project manager

sales engineer

project engineer

qa engineer

architect engineer

ml engineer

Tabby

<div><h3 class="jobSectionHeader">Description</h3><div> 

Senior Data Engineer 
 
 | Full-time | On site | Riyadh 
</div><div>Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 15 million users choose Tabby to stay in control of their spending and make the most out of their money. 
 
 
</div><div>The company's flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 40,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores.
</div><div> 
Tabby generates over $10 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region.
</div><div> 
Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $4.5 billion. 
 
 
</div> 
<h3 class="jobSectionHeader">Key Responsibilities</h3><div> 
Tabby is looking for a Senior Data Engineer to help build and evolve its core data platform, combining modern data warehouse capabilities with internal data services such as a Feature Store. You will work across DWH, streaming, and data services domains to power analytics, ML, and operational use cases across the company. 
</div><div>You will join a high-impact, high-growth environment and collaborate with world-class engineers, analysts, and ML teams to design and deliver scalable data solutions that are deeply integrated into Tabby's products and internal tools. 
 
What you&rsquo;ll bring
</div><ul><li>3&ndash;5+ years of experience as a Data Engineer, ML Engineer, or Backend Engineer working on data-intensive systems.</li>
<li>Proven experience in DWH development and maintenance for business users, analysts, and ML engineers.
</li><li>Strong background in designing and operating high-load, scalable data processing and storage systems.
</li><li>Solid understanding of data architecture patterns such as Kimball, Inmon, Medallion, and Data Mesh.
</li><li>Hands-on experience with data modeling concepts: SCD forms, normal forms, star schema, Data Vault.
</li><li>Proficiency in Python following best practices for clean, testable, and maintainable code.</li>
<li>Advanced SQL skills and best practices for working with large datasets and complex transformations.</li>
<li>Familiarity with system design best practices for distributed data platforms and services.</li>
<li>Experience with modern data stack tools such as Airflow, dbt, BigQuery, ClickHouse, PostgreSQL, Docker, GitLab CI/CD, and Google Cloud Platform.</li>
<li>Experience with event-driven systems and streaming pipelines, including tools like Debezium and message brokers/queues.
</li>Strong communication skills in English (B2 level or higher) and the ability to work independently in a remote setup. 
<li>
</li></ul> 
<h3 class="jobSectionHeader">What you&rsquo;ll bring:</h3><div> 
What you&rsquo;ll bring:</div><ul>
<li>Design, build, and maintain Tabby&rsquo;s corporate data warehouse to support business users, analysts, and ML engineers.
</li><li>Develop and evolve internal data services such as a Feature Store and other high-impact data products.</li>
<li>Build and operate robust EL/ELT/ETL pipelines for both batch and streaming use cases.</li>
<li>Integrate new tools and practices for data processing, storage, governance, and data quality across the platform.</li>
<li>Implement and maintain reliable data synchronization between internal and external systems.
</li><li>Design and support high-load, scalable data processing and storage solutions, ensuring performance and reliability.
</li><li>Contribute to the architecture of the data platform, including technology choices and system design decisions.</li>
<li>Optimize infrastructure and data workflows with a focus on cost efficiency in the cloud.
</li><li>Collaborate closely with analytics, risk, and ML teams to understand data needs and deliver high-quality datasets and services.</li>
</ul><div>Nice to have
</div><ul><li>Experience with REST and gRPC APIs as well as message brokers and queues for integrating data services.</li>
<li>Experience with modern systems of data storage: relational, MPP, and NoSQL databases.</li>
<li>Hands-on experience with Google Cloud Platform and its data services.</li>
GO development experience for building high-performance data services. 
<li>
</li></ul> 
<h3 class="jobSectionHeader">What we offer:</h3> 
<ul>
<li>
Work alongside a high-performing, international engineering team in a global fintech unicorn</li>
<li>Stock options (ESOP) in a fast-scaling, pre-IPO company</li>
<li>Health Insurance</li>
<li>Competitive salary and other bonuses</li></ul><div></div><h3 class="jobSectionHeader"> 
About Tabby</h3><div>
Tabby creates financial freedom in the way people shop, earn and save, by reshaping their relationship with money. 
 
The company&rsquo;s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 32,000 global brands and small businesses, including Amazon, Noon, IKEA and Shein use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores. 
 
Tabby has generated over $7 billion in transaction volume for its partner brands and has the highest rated, most reviewed, largest and fastest growing app of any fintech in the GCC region. 
 
