[Hiring] Expert Artificial Intelligence/Machine Learning Engineer @Ciklum

Role Description

As an Expert Artificial Intelligence/Machine Learning Engineer, become a part of a cross-functional development team engineering experiences of tomorrow. Together, we will work on the project Phase 2 Customer Expansion: Design, build, and deploy the next-generation, customer-facing RemitIntel Application.

• System Architecture: Lead the end-to-end design and deployment of scalable AI systems, specifically focusing on LLM-driven applications, Multi-Agent systems, and Retrieval-Augmented Generation (RAG).
• Technical Governance: Serve as the primary technical authority for clients, ensuring all AI solutions meet enterprise-grade standards for performance, security, and reliability.
• Hands-on Development: Drive the full development lifecycle from initial experimentation and rapid prototyping to production-grade implementation.
• Strategic Presales: Act as a Technical SME during discovery phases, translating business challenges into viable AI roadmaps and engineering solutions.
• Operational Excellence (LLMOps): Establish best practices for CI/CD, model observability, and automated evaluation to ensure continuous improvement of deployed models.
• Cross-Functional Leadership: Collaborate with Product and Data teams to align technical delivery with business KPIs, while mentoring junior engineers through code reviews and internal workshops.

Qualifications

• 8+ years in software, data, or AI engineering, featuring at least 3–4 years of direct experience architecting and implementing AI/ML solutions.
• BSc, MSc, or PhD in Computer Science, Mathematics, or a related quantitative field, with a deep command of probability, statistics, and machine learning optimization.
• Proven track record in building and deploying advanced AI systems, including Large Language Models (LLMs), Multimodal architectures, RAG, and Agentic systems.
• Expert-level Python skills and mastery of frameworks such as PyTorch, TensorFlow, LangChain, and Hugging Face.
• Hands-on experience with cloud-native AI stacks (AWS SageMaker, Azure ML, or GCP Vertex AI) and enterprise data platforms.
• Proficiency in modern AI engineering practices, including CI/CD, model versioning, observability, and evaluation methodologies (e.g., CRISP-ML(Q)).
• Experience architecting end-to-end pipelines—from data ingestion and API integration to production-grade model serving and optimization.
• Ability to handle diverse modalities (text, image, audio) and complex scenarios such as time-series forecasting and anomaly detection.
• Strong understanding of security, data privacy (GDPR/CCPA), and ethical AI frameworks within enterprise system design.

Benefits

• Work alongside top professionals in a friendly, open-door environment.
• Take on large-scale projects with a global impact and expand your expertise.
• Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications.
• Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies.
• Enjoy radical flexibility – work remotely or from an office, your choice.
• Medical subscription to Regina Maria, meal tickets of 40 ron net/day worked.