The role

We are seeking a customer-obsessed Solutions Architect to lead technical engagement with Nebius customers across the UAE and the broader region. This role is focused on presales excellence, strong technical storytelling, and driving adoption of Nebius AI Cloud across a wide range of industry segments.

As a Solutions Architect, you will act as a trusted technical partner to customers, helping them understand, evaluate, and adopt Nebius for their AI/ML and high-performance computing workloads. You will combine deep technical expertise with strong communication skills to clearly articulate Nebius’ value proposition and differentiate our platform in a competitive market.

You’re welcome to work remotely from the UAE.

Your responsibilities will include:

• Own end-to-end technical presales engagements, from discovery through solution design, PoC execution, and production readiness
• Serve as a trusted technical advisor to customer stakeholders, including CTOs, Heads of AI/ML, and platform engineering teams
• Deliver compelling technical presentations, demos, and workshops that clearly communicate the value of Nebius across different customer segments
• Execute demos and PoCs to demonstrate performance, scalability, and cost efficiency of Nebius solutions
• Translate customer requirements into scalable, production-ready architectures and best practices
• Collaborate closely with Sales, Product, and Engineering to align customer needs with Nebius capabilities and roadmap
• Act as a technical advocate for customers internally, ensuring feedback is incorporated into product and go-to-market strategy
• Support regional go-to-market efforts, including events, meetups, webinars, and technical content creation
• Contribute to building repeatable technical playbooks and assets for the MEA market

We expect you to have:

• 2–5+ years of experience in technical roles such as Solutions Architect, Cloud Architect, Sales Engineer, or similar, with strong customer-facing exposure
• Proven experience in presales or customer-facing technical roles, including discovery, solution design, and PoC execution
• Strong ability to deliver technical pitches and clearly explain complex infrastructure and AI/ML concepts to both technical and business audiences
• Experience positioning cloud or infrastructure solutions and articulating value propositions in competitive environments
• Solid understanding of ML/AI workloads, including training and inference, and the underlying infrastructure requirements
• Experience with cloud platforms, Kubernetes, and distributed systems
• Hands-on experience with Infrastructure as Code (e.g., Terraform) and scripting/programming (Python preferred)
• Strong communication and storytelling skills, with the ability to adapt messaging across different customer segments
• Deep understanding of the MEA market, including customer expectations, buying behaviors, and local ecosystem
• Fluency in Arabic and English preferred (both written and spoken), with the ability to engage confidently with local customers and stakeholders
• A highly customer-centric mindset, with the ability to balance technical depth and business value

It will be an added bonus if you have:

• Experience with GPU-accelerated workloads and AI infrastructure (NVIDIA ecosystem, CUDA, etc.)
• Hands-on experience with MLOps tools and frameworks (Kubeflow, MLflow, etc.)
• Familiarity with HPC environments and schedulers (e.g., Slurm)
• Experience contributing to regional go-to-market or developer/community initiatives

Why Tamara?

We’re proud to be Saudi’s first FinTech unicorn.

Our mission is to help people own their dreams by building the most customer-centric financial super app in the world. & There is no playbook for that; our Tamarians are writing it. Our teams are made up of innovators, problem-solvers, and learners we thrive on curiosity and collaboration.

If this sounds like you: curious, driven, and ready to build, we’d love to meet you

Apply now and join the next generation of Builders!

About Tamara's Builders Program 

At Tamara, we believe exceptional talent deserves an exceptional launchpad.

Our Flagship Builders Program is designed for ambitious graduates ready to step into real responsibility from day one. This isn’t a rotational “observer” program, it’s a career accelerator built for those who want to build, own, and raise the bar early.
Designed for recent graduates and early-career talent with up to two years of experience, the program places you directly into high-impact roles across Product, Engineering, Design, and beyond. You’ll contribute immediately and grow at an accelerated pace.
From Product to Engineering, Design to Commercial, you’ll tackle meaningful challenges that shape how millions experience fintech across the region. You’ll be trusted with ownership, surrounded by high-caliber peers, and mentored by leaders who expect excellence.

Our January and June cohorts are your opportunity to move fast, think big, and start building what’s next - not someday, but now.

About the role

We’re looking for a fresh graduate or early-career Associate Data Scientist on a builder path.

This role blends product thinking, applied statistics, and production-minded analytics. You will:

• turn ambiguous problems into measurable questions
• build reliable measurement (metrics and experimentation)
• create lightweight models and decision tools that teams can use in real workflows
• partner closely with engineering, product, and risk to improve customer outcomes and business performance
• build AI-assisted decision workflows (for example, LLM-powered analysis copilots backed by a curated metrics layer, with clear guardrails and validation)

With the advancement of AI, we value people who have strong fundamentals and clear thinking. Understanding data generation, measurement, tradeoffs, and how to validate results matters more than memorizing tools. You'll learn how to use AI responsibly to move faster, while still owning correctness, robustness, and interpretation.

