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AI Engineer ; Remote

Remote / Online - Candidates ideally in
Turkey (Türkiye)
Listing for: Sezzle
Remote/Work from Home position
Listed on 2026-04-22
Job specializations:
  • Software Development
    AI Engineer, Cloud Engineer - Software, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 150000 - 300000 TRY Yearly TRY 150000.00 300000.00 YEAR
Job Description & How to Apply Below
Position: AI Engineer I (Remote)

Salary range: 2,500 - 3,333 USD per month (Gross in USD)

About Sezzle

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting‑edge tech with seamless, interest‑free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values.

As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey.

About the Role

We are seeking a talented and motivated AI Engineer I on the Applied AI team. This role presents an exciting opportunity to thrive in a dynamic, fast‑paced environment within a rapidly growing team, with strong prospects for continued growth and increased ownership. As an AI Engineer I, you will contribute to the development of platforms and systems that power Sezzle’s AI‑driven capabilities, including building AI‑powered features, developing intelligent automation and agentic systems, and embedding AI solutions into customer‑facing products, internal tools, and operational workflows.

What

You’ll Do
  • Contribute to the design and development of AI‑powered platforms and systems, working alongside senior engineers on complex initiatives.
  • Own end‑to‑end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
  • Build AI‑driven features, intelligent automation, and agentic systems that enhance customer experiences and improve team productivity.
  • Embed AI capabilities into existing team workflows, products, and processes, ensuring solutions integrate naturally.
  • Integrate AI capabilities into customer‑facing products, internal tools, and operational workflows.
  • Build full‑stack components spanning backend services, APIs, data layers, and frontend interfaces.
  • Translate business and operational problems into maintainable, AI‑enabled technical solutions with guidance from senior team members.
  • Apply system thinking to ensure reliability, performance, and security across platforms.
  • Collaborate with engineers, teams, and stakeholders across the company to understand requirements and deliver impactful solutions.
  • Participate in production support and incident response for team‑owned systems, learning operational best practices.
  • Engage in code reviews and knowledge sharing to continuously improve skills and contribute to team growth.
What We’ll Look For
  • 1–3 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
  • Hands‑on experience designing, building, and shipping AI‑powered systems into production environments.
  • Strong proficiency in Python, SQL, and frontend frameworks such as React.
  • Proven experience designing and owning production‑grade full‑stack systems.
  • Experience working with distributed systems, internal platforms, or complex data workflows.
  • Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.
Preferred Qualifications
  • Exposure to building AI‑powered platforms or products, including contributing to architectural decisions.
  • Foundational knowledge of core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, and model evaluation.
  • Familiarity with transformer architectures (BERT, GPT, etc.) and basic understanding of attention mechanisms, tokenization, and fine‑tuning concepts.
  • Exposure to embeddings and vector representations, including text embeddings and similarity search concepts; interest in vector databases (Pinecone, Weaviate, pgvector, or similar).
  • Familiarity with NLP techniques such as text classification, named entity recognition, or semantic search.
  • Familiarity with real‑world agentic frameworks workflow engines (e.g., in-house automation platforms, Lang Chain/Graph, n8n, Make, or similar), with a solid understanding of how they work under the hood.
  • Experience…
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