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BJAK

Applied AI Engineer

BJAK

Applied AI Engineer developing AI features for real-world insurance workflows. Collaborating in a fully remote global team to optimize insurance management processes.

Posted 6/28/2026full-timeRemote • 🇨🇭 SwitzerlandMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in building and shipping AI features, with a strong foundation in machine learning and modern neural network architectures. Proficient in developing production-quality code and optimizing systems for performance and reliability.

Highest-signal resume keywords
Machine LearningNeural Network ArchitecturesModel Training and Fine-TuningProduction-Quality CodeProblem-Solving in Ambiguous Environments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Machine LearningNeural Network ArchitecturesModel TrainingModel Fine-TuningModel DeploymentProduction-Quality CodeSystem OptimizationEvaluation FrameworksDebuggingUser Experience Design
Soft Skills
Problem-SolvingAdaptabilityCollaborationContinuous ImprovementIteration
Industry Keywords
AI FeaturesModel OutputsLatency OptimizationCost OptimizationProduction ReliabilityAgent WorkflowsOrchestration

About the role

Key responsibilities & impact
  • Build and ship AI features end-to-end (model → system → user experience)
  • Design and iterate on prompts, tools, memory, and agent workflows
  • Turn raw model outputs into structured, reliable, and predictable behaviors
  • Debug issues across the full stack (model, orchestration, infra, UX)
  • Optimize for latency, cost, and production reliability
  • Develop lightweight evaluation frameworks to measure real-world performance
  • Work closely with product and engineering to translate ambiguous problems into working systems

Requirements

What you’ll need
  • Strong foundation in machine learning and modern neural network architectures
  • Hands-on experience with training, fine-tuning, or deploying ML models
  • Ability to write clean, production-quality code
  • Comfort working across abstraction layers (model → infra → product)
  • Strong problem-solving skills in ambiguous, fast-moving environments
  • Bias toward shipping, iteration, and continuous improvement

Benefits

Comp & perks
  • Our product focuses on achieving high reliability for long-running workflows
  • Collaborates effectively with engineers, product, and research teams to deliver reliable ML-powered features
  • Iterations on models and systems are driven by real-world signals and measurable improvements