As a Senior Machine Learning Engineer, you will be part of an international team and play a pivotal role in designing, implementing, and deploying multimodal machine learning models.
We solve real-world challenges posed by SAP Concur customers with a focus on intelligent document processing, e.g., information extraction, OCR, and entity recognition. You will apply the state-of-the-art in deep learning and take one of the richest data sets available in industry to the next level.
What you’ll do
- You'll be involved in various aspects of the data science process, including acquiring data, conducting exploratory data analysis, building models, and monitoring their performance
- Evaluate and adopt generative AI based solutions – either through external LLM’s or fine tuning Local LLM’s.
- Work closely with Software Engineers to integrate machine learning models into production systems and ensure scalability and reliability.
- Perform thorough testing and validation of machine learning models to ensure accuracy and robustness.
- Collaborate with cross-functional teams to define requirements, scope, and milestones for machine learning projects.
- Stay up-to-date with the latest advancements in machine learning ,mentor team members and contribute to the team's knowledge-sharing initiatives.
What you Bring
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
- Solid understanding of machine learning algorithms, model evaluation, and validation techniques.
- Exposure to Generative AI and familiarity with the capabilities of recent advances in Large Language Models.
- Strong programming skills in Python and proficiency in machine learning libraries (e.g., scikit-learn, Hugging Face, Langchain, and PyTorch).
- Experience with SQL or NoSQL databases.
- Familiarity with cloud platforms and ML frameworks (e.g., AWS Sagemaker, MLFlow, Weights and Biases) and deploying machine learning models in production environments.
- Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders.
- Experience in building data pipelines will be an added advantage.