We are an innovative AI startup focused on developing systems that automatically detect, understand, and repair software defects. Our goal is to minimize the time engineers spend troubleshooting bugs and to advance towards self-healing software. We are seeking a proactive AI Engineer who excels in both writing production code and conducting experiments, training models, and enhancing system performance. This position involves working with transformer-based models, graph-based reasoning, and practical optimization throughout the machine learning lifecycle.

The Role

You will be responsible for building and deploying machine learning systems aimed at code comprehension, defect detection, root-cause analysis, and automated program repair. Your day-to-day tasks will include:

• Designing, fine-tuning, evaluating, and enhancing transformer-based models applied to source code, logs, traces, and technical documentation.
• Utilizing graph-based representations and implementing Graph Neural Network (GNN) approaches where they provide measurable benefits.
• Managing the entire model lifecycle, from data preparation and experimentation to deployment, monitoring, and iteration.
• Optimizing training and inference for model quality, latency, memory usage, throughput, and cloud costs.
• Transforming research concepts into reliable product features.

Requirements

• 5+ years of professional experience with Python, machine learning, and deep learning.
• 3+ years of practical experience with transformer models in real-world applications, ideally beyond basic API usage.
• 2+ years of experience with AWS in production settings.
• Proven experience in building end-to-end machine learning systems, including data pipelines, training workflows, model serving, evaluation, and monitoring.
• Strong understanding of experimentation, model debugging, and production reliability.
• Professional English communication skills.

Nice to Have

• PhD in Computer Science, Machine Learning, or a related field.
• Experience with MLOps platforms and production ML tools.
• Contributions to research, open source projects, or technically challenging production systems.

What We Offer

• A remote-friendly culture with significant ownership and real product impact.
• The opportunity to tackle a genuinely challenging problem at the cutting edge of AI and software engineering.
• Flexible working arrangements and the chance to influence core technology from the ground up.