Machine Learning Engineer

Roles and responsibilities

We are looking for a skilled professional with expertise in Machine Learning Engineering (MLE Level II) and Data Science (Level II) to join our AI & Data Science team at Property Finder. This role will focus on developing and deploying advanced AI solutions using Generative AI, Large Language Models (LLMs), and transformer-based models to drive personalisation, automation and innovation across our platforms. The ideal candidate will have a strong foundation in machine learning, practical experience with transformer architectures, and the ability to collaborate across teams to deliver impactful AI-driven solutions.

Join a forward-thinking team at the forefront of innovation, working on cutting-edge projects that leverage GenAI and Large Language Models (LLMs) to transform the real estate experience. Be part of a collaborative and dynamic environment that values continuous learning, technical excellence, and teamwork. With exposure to advanced AI technologies and challenging projects, you'll have the opportunity to grow professionally and make a meaningful impact in an ever-evolving industry.

Key Responsibilities

• Deep understanding and working knowledge of deep learning and neural networks architectures
• Design, fine-tune, and deploy Large Language Models (LLMs) and generative models tailored to business needs.
• Develop applications using transformer-based architectures such as GPT, BERT, T5, or similar frameworks.
• Implement use cases in personalization, content creation, and workflow automation using Generative AI.
• Optimize LLM performance for inference in real-time or large-scale production environments.
• Conduct research and experimentation to identify improvements in GenAI and LLM applications.
• Build and maintain scalable ML pipelines to deploy LLMs and generative models efficiently.
• Develop workflows for fine-tuning and serving transformer models in production.
• Automate the deployment process using MLOps tools (e.g., Kubernetes, MLflow, Docker).
• Optimize data pipelines and feature engineering processes to support transformer-based models.
• Build and implement ML models for predictive analysis and personalization.
• Collaborate with cross-functional teams to generate actionable insights and support business strategies.
• Conduct data wrangling, feature engineering, and advanced statistical analysis.
• Design and evaluate experiments (e.g., A/B testing) to validate model performance.
• Partner with the GenAI team to align model development with business goals.
• Work closely with MLE and Data Science teams to ensure seamless integration of LLMs and generative solutions into production workflows.
• Collaborate with the Futurism team to explore cutting-edge AI applications and opportunities for LLMs.

Desired candidate profile

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• 2+ years of experience in machine learning engineering and data science roles, with 2+ years hands-on experience in transformers, LLMs and generative models.
• Proficiency in fine-tuning and deploying transformer models (e.g., GPT, BERT, T5).
• Familiarity with tools like Hugging Face Transformers, OpenAI APIs, and LangChain.
• Expertise in prompt engineering and domain-specific fine-tuning of LLMs.
• Knowledge of attention mechanisms and sequence-to-sequence modeling.
• Strong experience with ML pipelines and MLOps tools (e.g., Kubernetes, Docker, MLflow).
• Advanced SQL and Python programming skills.
• Familiarity with cloud platforms (AWS, GCP, Azure) for scalable deployments.
• Intermediate experience with supervised and unsupervised learning algorithms.
• Proficiency in data wrangling and feature engineering.
• Knowledge of statistical analysis and hypothesis testing.
• Strong analytical and problem-solving abilities.
• Effective communication skills to collaborate with cross-functional teams.
• Adaptability to work in a fast-paced, dynamic environment.