TravelTech solutions for customers and businesses. Their unique online search engine allows users to combine transportation from carriers that normally do not cooperate.
Travel itineraries allow users to combine flights and ground transportation from over 800 carriers.
They just closed €100,000,000.00 funding round and are poised to grow above and beyond!
- Deploy and maintain machine learning models
- Write ML algorithms and get AI to production to actually have an impact on our product
- Identify weak spots, refactor code that needs it during development
- Optimize code and usage of 3rd party services for speed and cost-effectiveness
- Regularly update and clearly communicate with the team about your progress and struggles on call / slack duty
- 2+ years of full-time professional experience in a similar position
- Experience with ML platforms like Databricks, Vertex AI or similar
- Fluent English
Ideal Candidate Profile:
- Experience with orchestration tools (Airflow best fit). Experience in big data processing engines – Apache Spark, Apache Beam and its cloud runners Dataproc/Dataflow – welcomed
- Experience with MLOps frameworks like MLFlow, TensorFlow or similar strongly preferred
- Knowledge of ML/AI algorithms like OLS and Gradient Descent and their application from linear regression to deep neural networks
- Working with batch and real-time data processing
- Coding skills – Python or Scala (we use both though)
- Cloud Knowledge – Google Cloud (best fit) – experience with BigQuery big advantage, AWS, Azure
- BS/MS in Computer Science or a related field (ideal)
- It feels like a startup within a scale-up company!
- Fast-paced & ambitious growing company… which means a lot of data to process!
- Great team spirit and autonomy to deliver results the way you prefer.
- No blame culture
- “All of us make mistakes and we try to ensure that we learn from that and do not repeat the same mistake in the future. Each major incident is addressed in the postmortem to improve the process.”
- Fail fast, learn fast
- “When delivering a new business feature, we implement the MVP version in the first place to prove the business case. Afterward, we aim for a proper technical solution. We try to avoid nitpicking.”
- “Our aim is to provide you with enough context so that you can act independently. Most of our workload is organized in Jira but you aren’t limited to strictly defined tasks. We encourage you to come up with your own solution to the problems and will support you in cross-team cooperation. We don’t like micromanagement.”
- No question is stupid
- “We promote a safe environment within the team to make sure you will feel comfortable to ask any questions or raise any concerns since day 1.”
- Help other teammates
- “As no one is a specialist for all directions, we believe that knowledge sharing is the key to the team’s success. We encourage you to ask questions and we support you to pass technical knowledge and domain knowledge on more junior team members. We help each other if needed.”
- Releases & deployment process
- “We rely on fully automated CI/CD pipelines that allow us to release/rollback versions as often as we need – with a single click. We like canary releases.”
- Python 3.6 – 3.9
- Flask, Falcon, FastAPI, Connexion, Celery
- Yarn workspaces (monorepo-like setup)
- GraphQL, Node.js
- PostgreSQL, Redis, SQLAlchemy
- GCP, AWS, K8s, Docker, Datadog, Gitlab (including GItlab pipelines)
- React, Redux, Relay, Next.js, Flow, TypeScript, Styled-components, Babel, Webpack, Gulp, Storybook
- Cypress E2E testing and Jest with React Testing Library
- Agile working processes: both Scrum, Kanban and even Scrumban in place.
- Core backend languages are Python & Golang
- Code maintenance using GitLab and deploy using its CI/CD
- Deployments are running on Kubernetes (GKE)
- GCP products (Pub/Sub, Google Cloud Storage, BigQuery, CloudSQL)
- NoSQL databases – Redis, ElasticSearch
- To ensure nothing goes wrong we monitor our service using Sentry & Datadog
- Very flexible, but also value Face-to-face collaboration as it creates great team spirit, a feeling of belonging, and keeps mental health in check.
- Flexible working schedule
- Start date as soon as you can
- Valuable Stock options
- Hardware from Apple or Microsoft based on your preferences
- Quarterly bonuses
- VIP Medical Care
- 20+5 days vacation/year
- Sick days
- Meal vouchers, Cafeteria program, Multisport card
- Visa supported
- Relocation package 1.5x to 2.0x first month’s salary to cover initial expenses.
If interested, please share your CV at firstname.lastname@example.org.