Your responsibilities

• Define problems and measurement
  • Translate product or business questions into testable hypotheses and clear success metrics.
  • Build and maintain metric definitions and analysis templates so decisions are consistent and repeatable.
• Experimentation and causal thinking
  • Design, analyze, and interpret A/B tests (and quasi-experiments when randomization is not possible).
  • Partner with product and engineering to ensure correct tracking, guardrails, and experiment quality.
• Modeling for decisions (practical ML)
  • Build baseline predictive and segmentation models (for example, churn propensity, risk signals, customer clustering) with clear evaluation and limitations.
  • Focus on models that are actionable: who will use them, when, and what decision they change.
• Applied AI (LLMs) for analytics and decisioning
  • Prototype small, safe LLM use cases that improve how teams explore data (for example, natural-language Q&A over a curated dataset, summarizing experiment results, or generating investigation checklists).
  • Help define evaluation and validation approaches for AI-assisted outputs (sanity checks, golden queries, offline test sets, and human review loops).
  • Partner with platform and security stakeholders to ensure AI workflows are permissioned correctly and avoid leaking sensitive data.
• Analytics that ships
  • Create reusable, well-documented analysis assets: datasets, feature tables, notebooks, dashboards, and simple services or jobs.
  • Collaborate with data engineering to productionize reliable pipelines where needed.
• Data quality and reliability
  • Validate data inputs, monitor key metrics, and investigate anomalies.
  • Document assumptions and build sanity checks so analyses and models are trustworthy.
• Responsible use of AI tools
  • Use AI to accelerate coding, documentation, and exploration.
  • Validate AI outputs, protect sensitive data, and follow safe data handling practices.

Your expertise (must have)

• Fresh graduate or < 1 year of relevant experience (internships, capstone projects, or part-time roles count).
• Strong SQL fundamentals (joins, aggregations, window functions).
• One programming language for data (preferably Python) with basic skills in:
  • Data manipulation (tables/dataframes)
  • Statistics fundamentals (distributions, sampling intuition, confidence basics)
  • Basic modeling (regression/classification basics and evaluation intuition)
• Strong analytical thinking:
  • Ability to define a problem, validate data, and explain results clearly.
• Strong attention to detail and commitment to accurate, reliable outputs.
• Ability to work effectively in a team-oriented environment.

Nice to have

• Exposure to experimentation platforms or frameworks (for example Statsig, Optimizely, internal experimentation tooling).
• Familiarity with modern analytics stacks (dbt, BigQuery, Snowflake, Looker, PowerBI, Tableau) through coursework or projects.
• Exposure to ML tooling (scikit-learn, notebooks, basic MLOps concepts) and version control (Git).
• Familiarity with LLM concepts (prompting basics, retrieval/RAG intuition, and evaluation approaches) through coursework or side projects.
• Understanding of product analytics concepts (funnels, cohorts, retention) and causal pitfalls (selection bias, confounding).
• Experience creating AI-ready data assets (clean semantic layers, metric definitions, data contracts, documentation, and sanity-check checklists).
• Knowledge of responsible data handling (PII basics, access controls, safe sharing).

What success looks like

• You can independently deliver an end-to-end analysis with clear assumptions, validation steps, and a concrete recommendation.
• You help ship at least one decision tool (experiment, metric framework, or lightweight model) that changes a product or business decision.
• Stakeholders can run repeatable analyses with less back-and-forth, and your work reduces ambiguity in key metrics.
• You can spot when results look off, debug quickly, and explain the root cause.

About Us

Tamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.

Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.

Your Role

We are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.

You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.

Your Responsibilities

Model Deployment & Scaling

• Productionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architectures
• Design low-latency, high-availability APIs and pipelines for real-time model inference.
• Implement batch scoring systems for periodic risk assessments.=

MLOps & Infrastructure

• Build and maintain CI/CD pipelines for model deployment and monitoring.
• Set up automated feature engineering pipelines, leveraging feature stores.
• Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.

Model Monitoring & Maintenance

• Implement real-time and batch monitoring for data drift, concept drift, and model performance.
• Build automated retraining workflows and model rollback mechanisms.

Collaboration with Risk DS

• Work closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.
• Advise DS on efficient model architectures for operational environments.
• Optimize feature computation for speed and scalability.

System Design & Integration

• Integrate models with credit underwriting, fraud detection, collections, and merchant risk systems.
• Collaborate with backend engineering to align on API contracts and system interfaces.

Your Expertise

• 6+ years of experience as an MLE, ML Engineer, Mlops Developer.
• Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).
• Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).
• Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).
• Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).
• Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).
• Proven track record of deploying and maintaining ML models in production at scale.
• Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).

All qualified individuals are encouraged to apply.

The role of a Data Scientist at Dataiku is quite unique. Our Data Scientists not only code up solutions to real-world problems, but also participate in client-facing endeavours throughout the customer journey. This includes supporting their discovery of the platform, helping integrate Dataiku with other tools and technologies, some user training, and co-developing data science projects from design to deployment.

Just as non-technical skills are important, so too are technical skills. Our Data Scientists work on the Dataiku platform every day. Aside from the visual tools, our team primarily uses Python and SQL, with occasional work in other languages (e.g., R, PySpark, JavaScript). An ideal candidate is excited to learn complex new technologies and modelling techniques while being able to explain their work to other data scientists and clients.

