Overview
Machine Learning Engineer Jobs in Dubai, Dubai, United Arab Emirates at sansaino
Title: Machine Learning Engineer
Company: sansaino
Location: Dubai, Dubai, United Arab Emirates
Machine Learning Engineer
*Department:* Engineering / Data Science
*Reports To:* Director of Engineering or Head of Data Science
*Employment Type:* Full-Time
*Location: United Arab Emirates
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## About the Role
We are looking for a Machine Learning Engineer to design, build, and deploy ML models and data pipelines that power intelligent search, recommendations, and analytics across our platform. You will work at the intersection of software engineering and data science, turning research prototypes into production-grade systems. This role emphasizes hands-on Python development, deep integration with OpenSearch for scalable indexing and retrieval, and a strong foundation in applied data science.
## What You'll Do
– Design, train, evaluate, and deploy machine learning models for classification, ranking, anomaly detection, natural language processing, and recommendation systems.
– Build and maintain OpenSearch indices, mappings, and query pipelines to support semantic search, vector similarity search (k-NN), and large-scale log analytics.
– Develop custom OpenSearch plugins, ingest pipelines, and scoring functions to integrate ML model outputs directly into search and retrieval workflows.
– Write clean, testable, production-quality Python code across the full ML lifecycle — data ingestion, feature engineering, model training, evaluation, serving, and monitoring.
– Collaborate with data scientists to translate experimental notebooks and proof-of-concept models into robust, versioned, and observable production services.
– Design and manage ETL/ELT pipelines that prepare, validate, and transform data for both model training and OpenSearch indexing.
– Establish monitoring, alerting, and retraining strategies to ensure model performance and data quality do not degrade over time.
– Contribute to architecture decisions around ML infrastructure, including model serving frameworks, feature stores, experiment tracking, and CI/CD for ML.
– Document systems, mentor teammates, and participate in code reviews to raise the technical bar across the team.
## What We're Looking For
*Required:*
– 3+ years of professional experience building and deploying machine learning models in production environments.
– Strong proficiency in Python, including ML/data libraries such as scikit-learn, pandas, NumPy, PyTorch, or TensorFlow.
– Hands-on experience with OpenSearch or Elasticsearch — including index design, custom analyzers, query DSL, aggregations, and relevance tuning.
– Solid understanding of data science fundamentals: statistics, probability, experimental design, feature engineering, and model evaluation.
– Experience building data pipelines using tools such as Apache Airflow, Dagster, Prefect, or similar orchestration frameworks.
– Familiarity with containerization (Docker) and cloud platforms (AWS, GCP, or Azure).
– Comfort working with SQL and relational databases alongside unstructured and semi-structured data sources.
– Strong communication skills and the ability to explain technical trade-offs to both technical and non-technical stakeholders.
*Preferred:*
– Experience with OpenSearch vector search (k-NN plugin), Learning to Rank, or neural search pipelines.
– Familiarity with ML serving platforms such as MLflow, BentoML, SageMaker, or Vertex AI.
– Background in NLP techniques including embeddings, transformers, and retrieval-augmented generation (RAG).
– Experience with distributed computing frameworks like Spark or Dask for large-scale data processing.
– Knowledge of MLOps practices: experiment tracking, model registries, A/B testing frameworks, and automated retraining pipelines.
– Contributions to open-source projects or published research in machine learning, information retrieval, or related fields.
## Qualifications
– Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field. Equivalent practical experience is also valued.
## What We Offer
– Competitive salary and equity compensation.
– Comprehensive health, dental, and vision coverage.
– Flexible work arrangements with remote-friendly options.
– Professional development budget for conferences, courses, and certifications.
– A collaborative, low-ego engineering culture that values curiosity and continuous learning.
Contact: [email protected]