AI/ML Engineer

AI / ML Engineers design, build, and operate machine and deep learning solutions that drive intelligent automation and data-driven decision-making across the organization. AI Engineers are responsible for deploying production-ready models, integrating them into scalable systems, and ensuring their reliability and performance through robust ML Ops practices. The incumbent will oversee the full machine learning lifecycle-including data preparation, model development, validation, deployment, monitoring, and retraining-using modern orchestration, CI/CD tools, and cloud platforms (e.g., Microsoft Azure). A key focus of this role includes advancing the organization's capabilities in Natural Language Processing (NLP) and Generative AI, such as developing and fine-tuning Large Language Model-based chatbots, implementing text classification and extraction pipelines, and ensuring linguistic models align with business objectives and compliance requirements. The AI Engineer collaborates closely with data scientists, software engineers, and infrastructure teams to ensure AI solutions are secure, maintainable, and aligned with enterprise architecture and strategic goals., This role encompasses all aspects of artificial intelligence R&D and ML Ops.

Daily activities include:

· Designing and implementing machine and deep learning-based AI & NLP workflows, algorithms and solutions in alignment with the business needs.

· Deliver scalable and maintainable solution using the latest cutting-edge technology.

· Identification and evaluation of strategic innovations (concepts, tools/languages, technologies, services) in the field of AI, NLP and deep learning.

· Constant personal development in new technologies.

Scope of Work / Duties of Consultant:

· R&D of AI-based workflows, algorithms and solutions.

· Work in public cloud environments (AWS, Azure, or Google) as well as on-premises.

· Work with GPU-based backends and cloud platforms.

· Install and configure AI and ML Ops systems to ensure functionality.

· Analyze structural requirements for new software and applications.

· Evaluate and analyze complex AI solutions and result collections.

· Supervise and develop AI and ML Ops processes.

· Design complex AI and ML Ops pipelines and workflows.

· Present technical concepts to non-technical audiences.

· Improve and enhance existing AI solutions. Handover AI solutions to clients or colleagues.

· Improve performance by conducting tests, troubleshooting and integrating new elements.

· Define and prototype basic demonstrations for AI solutions and workflows.

Do you have a Master's degree?, · +5 years' experience as a researcher or engineer in AI, NLP and deep learning-related tasks. Having experience in an "industry" environment is a plus

· +5 years' experience with text classification, information extraction, sequence labelling, model selection, evaluation, and result analysis.

· +3 years' experience of multi-class and multi-task classification; LLMs; dialogue systems / chatbots, Retrieval Augmented Generation (RAG), Agentic AI; adversarial architectures; online learning methodologies; model compression (pruning, quantization, distillation…); AI model serving for production settings.

· +3 years' experience with Cloud platforms (e.g., Azure); API and web service development in python; web app development in Python; agile methodologies; containers and their orchestration; cloud computing solutions.

· Presence in the AI community, e.g., with experience in publishing research material., · The resource MUST have the following skills and experience:

· Advanced knowledge of the following technologies: python, bash, git, ssh, and linux terminal.

· Advanced knowledge of one of the following deep learning backends: keras, tensorflow, pytorch, or JAX.

· Advanced knowledge of one of the following solutions for AI model serving: NVIDIA Triton Inference Server; vLLM; or Ollama.

· Knowledge of one of the following web app development solutions: Dash, Flask or Streamlit.

· Knowledge of Microsoft Azure DevOps Services for R&D and AI model / solution deployments, including ML and Copilot Studio.

· Knowledge of docker and Kubernetes for R&D and production settings.

The resource SHOULD have the following skills and experience:

· Knowledge of the following platforms: AWS (e.g., Sagemaker & bedrock) and GCP (e.g., Vertex AI) in the framework of AI and MLOps.

· Knowledge of computer vision and speech processing.

· Knowledge of MLflow and Kubeflow.

· Knowledge of Java, C and C++ programming languages.

· Thorough knowledge of Microsoft Office Suite products.

· Good communication skills and customer relationship skills.

· Knowledge of public cloud environment configuration & management for AI and cloud version control processes.

· Knowledge of Agile development methodology and concepts.

· Knowledge of a second language would be an asset.

Required Soft Skills:

• Excellent written and verbal communication skills, interpersonal and collaborative skills

• High degree of initiative, proactive and ability to work with little supervision

• Ability to deliver quality results

• Excellent communication, facilitation, and interpersonal skills with the ability to convey complex topics through effective documentation as well as presentations to all levels of the organization

• Excellent organizational skills, reporting and documenting

• Excellent written and spoken English

• Ability to effectively collaborate with teams in an international, multicultural, multi-disciplinary environment working under different time-zones

Desirable certifications:

• Bachelor's degree in computer science, mathematics, logic, telecommunication technologies, or similar. Master's degree or PhD in natural language processing, artificial intelligence, deep learning, or similar.

• Peer-reviewed scientific publications accepted and published in top conferences or journals. E.g., ACL and EMNLP.