AI/ML Engineer - Dubai, United Arab Emirates - Hiring Talent Globally

    Hiring Talent Globally
    Hiring Talent Globally Dubai, United Arab Emirates

    1 week ago

    Description


    Requirements:

    • Strong proficiency in Python, PyTorch or TensorFlow.
    • Hands‑on experience in NLP, ML, time‑series forecasting, and computer vision.
    • Solid understanding of financial markets, macroeconomic indicators, and technical analysis.
    • Experience building end‑to‑end ML pipelines and deploying models to production.
    • Familiarity with MLOps tools (MLflow, W&B), Docker, FastAPI, and cloud environments.
    • Background in fintech, algorithmic trading, or financial analytics.
    • Experience with LLMs, embeddings, RAG pipelines, and transformer architectures.
    • Knowledge of backtesting frameworks (Backtrader, Zipline, or custom engines).
    • Experience with distributed computing (Spark, Ray).

    Responsibilities:

    • Develop linear and data‑driven forecasting models for macroeconomic indicators (GDP, CPI, employment).
    • Build predictive models for on‑chain metrics, DVOL, volatility indices, and other market signals.
    • Design data‑settled forecasting instruments for expectation‑based trading.
    • Collaborate with product and engineering teams to integrate models into production systems.
    • Create rule‑based and ML‑driven technical indicators for short‑ and mid‑term trading strategies.
    • Build ML models for pattern recognition, volatility regime detection, and microstructure analysis.
    • Conduct backtesting, feature engineering, and model optimization.
    • Work closely with traders and analysts to convert signals into actionable insights.
    • Develop financial NLP models (FinBERT‑style, transformer‑based, LLM‑based) for real‑time sentiment scoring.
    • Build systems to evaluate market impact of news, economic releases, and social media signals.
    • Design pipelines for ingestion, cleaning, ranking, and scoring of text‑based financial data.
    • Integrate sentiment signals into trading and forecasting models.
    • Apply computer vision techniques to analyze candlestick charts, indicators, and visual market patterns.
    • Build CNN/ViT‑based models to detect technical patterns (breakouts, divergences, head & shoulders, etc.).
    • Convert chart images into structured features for ML and quant models.
    • Work with data engineering teams to generate and maintain chart‑based datasets.


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