Artificial Intelligence Engineer

Company: DeepAdapt

Location: Remote, Türkiye

Company HQ: Irvine, California, U.S.A.

Role Type: Contract

Compensation: Contract-based, with potential equity for the right founding-level contributor

DeepAdapt is building frontier AI infrastructure focused on adaptive runtime intelligence. We are developing systems that can learn, improve, and optimize behavior over time — not just orchestrate existing tools.

We are a small, ambitious team looking for a deeply technical AI engineer who wants to help build the core intelligence layer of the product from the ground up.

This is not a role for someone who only connects APIs, builds basic agents, or relies on prompting alone. We are looking for someone who understands how models learn, how to train and fine-tune them, and how to turn research ideas into production systems.

We are seeking an Artificial Intelligence Engineer for a remote contract position open to candidates based in Türkiye.

You will design, train, fine-tune, evaluate, and deploy AI models that power our runtime intelligence layer. You will work on algorithms for pattern recognition, adaptive learning, and continual improvement, while helping move ideas from research and prototype into real production systems.

You should be comfortable working hands-on with modern machine learning frameworks, production code, and AI coding tools such as Cursor or GitHub Copilot. You will work directly with the founders and a small multidisciplinary team where your technical decisions will shape the product.

• Design, train, fine-tune, and evaluate AI models for runtime intelligence systems
• Build and improve algorithms for pattern recognition, adaptation, and continual learning
• Develop systems that can learn from data, feedback, and operational signals
• Take ideas from research to prototype to production
• Deploy and optimize models in real-world environments
• Measure and improve model accuracy, latency, reliability, and cost
• Build clean, production-ready software around AI systems
• Collaborate directly with founders on core product and technical direction
• Use modern AI coding tools to move quickly from concept to working implementation

We are looking for a strong computer scientist and hands-on AI engineer who can build real systems.

You should have a deep understanding of how machine learning models learn, including training loops, loss functions, optimization, evaluation, overfitting, generalization, and model improvement. You should have practical experience training or fine-tuning models, not only using prebuilt APIs.

The ideal candidate is fast, curious, technical, and comfortable with ambiguity. You should think like an owner, care about product impact, and want meaningful involvement in building a company from an early stage.

• Strong foundation in Computer Science and Software Engineering
• Hands-on experience training, fine-tuning, and evaluating machine learning or deep learning models
• Practical knowledge of neural networks and modern ML frameworks such as PyTorch, TensorFlow, JAX, or Hugging Face
• Experience with pattern recognition, classification, prediction, anomaly detection, NLP, computer vision, recommendation systems, or related ML areas
• Ability to build production-quality software, not just experiments
• Understanding of model evaluation, data quality, performance measurement, and failure analysis
• Experience deploying or integrating AI models into production systems
• Strong Python skills and familiarity with modern development workflows
• Fluency using AI coding editors such as Cursor, GitHub Copilot, or similar tools
• Strong problem-solving skills and ability to work independently in a fast-moving remote environment

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
• Experience with GPU optimization, distributed training, CUDA, TensorRT, ONNX, Triton, vLLM, or high-performance AI infrastructure
• Experience with continual learning, adaptive learning systems, reinforcement learning, or online learning
• Experience building agentic AI systems
• Experience with MLOps, model monitoring, evaluation pipelines, and production inference optimization
• Startup or founding-team experience

• You have personally trained or fine-tuned neural networks
• You can explain how a model learns, fails, improves, and generalizes
• You have shipped ML or AI systems into production
• You are comfortable owning technical decisions end to end
• You care about both research quality and production reliability
• You move fast without sacrificing engineering discipline
• You want to build core technology, not just use existing tools
• You are excited by early-stage ambiguity and ownership

• Your AI experience is mainly prompt engineering or API orchestration
• You have only built simple LangChain or agent demos
• You have not worked directly with datasets, model training, fine-tuning, or evaluation
• You prefer well-defined corporate structures over early-stage speed and ambiguity
• You are not comfortable owning production outcomes

• Potential equity in the company for the right founding-level contributor
• Meaningful ownership in the technology you help create
• Founding-level impact on the core product
• Remote-first work from anywhere in Türkiye
• Direct collaboration with founders
• A small, ambitious team building frontier AI infrastructure
• The opportunity to work on adaptive AI systems beyond basic agent orchestration