ML/NLP Engineer

As a ML / NLP Engineer you will play a key role in driving the development, deployment and optimization of advanced machine learning and natural language processing solutions that directly support the organization’s strategic goals. You would be responsible for designing end-to-end ML pipelines, ensuring production readiness and delivering scalable models that generate measurable business impact. Acting as a technical expert, you will provide leadership in adopting MLOps best practices, guiding junior engineers and fostering innovation within the team.

Tasks & Responsibilities

• Develop, optimize, and evaluate new Machine Learning (ML) and Statistical models.
• Design, implement, and deploy scalable ML and Natural Language Processing (NLP) models tailored to specific business needs.
• Select suitable algorithms and fine-tune models to achieve optimal performance.
• Ensure models are production-ready and integrate them seamlessly into existing systems.
• Oversee the entire ML pipeline, from data collection and preprocessing to model training, evaluation, and deployment.
• Implement monitoring and maintenance strategies to ensure the model's performance remains consistent over time.
• Develop data pipelines and preprocess data for training and inference to gain valuable insights into complex datasets, enabling informed decision-making.
• Work closely with data scientists, software engineers, product managers, and other stakeholders to align ML initiatives with business goals.
• Implement evaluation metrics and conduct cross-validation to assess model effectiveness and reliability.
• Present project progress and outcomes to executive leadership.

• Master’s degree in Data Science, ML or a related field.
• Over 3 years of experience in ML/NLP Engineering.
• Additional MLOps and AI/Data Science experience is desired.
• Advanced experience with Python for complex applications and ML models.
• In-depth understanding of Artificial Intelligence principle.
• Excellent verbal and written communication skills in English.
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow and Scikit-learn, as well as Hugging Face ecosystem.
• Strong expertise in NLP techniques, including Tokenization and Named Entity Recognition (NER).
• Proficiency using Pandas and Polars, along with experience in building interactive data applications and prototypes using Streamlit.
• Solid experience with tools such as FastAPI, Celery and Keycloak, as well as working with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) pipelines.
• Familiarity with MLflow and Kubeflow.

Headquartered in Switzerland, MDPI is a fully Open Access publisher with a portfolio of more than 500 journals across all scientific disciplines. To date, MDPI has published the works of over 4.5 million researchers, collaborating with an extensive network of academic institutions and scientific societies worldwide. Above all, MDPI is committed to ensuring that high-quality research is freely accessible to readers across the globe.

At MDPI, technology is not just a support function - it’s a core driver of our innovation, performance and customer experience. We are proud to develop most of our software in-house and host our systems on-premises, further enriching our already diverse technology landscape. Our commitment to building on open-source stacks empowers our teams to work with flexible, modern and community-driven tools. From cutting-edge submission systems to advanced digital services, our IT environment is a dynamic playground where creativity meets complexity. With a strong focus on continuously growing our technology capabilities, MDPI offers a unique opportunity to work at the forefront of digital transformation in publishing. Join us and be part of a team where your ideas matter, your skills are valued and your passion for technology can truly thrive.

Initiatives

At MDPI, we develop and maintain various platforms in order to better serve the scientific community. Please find here-below a list of our main platforms:

https://www.mdpi.com/

https://sciprofiles.com/

https://sciforum.net/

https://www.scilit.net/

https://www.preprints.org/

https://encyclopedia.pub/

#MDPISerbia