Junior AI/ML Engineer

About the Project
We are seeking a highly skilled and pragmatic Junior AI/ML Engineer to join the team building "a Stealth Prop-tech startup," a groundbreaking digital real estate platform in Dubai. This is a complex initiative to build a comprehensive ecosystem integrating long-term sales, short-term stays, and advanced technologies including AI/ML, data analytics, Web3/blockchain, and conversational AI. You will be responsible for operationalizing the machine learning models that power our most innovative features, ensuring they are scalable, reliable, and performant.
This is a crucial engineering role in a high-impact project, offering the chance to build the production infrastructure for cutting-edge AI in the PropTech space.
Job Summary
As a Junior AI/ML Engineer, you will bridge the gap between data science and software engineering. You will be responsible for taking the models developed by our data scientists and deploying them into our production environment. Your work will involve building robust data pipelines, creating scalable training and inference systems, and developing the MLOps infrastructure to monitor and maintain our models. You will collaborate closely with data scientists, backend developers, and product managers to ensure our AI-driven features are delivered efficiently and reliably to our users.
Key Responsibilities
Design, build, and maintain scalable infrastructure for training and deploying machine learning models at scale.
Operationalize ML models, including the "TruValue UAE" AVM and the property recommendation engine, by creating robust, low-latency APIs for production use.
Develop and manage data pipelines (ETL) to feed our machine learning models with clean, reliable data for both training and real-time inference.
Implement and manage the MLOps lifecycle, including CI/CD for models, versioning, monitoring for model drift, and automated retraining.
Optimize the performance of machine learning models for speed and cost-efficiency in a cloud environment.
Collaborate with backend engineers to seamlessly integrate ML services with the core platform architecture.
Work with data scientists to understand model requirements and provide engineering expertise to improve model efficacy and feasibility.
Build the technical backend for the AI-powered chatbot, integrating it with NLP services and the core platform data.
Required Skills and Experience
3-5+ years of experience
in a Software Engineering, Machine Learning Engineering, or related role.
A Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
Strong software engineering fundamentals with expert proficiency in Python.
Proven experience deploying machine learning models into a production environment on a major cloud platform (AWS, Google Cloud, or Azure).
Hands-on experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Experience building and managing data pipelines using tools like Apache Airflow, Kubeflow Pipelines, or cloud-native solutions.
Collaborate with cross-functional teams to integrate AI solutions into products.
Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker) and orchestration (Kubernetes).
Preferred Qualifications
Experience in the
PropTech (Property Technology)
or
FinTech
sectors is highly desirable.
Direct experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, AWS SageMaker, Google AI Platform).
Familiarity with big data technologies (e.g., Spark, BigQuery, Redshift).
Experience building real-time machine learning inference systems.
Strong understanding of microservices architecture.
Experience working in a collaborative environment with data scientists.

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