The work arrangement is remote, and candidates must be able to work during EST hours.
This is a full-time position with a competitive base salary in USD.
The industry focus is on PropTech, B2B SaaS, and Real Estate Technology.
The work schedule is 40 hours per week.
Key responsibilities include training and evaluating ML models using common machine learning frameworks in Python, developing and refining NLP pipelines, performing fine-tuning and prompt engineering for LLMs, creating semantic search and recommendation models, conducting experiments and performance benchmarking, collaborating with software engineers to integrate models into backend systems, and preparing clear documentation and evaluation reports.
Requirements:
Strong proficiency in Python for machine learning and data processing is required.
Experience with NLP libraries such as spaCy, Hugging Face Transformers, gensim, and nltk is necessary.
Candidates must be comfortable training deep learning models using Keras, TensorFlow, or PyTorch.
The ability to design and execute ML experiments, evaluate models, and interpret results is essential.
Familiarity with version control (Git), shell scripting, and Linux development environments is required.
Basic backend software engineering skills, including creating and managing endpoints, database services, and task queues, are needed.
Experience with production environments, such as batch inference and model packaging, is required.
Nice to have: experience with MLOps tools (e.g., MLflow, SageMaker, DVC), contributions to Kaggle competitions, AI research, or open-source ML/NLP projects, and a background in classical ML, unsupervised learning, or semantic modeling.
Benefits:
Professional development opportunities include an annual learning budget for books, courses, and conferences.
Mentorship from startup veterans with experience at companies like Looker, GitHub, and Mulesoft is provided.
Employees will have the opportunity to help shape a growing brand that influences fintech innovation.
Inspiring workspaces are available in Berlin, New York, and London, along with travel opportunities.
A flat hierarchy allows employees to work directly with founders and have their ideas heard.
A flexible work setup includes equipment of the employee's choice and strong home office support.
