Senior AI Engineer

act digital; Porto; On-site; EUR 50,000 - 75,000; Full time

Job summary

act digital is seeking an AI/ML Engineer to translate business needs into cutting-edge AI/LLM-based solutions. You will design, fine-tune, and deploy ML models, crafting prompts and optimizing parameters to boost performance.

You will develop POCs with Jupyter, ensure governance, and integrate AI into scalable systems. The role requires 2+ years in ML/Generative AI, strong Python, and hands-on AWS SageMaker or Azure experience.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• Minimum of 2 years of experience in Machine Learning, Generative AI, or Data Science.
• Strong software development experience, with solid knowledge of Python.
• Hands-on experience with Large Language Models (LLMs), particularly GPT, Transformers, and Hugging Face.
• Practical experience in AI/ML model fine-tuning and Prompt Engineering.
• Knowledge of LLM parameter experimentation and optimization, including temperature and top-p.
• Experience with AWS, particularly SageMaker and Bedrock, or equivalent Azure services.
• Solid understanding of databases, software architecture, and scalable system design.
• Knowledge of AI Governance, AI Guardrails, API security, and data privacy.
• Experience developing Proofs of Concept (POCs) and working with tools such as Jupyter Notebooks.
• Knowledge of cloud-native architectures and AI solution integration into business applications.
• Experience with Agile/Scrum methodologies.

Responsibilities

• Translate business requirements into functional applications and innovative AI/LLM-based solutions.
• Design, develop, fine-tune, deploy, and optimize Machine Learning and Artificial Intelligence models.
• Develop and optimize prompts for LLM-based solutions through Prompt Engineering.
• Experiment with and fine-tune model parameters, such as temperature and top-p, to improve model performance.
• Develop Proofs of Concept (POCs) for R&D initiatives using tools such as Jupyter Notebooks.
• Analyze complex datasets and identify opportunities for AI model implementation.
• Implement AI Governance practices, guardrails, auditing mechanisms, and secure AI usage standards.
• Design scalable, robust, cloud-native architectures and integrate AI solutions into business applications.
• Develop cross-functional services and foundational components reusable across business areas.
• Ensure API security, data privacy, and responsible use of AI solutions.
• Collaborate with multidisciplinary teams to develop and enhance technological solutions.
• Participate in code reviews, share technical knowledge, and mentor other team members.

Skills

Python

Machine Learning

LLMs

Prompt Engineering

Model Fine-tuning

Parameter Tuning (temperature/top-p)

AWS SageMaker/Bedrock

Azure AI Services

Databases

Software Architecture

APIs Security

Agile/Scrum

Education

Bachelor's or Master's in Computer Science/Software Engineering

Tools

Docker

Kubernetes

Jupyter Notebooks

Git

Job description

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• Minimum of 2 years of experience in Machine Learning, Generative AI, or Data Science.
• Strong software development experience, with solid knowledge of Python.
• Hands-on experience with Large Language Models (LLMs), particularly GPT, Transformers, and Hugging Face.
• Practical experience in AI/ML model fine-tuning and Prompt Engineering.
• Knowledge of LLM parameter experimentation and optimization, including temperature and top-p.
• Experience with AWS, particularly SageMaker and Bedrock, or equivalent Azure services.
• Solid understanding of databases, software architecture, and scalable system design.
• Knowledge of AI Governance, AI Guardrails, API security, and data privacy.
• Experience developing Proofs of Concept (POCs) and working with tools such as Jupyter Notebooks.
• Knowledge of cloud-native architectures and AI solution integration into business applications.
• Experience with Agile/Scrum methodologies.

Nice to Have

• Relevant certifications in AWS, Azure, or Artificial Intelligence.
• Experience developing and deploying production-grade AI solutions.
• Knowledge of MLOps and AI Governance frameworks.
• Experience with C#/.NET or Java/Spring Boot.
• Familiarity with Docker, Kubernetes, and DevOps/CI/CD pipelines.

Responsibilities

• Translate business requirements into functional applications and innovative AI/LLM-based solutions.
• Design, develop, fine-tune, deploy, and optimize Machine Learning and Artificial Intelligence models.
• Develop and optimize prompts for LLM-based solutions through Prompt Engineering.
• Experiment with and fine-tune model parameters, such as temperature and top-p, to improve model performance.
• Develop Proofs of Concept (POCs) for Research & Development initiatives using tools such as Jupyter Notebooks.
• Analyze complex datasets and identify opportunities for AI model implementation.
• Implement AI Governance practices, guardrails, auditing mechanisms, and secure AI usage standards.
• Design scalable, robust, cloud-native architectures and integrate AI solutions into business applications.
• Develop cross-functional services and foundational components that can be reused across different business areas.
• Ensure API security, data privacy, and responsible use of AI solutions.
• Collaborate with multidisciplinary teams to develop and enhance technological solutions.
• Participate in code reviews, share technical knowledge, and mentor other team members.