Job Overview
Location
Zurich, Switzerland
Job Type
Full-time
Category
Software Engineering
Date Posted
May 26, 2026
Full Job Description
đź“‹ Description
- • Build and improve core machine learning components across data, training, evaluation, and inference pipelines for a production AI smart assistant.
- • Fine-tune and adapt neural models as integrated parts of large-scale, real-world systems with strict reliability and latency constraints.
- • Implement robust evaluation and testing frameworks to understand and quantify model behavior under non-deterministic conditions.
- • Design, build, and maintain data pipelines that ingest and process both real-world user data and synthetic datasets for model training and validation.
- • Debug production ML issues including performance degradation, inference failures, and model drift in live systems.
- • Ship iterative improvements to ML systems based on real user feedback and measurable operational metrics.
- • Collaborate closely with senior ML engineers and cross-functional product teams to align technical execution with product goals.
- • Operate under real production constraints including cost efficiency, safety, scalability, and system reliability.
- • Develop production-quality Python code using PyTorch or JAX to support end-to-end ML workflows.
- • Work with GPU-based production ML systems to optimize inference speed, memory usage, and throughput.
- • Identify root causes of model failures and implement systemic fixes to prevent recurrence.
- • Ensure training loops, evaluation metrics, and inference systems are reproducible, maintainable, and well-documented.
- • Drive model iterations using real-world signals rather than theoretical benchmarks alone.
- • Contribute to a high-talent-density team that values collective decision-making, rapid iteration, and independent execution.
- • Balance shipping high-quality work with continuous learning from live system behavior and user interactions.
- • Participate in an interview process consisting of 3–4 virtual or onsite technical interviews evaluated by engineering team members.
- • Join a team focused on delivering a magical, practical AI product that brings intelligent assistance to billions of everyday users.
🎯 Requirements
- • Strong foundations in machine learning and modern neural architectures.
- • Hands-on experience training, fine-tuning, or deploying ML models in production environments.
- • Comfortable writing production-quality Python code and rapidly learning new tools.
- • Curious, coachable, and eager to learn from real-world systems in production.
- • Able to work through ambiguity with guidance and grow ownership over time.
- • Bias toward shipping, iteration, and continuous improvement.
🏖️ Benefits
- • Work on a high-impact AI product designed to bring practical intelligence to everyday users.
- • Collaborate with a small, world-class team that values talent density and independent execution.
- • Receive prompt feedback and decisions throughout the interview process.
- • Be part of a team building a truly magical AI product with global reach.
Skills & Technologies
About Bjak Sdn. Bhd.
Bjak operates Malaysia’s largest digital auto-insurance marketplace, enabling instant price comparison and online purchase of motor coverage from leading insurers. The platform uses proprietary technology to simplify complex tariffs, deliver personalised quotes and e-policy issuance within minutes, eliminating paperwork and agent visits. Licensed by Bank Negara Malaysia, Bjak also offers road-tax renewal, accident assistance and claims support, serving millions of drivers nationwide while partnering with insurers to increase digital distribution efficiency and customer reach.
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