Principal AI Engineer

Sustainalytics

Bucharest or Timisoara, Romania

As a Principal AI Engineer at Morningstar Sustainalytics, you will play a key role in developing advanced AI solutions for applications in Environmental, Social, and Governance (ESG) domain. Your work will focus on areas such as:

Extracting information automatically from unstructured documents;
Building Natural Language Generation (NLG) systems;
Developing text classification models.

You will collaborate closely with a cross-functional team, including QA specialists, MLOps engineers, and Business Analysts, to drive innovation through ongoing experiments and proof-of-concept (POC) projects, leveraging cutting-edge AI technologies.

Responsibilities:

Lead the development of production-ready machine learning models to solve real-world challenges, enabling analysts to make faster, more informed decisions while extracting meaningful insights from data;
Process and prepare data through cleaning, transformation, feature engineering, and augmentation to optimize model performance;
Design, fine-tune, and adapt machine learning models to address our unique data requirements;
Propose new ML architectures and methodologies tailored to our evolving business requirements;
Collaborate closely with cross-functional teams, including Business Analysts, , Software Architects, Quality Assurance and MLOps Engineers, to design, implement, and scale impactful AI solutions;
Deliver flexible, incremental solutions in a dynamic environment, ensuring they align with evolving requirements;
Drive continuous innovation and create Proof-of-Concepts (PoCs) to explore and integrate emerging AI technologies.

Requirements:

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field;
5+ years of relevant experience in the field;
Proven track record in developing machine learning projects;
Proficiency in Python and with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, scikit-learn etc.;
Expertise in model training, fine-tuning, and adaptation of open-source models (e.g., Transformers, LLMs), with hands-on experience in transfer learning and domain adaptation;
Proven experience in deploying and monitoring machine learning models in production environments;
Experience working with diverse data types (e.g., tabular, text, images), along with advanced preprocessing, feature engineering, and data augmentation capabilities;
Familiarity with cloud platforms like AWS and Azure;
Strong communication and documentation abilities, including the capacity to explain complex technical concepts to non-technical stakeholders;
Proficiency in documenting experiments to ensure reproducibility and knowledge sharing.

Apply Now

Don't forget to mention EuroTechJobs when applying.

Share this Job