Join our Artificial Intelligence team as a Software Engineer and help us revolutionize marketing with ML-powered solutions! You'll work on cutting-edge technologies, impacting millions of users, and contributing to a product that truly makes a difference. The salary range starts at 3500€ per month, along with restricted stock unites and other benefits. Working in one of our Central European offices or from home on a full-time basis, you'll become a core part of the Engineering Team.
What challenge awaits you?
You'll face the exciting challenge of building and maintaining ML-powered features in a production environment, ensuring they are reliable, scalable, and deliver real value to our users. You'll work alongside a team to overcome the unique challenges of building and running ML models in a SaaS environment, including managing data complexity, optimizing for performance, and ensuring model robustness.
You will cooperate with your teammates, Data Science engineers, and Engineering and Product leaders to speed up ML-powered features' delivery (from ideation to production) by applying principles of continuous discovery, integration, testing, and other techniques from Agile, DevOps, and MLOps mindsets. This will involve building efficient workflows, automating processes, and fostering a culture of collaboration and innovation.
Your job will be to:
- Design & Deliver new features
- Ensure quality and performance of developed solution
- Support and Maintain owned components
a. Design & Deliver new features
- Translate business requirements for ML-powered features into technical specifications and design documents.
- Collaborate with data scientists to ensure new ML features' technical feasibility and scalability.
- Define and develop back-office API endpoints (to configure the features) as well the high-performance serving endpoints.
- Develop and implement ML models, algorithms, and data pipelines to support new features.
- Deploy and monitor new features in production, ensuring seamless integration with existing systems.
b. Ensure quality and performance of developed solution
- Perform rigorous testing and quality assurance of ML models and code, including unit tests, integration tests, and A/B testing.
- Implement monitoring systems and dashboards to track the performance of ML models in production, identify potential issues, and optimize for accuracy and efficiency.
- Contribute to developing and implementing DevOps and MLOps best practices within the team.
c. Support and Maintain owned components
- Maintain end-to-end features, encompassing back-office APIs, models, definitions, and high-performance serving APIs.
- Provide ongoing support and maintenance for existing ML-powered features, including troubleshooting issues, fixing bugs, and implementing enhancements.
- Support our client-facing colleagues in the investigation of possible issues (L3 support).
- Document code, design decisions, and operational procedures to facilitate ongoing maintenance and knowledge sharing.
What technologies and tools does the AI team work with?
- Programming languages - Python
- Google Cloud Platform services - GKE, BigQuery, BigTable, GCS, Dataproc, VertexAI
- Data Storage and Processing - MongoDB, Redis, Spark, TensorFlow
- Software and Tools - Grafana, Sentry, Gitlab, Jira, Productboard, PagerDuty
The owned area encompasses various domains such as Recommendations, Predictions, Contextual bandits, MLOps. Therefore, having experience in these areas would be beneficial. The team also works with large amounts of data and utilizes platforms and algorithms for model training and data processing & ML pipelines. Experience in these areas is highly valued.
Your success story will be:
- In 30 Days: Successfully onboard and contribute to ongoing tasks, demonstrating understanding of the codebase and team processes.
- In 90 Days: Contribute to design discussions and independently deliver high-quality code for assigned features. Participate in investigating and resolving production issues.
- In 180 Days: Independently manage larger tasks, contribute to team improvements, and confidently handle L3 support, investigating and resolving production issues.
You have the following experience and qualities:
- Professional — Proven experience in python engineering, system design, and maintenance in the area of AI/ML-powered features.
- Personal — Demonstrates strong initiative, ability to work within a team, communication skills, and a commitment to continuous learning and improvement.
Professional experience
- Proven experience in Python engineering, with a strong focus on designing and maintaining AI/ML-powered features in production environments.
- Experience with cloud platforms (e.g., GCP, AWS) and relevant services for ML development and deployment.
- Solid understanding of software architecture principles, particularly in the context of building and maintaining scalable and reliable APIs and microservices.
- Experience with version control systems (e.g., Git) and CI/CD pipelines for efficient development and deployment.
- Familiarity with common ML frameworks, libraries, and tools (e.g., TensorFlow, PyTorch, Scikit-learn, etc.) and with ML pipelines/orchestration frameworks (Kubeflow, Airflow, Prefect,... )
Personal qualities
- Demonstrates strong initiative and a proactive approach to problem-solving.
- Excellent communication and collaboration skills, with the ability to work effectively within a team.
- A genuine passion for learning new technologies and keeping up-to-date with the latest advancements in AI/ML.
- A commitment to delivering high-quality work and a dedication to continuous improvement.
