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SUREFLOW · Dubai Healthcare City

AI/ML Engineer

full timePosted Aug 11
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Stack mentioned

iotetlllmmlopspythonpandasnumpystatisticsdockerpytorchtensorflowmlflowci/cdartificial-intelligenceanomaly-detectiontime-seriesdeep-learningmachine-learningdata-visualization

Apply only if you are currently based in Dubai and available to join immediately.
Applications that do not meet these criteria will not be considered.

Company overview

We are a fast-growing technology company that designs and develops IoT hardware and software products. Our multidisciplinary team leverages cutting-edge design tools and advanced engineering technologies to bring new ideas to life. We are seeking an AI/ML Engineer to design, build, and deploy the intelligence layer powering our web and mobile applications. Our platform ingests high-volume real-time IoT telemetry, and we need AI-driven features built on top of this data: real-time anomaly detection, forecasting, and intelligent user-facing tools.

Responsibilities:

- Design and build real-time anomaly detection models from streaming IoT sensor data, and manage detection thresholds, false positive rates, and feedback loops to keep alerts actionable.

- Build time-series forecasting models for consumption and demand prediction at device, customer, and aggregate levels.

- Design and build a conversational AI assistant to help end users query their data, understand trends, and receive proactive recommendations in natural language.

- Build data pipelines to transform raw sensor data into model-ready features, and integrate ML models into production APIs to serve predictions reliably to web and mobile apps.

- Evaluate, select, and fine-tune models, from classical time-series methods to deep learning approaches, based on accuracy, latency, and interpretability needs.

- Design LLM-powered pipelines to deliver accurate, grounded answers based on the user's own data.

- Ensure models handle multi-tenant data correctly, including strict isolation between customer data in model inputs and outputs.

- Establish model evaluation, monitoring, and MLOps practices, including tracking prediction accuracy and model drift, model versioning, reproducible training pipelines, and safe deployment and rollback.

- Collaborate with backend and infrastructure teams on compute requirements for training and serving.

- Continuously experiment with new AI capabilities as the product roadmap evolves.

- Document model design decisions, assumptions, and limitations clearly for both technical and non-technical stakeholders.

Requirements:

- Degree in Computer Science or a related field.

- 3+ years of experience building and deploying machine learning models in production.

- Strong hands-on experience with time-series forecasting and anomaly detection on sensor or IoT data.

- Experience integrating LLMs into applications, including prompt design and retrieval-augmented pipelines.

- Strong Python skills with standard ML and data libraries (scikit-learn, Pandas, NumPy), and solid foundation in statistics and probability.

- Experience deploying ML models into production APIs and containerized environments (Docker).

- Comfort working with time-series databases and streaming data, including feature engineering from sensor telemetry.

- Ability to communicate model behavior, limitations, and confidence levels to non-ML stakeholders, including through data visualization.

- Excellent English written and verbal communication.

- Experience with deep learning frameworks (PyTorch, TensorFlow) or MLOps tooling (MLflow, model registries, CI/CD for ML) (a plus).

- Experience with on-premise ML infrastructure, low-latency inference, or explainability techniques in an IoT or industrial context (a plus).

- Must be able to join immediately and already based in Dubai.

Job Type: Full-time

Pay: AED6,000.00 - AED9,000.00 per month

Work Location: In person

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