ai engineer in fintech

Life at Bir provides financial services.

• Lead AI and machine learning projects from problem understanding through development and deployment;
• Prepare, clean, structure, and label data for AI systems and analyze datasets to identify useful patterns;
• Design, develop, and improve AI and machine learning solutions for different use cases;
• Build LLM, RAG, and agent-based AI projects;
• Integrate LLM APIs into products and internal tools;
• Improve AI solution quality, performance, and reliability;
• Fine-tune, evaluate, and optimize models on custom datasets;
• Build and improve speech-to-text and text-to-speech features and pipelines;
• Deploy, monitor, and troubleshoot AI features in production, considering reliability, latency, and cost;
• Review and improve existing models, pipelines, and AI systems for reliability and efficiency;
• Establish and promote best practices for model governance and performance monitoring;
• Collaborate with data engineers, ML engineers, and product teams to deliver AI solutions;
• Provide technical guidance and support to junior and mid-level team members;
• Keep up with relevant AI developments and identify practical opportunities to apply new technologies.

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field, or equivalent practical experience;
• 4+ Years of hands-on experience in AI/ML engineering, applied AI, or data science;
• Strong programming skills in Python;
• Strong understanding of machine learning and deep learning, including model development, optimization, and evaluation;
• Strong data skills, including SQL and experience cleaning, structuring, labeling, and analyzing data for high-quality AI datasets;
• Experience working with large datasets and building AI/ML pipelines;
• Hands-on experience developing AI solutions with NLP, LLMs, and generative AI, including integrating LLM APIs into real applications;
• Hands-on experience fine-tuning and evaluating models;
• Practical experience with prompt engineering, RAG, embeddings, vector databases, and agentic AI;
• Experience building and consuming APIs, including REST, SDKs, authentication, rate limits, and error handling;
• Experience deploying and running AI services in production, including on-premise environments, with understanding of MLOps, model deployment, monitoring, and versioning;
• Strong communication skills and fluent Azerbaijani;
• Good English;
• Nice to have: experience with speech technologies such as ASR and TTS, familiarity with cloud platforms and Docker and Kubernetes, experience mentoring or technically guiding junior and mid-level team members.

• No conditions specified