Dubai Science & Technology Job Listings

Careem UAE

Automation Lead

Careem

Careem is building the Everything App for the greater Middle East, making it easier than ever to move around, order food and groceries, manage payments, and more. Careem is led by a powerful purpose to simplify and improve the lives of people and build an awesome organisation that inspires. Since 2012, Careem has created earnings for over 2.5 million Captains, simplified the lives of over 70 million customers, and built a platform for the region’s best talent to thrive and for entrepreneurs to scale their businesses. Careem operates in over 70 cities across 10 countries, from Morocco to Pakistan. Why this role matters at Careem Careem exists to simplify and improve the lives of people in our region. AI is a key driver of that mission. Whether it’s predicting demand, optimizing captain incentives, improving delivery ETA accuracy, or automating customer care, you’ll be helping to build real systems that impact millions of people across the Middle East, North Africa, and Pakistan. This is a hands-on role where you’ll ship models into production, experiment fast, and learn alongside a talented team that’s driving meaningful change. What you’ll do Build, train, and evaluate machine learning models for key services like ride-hailing, food delivery, and payments Work with real-world data and translate it into features, signals, and insights Collaborate with operations, engineers, product managers, and analysts to tackle challenges like OCR based partner onboarding, dynamic pricing, route optimization, churn prediction, and fraud detection Run experiments, track model performance, and help roll out models into live systems Improve the way we serve and monitor machine learning models Contribute to a strong team culture of learning, iteration, and accountability What you’ll need Must-haves: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related technical field Up to 3 years experience working with machine learning in any form: internships, research, personal projects, Kaggle competitions, or a previous job Solid Python skills, especially with libraries like pandas, NumPy, and scikit-learn A strong grasp of ML fundamentals like classification, regression, cross-validation, and evaluation metrics Familiarity with at least one ML framework such as TensorFlow, PyTorch, or XGBoost Clear communication, curiosity, and the ability to work well in a team Nice-to-haves: Exposure to deep learning techniques in NLP, vision, or recommender systems Experience working with large datasets using Spark, Hive, or cloud tools Familiarity with model deployment and monitoring workflows (Airflow, MLflow, etc.) Interest in solving real operational challenges like logistics, fraud detection, or customer retention A GitHub profile or project portfolio that shows what you’ve built What you’ll get A chance to work on AI problems at regional scale that improve lives and drive real business outcomes A smart, motivated team that values learning and practical impact Flexibility to work remotely, with strong support for collaboration and ownership A front-row seat to how AI is transforming mobility, delivery, and digital services in emerging markets Application Link: https://job-boards.greenhouse.io/careem/jobs/8086435002?gh_jid=8086435002

Negotiable Salary

ML Researcher (Time Series / Signals)63369923123457111

Workable

ML Researcher (Time Series / Signals)

Dubai - United Arab Emirates

We are a prop-trading company that combines the agility of a startup with the resources of a high-performing fund. Our team is focused on developing cutting-edge strategies, and working with us means not just advancing technology, but also being part of a team where ideas are valued, professional growth is encouraged, and every member has the opportunity to unlock their full potential. We’re looking for a Quantitative Researcher with a strong background in machine learning and time series modeling to join our team. What You’ll Be Doing: Researching, developing, and deploying cutting-edge machine learning models for forecasting complex, high-dimensional time series — from market signals to macroeconomic indicators and alternative data. Building ML pipelines from scratch: data ingestion, feature processing, modeling, calibration, and monitoring. Designing custom validation and testing approaches for non-stationary data, including regime shift detection and adversarial evaluation. Working with large-scale data sources — tick-level, satellite, transactional, web-scraped — and transforming them into structured features. Collaborating with quants and engineers to integrate ML models into real-world investment processes. Contributing to strategic research initiatives, including causal inference, representation learning, and attention-based models for time series. Requirements Experience: 4–8 years of work experience, ideally a mix of academia and industry. Publications at top AI venues (NeurIPS, ICLR, ICML) in the fields of Time Series or Signal Learning. Experience building models that forecast market or alternative signals, macroeconomics, commodities, or sentiment. Participation in building an ML research culture: internal toolkits, mentorship, and open science practices. Skills & Education: Expertise in deep learning for time series: Temporal Fusion Transformers, DeepAR, N-BEATS, PatchTST. Knowledge of causal inference and counterfactual reasoning for time series. Experience in multi-modal learning (time series + tabular data + text). Proficiency with the ML stack: PyTorch, HuggingFace, DVC, Docker, etc. Skills in model validation for non-iid data: custom cross-validation strategies, regime-aware data splits. Ability to build end-to-end ML pipelines — from data ingestion to production inference. Master’s degree or PhD in a quantitative field (Physics, Mathematics, Computer Science, or related areas). Languages: Russian, English. Nice to have: Understanding of option pricing models, hedging. Experience with C++ or Rust. Ability to communicate technical ideas to diverse audiences, including non-technical stakeholders. Benefits Culture of Innovation: An open, dynamic, and inclusive environment where your ideas matter. Flexibility & Impact: Enjoy the freedom of a startup with the backing of a well-resourced fund. High Impact: Work directly on projects that shape strategies and drive the fund’s success. 35 Days of Vacation – Plenty of time to rest and recharge. 100% Paid Sick Leave – Recover without financial worries. Top-Tier Equipment – Choose the tools that suit you best (within budget). Corporate Psychologist – Mental health support when you need it.