In this role, you'll help the team:

• Co-develop production-level data science projects with our customers

• Analyse and investigate various kinds of data and machine learning applications across industries and use cases

• Help users discover and master the Dataiku platform, via user trainings, office hours, and ongoing consultative support

• Provide data science expertise both to customers and internally to Dataiku’s sales and marketing teams

• Develop custom Python-based “plugins” in collaboration with Solutions, R&D, and Product teams, to enhance Dataiku’s functionality

You might be a good fit for the role if you have:

• English - fluent, Arabics - fluent/native will be a big plus

• Curiosity and a desire to learn new topics and skills

• Empathy for others and an eagerness to share your knowledge and expertise with your colleagues, Dataiku’s customers, and the general public

• The ability to clearly explain complex topics to technical as well as non-technical audiences

• 2 - 10 years of experience with Python and SQL

• 2 - 10 years of experience with building ML models and using ML tools (e.g., sklearn)

• Familiarity with data visualisation in Python and R

• Understanding of underlying data systems such as Cloud architectures, Hadoop, or SQL

Technical skills that may help you in the role:

• Experience with Consulting and/or Customer-facing Data Science roles

• Experience with Data Engineering or MLOps

• Experience developing WebApps in JavaScript, RShiny, or Dash

• Experience building APIs

• Experience using enterprise data science tools

• Passion for teaching or public speaking

#LI-AS2

We are seeking a highly motivated and skilled Quantitative Trader to manage and optimize an algorithmic, delta-neutral strategies portfolio. You will be responsible for managing backtest schedules, allocating capital to existing strategies, and automating processes to ensure efficiency. This role is highly technical and requires a strong analytical mindset, focus, and the ability to take ownership of tasks in a fast-paced environment.

⚠️ IMPORTANT: We consider only candidates with proven live-trading experience and a documented strategy performance record that meets the following criteria::

• Asset Classes: Spot, Perpetual Swaps, and Dated Futures. (Note: Options-based strategies are not currently under consideration).

• Strategy Types:

  • HFT: Classic market-making, microstructure models, and ML-driven approaches.

  • MFT: Directional ML models or portfolio-based strategies (e.g., Statistical Arbitrage, Beta-Neutral models).

• Performance Metrics:

  • Sharpe Ratio: 3.0+

  • Daily Capital Turnover: 3.0+

  • Target APY (Post-Leverage):

    • High-Capacity MFT: 30%+

    • Low-Capacity HFT: 100%+

What We Offer

We are committed to creating an environment where talented traders can thrive. We provide the tools, support, and financial incentives necessary for success.

• Competitive PnL Share We offer an above-market payout structure designed to generously reward strong performance. We believe that you should earn a significant share of the profits you generate, and our terms are both flexible and negotiable for top-performing strategies.

• Path to Leadership For high-impact contributors, we offer a clear path to leadership roles within our growing quant division. This is a unique opportunity for those interested in not just trading, but also in building and leading a world-class team.

• Autonomy & Support We empower you to focus on what you do best—trading. You will have full ownership of your strategy and research without rigid top-down bureaucracy. Our role is to provide the capital, infrastructure, and collaborative support you need to succeed.

• Tier-1 Trading Infrastructure Gain a competitive edge with access to our top-tier technology stack, built for performance and scale. This includes low-latency infrastructure, direct market access (DMA) to major exchanges, and dedicated engineering resources.

• Collaborative & Flat Structure We foster a non-siloed environment with direct access to senior traders, engineers, and leadership. This open communication culture accelerates development, encourages knowledge sharing, and helps solve complex problems faster.

• Relocation to Dubai For successful candidates interested in joining our main office, we provide a comprehensive relocation package to facilitate a smooth transition to Dubai for you and your family.

Technical Requirements & Expectations:

• Experience with ML pipelines and MLOps tools
• Familiarity with tools like Kedro, Optuna, and orchestration systems
• Capable of working with clusters for training and deploying models
• Comfortable structuring workflow from data cleaning to production-ready pipeline
• Skilled in automation tools for efficient, reliable model deployment
• Able to work independently with minimal onboarding support

Ideal Candidate Profile:

• Brings a ready-to-trade proprietary strategy
• Demonstrated live trading experience with proven profitability metrics (PnL history, risk metrics, win rate)
• Strong technical understanding of market microstructure, execution optimization, and infrastructure demands (latency sensitivity, tick-to-trade, co-location benefits)
• Ability to clearly articulate infrastructure, connectivity, and operational needs
• Comfortable working independently, while being ready to collaborate with our engineering and devops teams for optimization
• Strong preference for candidates with crypto trading experience (Binance, Bybit, OKEX, etc.); traditional market experience is welcome if the strategy is adaptable

Additional details:

– This role reports directly to the Managing Partner/Head of Trading, offering tremendous growth opportunities.
– Rust knowledge is a strong plus.
– Expertise in applying AI tools to finance is an edge
– Preference for candidates in the Dubai timezone, with an even stronger preference for those based in Dubai.
– Good English is a plus, but day-to-day most team members speak Russian