Python
Software Engineer
Join our team as a Software Engineer (Python) to build scalable backend systems, APIs, and automation tools that support high-performance data workflows and web applications.
Engineer intelligent systems at scale—shape the future of AI with Python, MLOps, and Kubernetes.
We seek a Python Software Engineer passionate about AI and Machine Learning to build high-impact, production-grade ML systems. You’ll work at the frontier of applied AI—designing scalable pipelines, automating model lifecycles, and deploying intelligent services in dynamic cloud environments. Your code will drive real-world decisions in precision medicine, logistics, fintech, and robotics.

Design & development
- Develop modular, high-performance Python services powering real-time inference, training, and feature computation.
- Architect ML pipelines from data preparation to model deployment using Airflow, DVC, or MLflow.
- Build REST/gRPC APIs and services that expose ML capabilities with Fast API, Flask, or Ray Serve.
- Implement batch and streaming data pipelines using Pandas, Spark, or Kafka with data validation and monitoring.
- Integrate tightly with Kubernetes-based infrastructure for containerized, autoscaling ML workflows.

Optimization & innovation
- Automate retraining, evaluation, and deployment via CI/CD and GitOps pipelines.
- Apply techniques like model versioning, drift detection, and canary deployments.
- Optimize ML models’ and services’ memory and latency through quantization or async processing.
- Leverage GPU acceleration, distributed training, and feature stores for scalable ML systems.
- Enhance model observability with Prometheus, OTEL, and custom model metrics.

Collaboration & leadership
- Partner with data scientists and ML researchers to move models from notebooks to production.
- Collaborate with security, platform, and data teams to ensure robust, compliant, and secure ML deployments.
- Contribute to open-source ML tooling and mentor engineers on MLOps best practices.
- Participate in design reviews, knowledge-sharing sessions, and interdisciplinary innovation sprints.

Our engineering culture and workflow principles
Remote desktop
Cloud playground
Deploy by commit
Automated tests
Partially remote
State-of-the-art
Scientific
Always learning
Organized
Apply to us
This is where your journey starts to something new. Just you and your ideas, implemented in your way in a stack that serves your convenience. We would be happy to hear from you!
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