Negotiable Salary

Data Scientist Trainees(Internship)63360122130051112

Workable

Data Scientist Trainees(Internship)

Dubai - United Arab Emirates

We’re looking for passionate and motivated individuals to join our Data Science Trainee Program at our Dubai office. This structured internship spans three months and is designed to provide hands-on experience, mentorship from industry experts, and skill development in AI, machine learning, and data analytics.You’ll work with real-world datasets, learn how to apply data science concepts in practice, and contribute to impactful projects that shape our fintech and regtech solutions. Key Responsibilities Assist in collecting, cleaning, and analysing structured and unstructured data Support the development of machine learning models and predictive analytics Contribute to data visualisations and reporting using Python libraries (e.g., Pandas, Matplotlib) Collaborate with cross-functional teams and mentors on live projects Help document analysis workflows and model outputs Participate in team discussions on problem-solving and model optimisation Eligibility Criteria Currently pursuing or recently completed a degree in Data Science, AI, Computer Science, Statistics, or a related field Basic understanding of Python programming and data tools (e.g., Pandas, NumPy, Scikit-learn) A strong interest in data science, machine learning, and AI Analytical mindset and problem-solving attitude Eagerness to learn and grow in a collaborative environment Preferred (But Not Mandatory) Familiarity with tools such as Jupyter Notebooks, Power BI, or data visualization libraries Basic understanding of statistical concepts and data wrangling Exposure to cloud tools or data pipelines is a plus What You’ll Gain ✅ Hands-on experience with real-world datasets and live projects ✅ Structured training and one-on-one mentorship by industry experts ✅ Exposure to corporate-level data science workflows in fintech/regtech ✅ Certificate of Completion and detailed performance feedback ✅ Opportunity for future consideration in full-time or paid roles based on performance ✅ A collaborative learning culture designed to help you grow Take the First Step Toward a Career in Data Science. This program offers much more than just learning—it’s an opportunity to build your foundation, gain confidence, and prepare for a successful career in tech. Apply now and start your journey in data science with Programmers Force!

Negotiable Salary

Research Lead - Mid-Frequency Trading (MFT)63360085577217113

Workable

Research Lead - Mid-Frequency Trading (MFT)

Dubai - United Arab Emirates

Role Overview: We are seeking a Quant Research Lead with deep expertise in mid-frequency systematic trading. You will be responsible for end-to-end research, development, and deployment of MFT strategies on crypto derivatives markets. Key Responsibilities: Research, design, and develop systematic mid-frequency trading strategies. Build and manage models from scratch — including alpha research, signal generation, backtesting, portfolio construction, and risk management. Collaborate closely with engineering and trading teams for efficient execution and scaling of strategies. Monitor live trading performance, adapt to market dynamics, and continuously optimize strategies. Requirements 5–10 years of experience in quantitative research/trading, specifically in systematic mid-frequency trading Track record of building strategies independently from ideation to production. Expert-level programming skills (Python, C++, R or similar). Solid understanding of market microstructure, quantitative research methods, alpha modeling, and execution systems.

Negotiable Salary

Quantitative Trader (Prop Trading)63360038634883114

Workable

Quantitative Trader (Prop Trading)

Dubai - United Arab Emirates

We are a prop-trading company that combines the agility of a startup with the resources of a high-performing fund. Our team is focused on developing cutting-edge strategies, and working with us means not just advancing technology, but also being part of a team where ideas are valued, professional growth is encouraged, and every member has the opportunity to unlock their full potential. We are looking for an experienced specialist with proven experience in Quantitative Research, including intraday trading. What You’ll Be Doing: Designing and scaling strategies across various investment decision horizons — from seconds to several days Generating ideas based on analysis of market microstructure, correlations, behavioral patterns, and inefficiencies Proposing and improving tools for backtesting, cross-validation, risk management, and PnL analysis Contributing to the development and fine-tuning of execution infrastructure, including order routing, slippage models, and latency sensitivity Continuously adapting strategies to changes in market conditions and exchange infrastructure Running fast iteration cycles: generate → test → deploy → refine (with structured post-mortems) Requirements Experience: 2–5 years of experience at a prop trading firm or internal quant desk Proven track record running live strategies with AUM > $1M or Sharpe > 2.0 on real accounts Ownership of a complete alpha or tech stack — from idea generation to execution Hands-on experience working with real-time data feeds, tick data, and low-latency infrastructure Skills & Education: Expertise in high-frequency or medium-frequency alpha generation Solid understanding of market microstructure, latency arbitrage, and order book dynamics Experience with real-time strategy automation and risk controls Strong coding skills in C++ or Rust and Python, with the ability to write production-grade low-latency code Proficiency in feature engineering and signal combination to maximize information ratio (IR) Experience with backtesting frameworks — either in-house or open-source (e.g., bt, Zipline, or others) Master’s or PhD in a quantitative field such as Physics, Mathematics, Computer Science, or a related discipline. Languages: Russian, English. Nice to have: Understanding of options pricing models Experience with machine learning, deep learning, or reinforcement learning (ML/DL/RL) techniques Strong communication skills, with the ability to explain complex technical ideas to both technical and non-technical stakeholders. Benefits Culture of Innovation: An open, dynamic, and inclusive environment where your ideas matter. Flexibility & Impact: Enjoy the freedom of a startup with the backing of a well-resourced fund. High Impact: Work directly on projects that shape strategies and drive the fund’s success. 35 Days of Vacation – Plenty of time to rest and recharge. 100% Paid Sick Leave – Recover without financial worries. Top-Tier Equipment – Choose the tools that suit you best (within budget). Corporate Psychologist – Mental health support when you need it.

Negotiable Salary