AI Engineer

About the Role

We are representing a partner company seeking an AI Engineer located in Ireland for a fully remote, full-time position. The role focuses on creating scalable, production-grade AI solutions tackling real-world challenges by combining strong foundational machine learning knowledge with practical engineering skills. Candidates will engage with multiple AI domains including large language models (LLMs), natural language processing (NLP), computer vision, and other emerging areas. The work spans data preparation, model development, evaluation, deployment, and managing MLOps pipelines. The role demands both deep technical expertise and the capacity to work autonomously in a rapidly evolving environment, along with the ability to communicate advanced AI concepts clearly to non-technical audiences.

Key Responsibilities

• Design, develop, and launch machine learning and AI systems for scalable real-world applications.
• Create, customize, optimize, and sustain AI models tailored to specific domains.
• Develop and uphold pipelines for data mining, preprocessing, feature engineering, and data labeling.
• Handle large datasets to prepare high-quality data for training and evaluation purposes.
• Apply machine learning techniques across LLMs, NLP, computer vision, and additional AI fields.
• Train, assess, enhance, and iteratively improve ML models based on their performance metrics.
• Design and support deployment and MLOps pipelines to ensure robust production environments.
• Deploy and serve models leveraging cloud services and containerized setups.
• Utilize Docker, Git, and pertinent MLOps tools within collaborative software development workflows.
• Analyze model outcomes, pinpoint limitations, and implement improvements.
• Effectively convey technical findings and progress updates to non-technical stakeholders.

Requirements

• Between 2 to 5 years of practical experience in building and deploying machine learning or AI models in production settings.
• Proficiency in Python programming.
• Hands-on experience with PyTorch and/or TensorFlow frameworks.
• Expertise in designing and architecting customized AI/machine learning models.
• Experience in at least one AI specialization such as LLMs, NLP, or computer vision.
• Deep understanding of supervised and unsupervised learning, deep neural networks, optimization strategies, and model evaluation techniques.
• Familiarity with data preprocessing, feature engineering, data mining, and annotation pipelines.
• Knowledge of MLOps and model deployment tools like MLflow, Kubeflow, or SageMaker.
• Experience working with cloud platforms for training and hosting models, for example, AWS Lambda.
• Experience in Docker-based container deployment of models.
• Comfortable with Git and team-based software development practices.
• Strong analytical thinking, problem-solving, and debugging skills.
• Ability to simplify and communicate complex AI topics to audiences without technical background.
• A curious and adaptable mindset suited to fast-changing work environments.
• Ability to function independently while collaborating effectively across distributed teams.

Compensation and Benefits

• Competitive salary of 4000 EUR.
• Full-time employment status.
• Opportunity to work entirely remotely.
• Engagement with real-world AI and machine learning applications at scale.
• Exposure to advanced AI domains including LLMs, NLP, computer vision, as well as MLOps and cloud technologies.
• Access to modern AI and software engineering practices and tools.
• International and remote working context.

Additional Information

This position is managed by our partner company responsible for application reviews and further recruitment steps. The hiring decision and subsequent process phases such as interviews and assessments are conducted by the partner's internal team.

Data Privacy: By applying, candidates consent to their personal data being processed in compliance with applicable regulations, including GDPR, for recruitment purposes. Use of AI tools may be involved in screening and analyzing applications to assist but not replace human decision-making.