Applied AI Engineer
BJAK
full-time
Posted on:
Location Type: Hybrid
Location: United States
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About the role
- 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
- Collaborate effectively with engineers, product, and research teams to deliver reliable ML-powered features.
Requirements
- 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
- A proactive AI system that understands context across conversations, plans actions, and carries work forward over time
- Work closely with product and engineering to translate ambiguous problems into working systems
- Join small, world-class teams that make decisions collectively and strike a balance between shipping high-quality work and learning.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningneural network architecturestraining ML modelsfine-tuning ML modelsdeploying ML modelsproduction-quality codeevaluation frameworksdebuggingoptimizationfull stack development
Soft Skills
problem-solvingcollaborationiterationcontinuous improvementadaptability