Senior AI/ML Engineer to $5000

CrunchCode — міжнародна сервісна ІТ-компанія з досвідом близько 7 років у розробці вебсервісів і вебзастосунків. Ми працюємо у форматах staff augmentation (outstaff) та outsourcing і підключаємо спеціалістів до проєктів клієнтів у довгостроковій моделі співпраці.

Ми працюємо переважно з проєктами в доменах логістики (включно з last mile),e-commerce, fintech та банкінгу, а також enterprise-рішеннями.
Для нас важливо, щоб проєкт був “чистим” і зрозумілим з точки зору етики та цінності для користувачів.

Ми принципово не беремо проєкти, пов’язані з:
● gambling / гемблінгом,
● adult-контентом та порнографією,
● шахрайством або будь-якою розробкою, що спрямована на обман чи маніпуляції.

What We Offer:
● Fully remote work
● Long-term, stable project
● High level of autonomy and trust
● Minimal bureaucracy
● Direct impact on business-critical logistics systems
● Long-term engagement, not a short-term contract.

Required: 
We’re looking for an Applied AI Engineer who combines strong ML fundamentals with the discipline of improving production AI systems through metrics, evaluation, and iteration. 
A large part of the role involves:
diagnosing failures in agent workflows
designing evaluation metrics and KPIs
improving system prompts and agent behavior
running structured experiments and measuring impact
You won’t be working in isolation on research projects - you’ll be improving systems that real users depend on.

Project Overview:
You’ll work on improving production AI systems through evaluation, experimentation, and system design.

Requirements (Must-have):
1. Strong AI/ML fundamentals. You understand the theory behind what you build and can choose appropriate methods for a problem.
Examples:
evaluation metrics (precision/recall/F1/etc.)
ranking and recommendation concepts
embeddings and similarity
experimentation methodology
Not required:
academic publications
advanced theoretical math
large-scale model training experience
2. Evaluation-driven mindset You:
think in metrics and baselines
design experiments instead of guessing
measure system improvements quantitatively
debug failures methodically
This is the most important signal for the role.

3. Experience with LLM systems You’ve worked with:
prompt design
agent workflows
evaluation of LLM outputs
production LLM integrations
4. Ability to ship production systems You can:
turn ideas into working systems
iterate based on results
balance exploration with delivery
5. Programming ability. You’re comfortable writing production code in at least one language (Python, Go, or similar) and learning others when needed.

Responsibilities:
- AI evaluation and KPI design — ~30%
- Prompt and agent system design — ~30%
- ML systems (recommendation, optimization, etc.) — ~30%
- Engineering integration — ~10%
 

Nice to Have:
- Experience improving an AI system after deployment
- Recommendation systems or ranking experience
- Optimization or constraint-based systems
- Computer vision experience
- Experience building evaluation frameworks
- Golang experience
- Startup or small-team engineering experience
- This role may not be a fit if
- You are looking for a research focused role without production deployment
- You rely heavily on frameworks without understanding fundamentals
- You’re uncomfortable working with partially-defined problems
- You prefer narrow specialization over product ownership

Hiring Process:
- Intro call
- Technical discussion (focused on real experience)
- Offer
Start: ASAP