Python Developer
Work Mode: Hybrid (3 days a week from the office)
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Experience: 5+ years
As a Software Engineer you will
Join a world-class team of Quantum and AI experts with an extensive track record in both
academia and industry.
Work with Fortune-500 customers from government and private sectors.
Contribute to our groundbreaking compressing tool
Tackle high value open problems from industry.
Take on technical leadership and work together with software and DevOps engineers as
well as our machine learning and quantum experts to industrialize the company’s core
technologies
Required Qualifications
Software Engineering
Proven track record designing and implementing production-grade software running under real load
Solid grasp of clean architecture, separation of concerns, SOLID principles, testability and maintainability as first-class concerns
Experience with software design patterns and sound judgment on when (and when not) to apply them
Understands service-level architecture: API design, layered architectures, event-driven patterns, and how to structure code that outlives its author
Good grounding in software security principles: input validation, secret management, dependency auditing, container hardening, secure API design
Experience with containerized deployment fundamentals (Docker) and CI/CD concepts
Python coding experience.
Soft Skills
Proposes solutions to unfamiliar problems: research first, presents alternatives with trade-offs, doesn’t wait to be told the answerBreaks complex cross-repo issues into sequenced, followable steps
Acts as developer, mentor, and reviewer in the same sprint – writes production code, gives PR feedback to mid-level engineers, upholds review standards
Communicates technical risk clearly – surfaces blockers early with context
Comfortable with ambiguity and working under pressure; self-directed
Collaborates cross-functionally (MLOps, DevOps, Platform Engineering) without needing a
manager to mediate
Preferred Qualifications
ML & LLM Exposure
Exposure to PyTorch and/or HuggingFace Transformers (fine-tuning, inference, compression
workflows)
Familiarity with ML infra concepts: training orchestration, experiment tracking, GPU job
Awareness of LLM techniques: distillation, quantization, pruning, inference serving
Some exposure to GPU-aware engineering (CUDA, mixed precision, multi-GPU) is a plus
Tooling & Infrastructure
ECR, ArgoCD/Helm, structured CI/CD pipelines beyond basic Docker
Async long-running job orchestration patterns
Variable performance bonus.Signing bonus.
Relocation package (if applicable).
Flexible remuneration: hospitality and public transportation.
Eligibility for educational budget according to internal policy. xqbhyrx
Flexible working hours.
Language classes and discounted lunch options