Tabby launched operations in 2020 and has raised +$1 billion in equity and debt funding from global and regional investors.</div></div>

Senior Data Engineer (Saudi National)

Qualcomm

<div><h2 class="jobSectionHeader">Company:
</h2>Qualcomm Middle East Information Technology Company LLC
<h2 class="jobSectionHeader">Job Area:
</h2>Engineering Group, Engineering Group &gt; Software Test Engineering
General Summary:
About Us
<div>Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region . As Saudi Arabia accelerates its digital transformation under Vision 2030, Qualcomm is investing in world‑class computing and data centre capabilities to power AI, cloud, and advanced connectivity at scale. This is a unique opportunity to work in a fast‑growing technology hub, supporting critical environments and helping shape the future of data centre operations in the Kingdom and beyond.
</div>About the Role
We are looking for a Site Reliability Engineer or Senior Engineer &ndash; Datacentre AI Engineering at Qualcomm Technologies, Inc., located in Riyadh, Saudi Arabia.
The role focuses on the design, operation, and continuous improvement of large‑scale AI inference systems in a datacenter environment. The engineer will support critical AI use cases by ensuring Qualcomm&rsquo;s AI infrastructure is reliable, scalable, and production‑ready for advanced machine‑learning workloads.
The role requires strong systems and software engineering fundamentals, hands‑on execution, and the ability to work independently on complex problem areas while collaborating closely with cross‑functional teams across hardware, software, and machine learning.
Ideal candidates will have 2-8 years of experience
Key Responsibilities will include
Key Responsibilities
1. AI Infrastructure
<ul><li>Design, deploy, and operate large‑scale AI inference systems supporting critical AI workloads.
</li><li>Ensure reliability, availability, and scalability of Qualcomm datacenter AI clusters.
</li><li>Develop and maintain software tools and support infrastructure around AI software stacks.
</li></ul>2. AI &amp; ML Engineering
<ul><li>Analyze software requirements and collaborate with architecture and hardware engineers to support AI workloads.
</li><li>Build, deploy, and operate components supporting LLM inference, agentic AI workflows, and AI services.
</li><li>Work with models, systems, and software teams to improve model performance on AI100 deployments.
</li><li>Identify and implement optimizations for workloads running on multi‑SoC and multi‑card systems.
</li></ul>3. Site Reliability Engineering (SRE)
<ul><li>Apply SRE fundamentals including monitoring, alerting, incident response, and performance optimization.
</li><li>Support production ML systems using MLOps tools and operational best practices.
</li><li>Contribute to incident reviews, operational documentation, and continuous reliability improvements.
</li></ul>4. Observability &amp; Tooling
<ul><li>Build and maintain observability tools, dashboards, and alerts to monitor system health and reliability.
</li><li>Monitor infrastructure and services using tools such as Prometheus, Grafana, CloudWatch, and custom telemetry.
</li><li>Create and maintain technical documentation, runbooks, and knowledge‑base articles.
</li></ul>5. Automation &amp; CI/CD
<ul><li>Develop automation to reduce manual operational tasks and improve system reliability.
</li><li>Support CI/CD pipelines for AI service and agent deployment.
</li><li>Apply Infrastructure‑as‑Code practices using tools such as Terraform and Ansible.
</li></ul><div></div>Required Skillset
1. AI &amp; Deep Learning
<ul><li>Experience working with AI/ML workloads such as LLMs, NLP, Vision, Audio, or Recommendation systems.
</li><li>Understand ML inference concepts including batching, token streaming, and performance considerations.
</li><li>Hands‑on experience with PyTorch and familiarity with modern ML frameworks.
</li><li>Familiarity with distributed inference, checkpointing, and accelerator‑based compute environments.
</li></ul>2. AI Operations
<ul><li>Experience supporting AI or ML applications in production environments.
</li><li>Familiarity with LLM inference pipelines and AI service operations.
</li></ul>3. Programming &amp; Software Design
<ul><li>Strong programming skills in Python with experience building and supporting production systems.
</li><li>Experience with scripting and automation using Python and Bash.
</li><li>Familiarity with configuration management and orchestration tools.
</li></ul>4. Systems &amp; Infrastructure
<ul><li>Strong Linux fundamentals include shell, containers, system services, and networking basics (DNS, TLS, HTTP/gRPC).
</li><li>Experience working with cluster schedulers such as Slurm or equivalent systems.
</li><li>Experience operating distributed systems with high availability and fault tolerance.
</li></ul>5. Observability &amp; Monitoring
<ul><li>Hands‑on experience with monitoring and logging tools such as Prometheus, Grafana, ELK, or Loki.
</li><li>Understanding of incident management, service health metrics, and system reliability monitoring.
</li></ul>6. DevOps &amp; SRE Practices
<ul><li>Solid understanding of SDLC, release processes, and operational reliability practices.
</li><li>Familiarity with CI/CD pipelines and Infrastructure‑as‑Code tools.
</li></ul><div></div>Preferred Skillset
<ul><li>Experience with GenAI, Agentic AI systems, or LLM orchestration frameworks.
</li><li>Exposure to LangChain, AutoGen, or RAG‑based systems.
</li><li>Experience with additional ML frameworks such as TensorFlow, JAX, or Ray.
</li><li>Knowledge of GPU/accelerator‑based systems and high‑performance networking (RDMA, InfiniBand, RoCE).
</li><li>Experience with advanced MLOps workflows or large‑scale AI platform operations.
</li></ul><div></div>Qualifications
<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in engineering, Computer Science, AI/ML, or a related field.
</li><li>2&ndash;8 years of software, systems, or infrastructure engineering experience, preferably in production or datacenter environments.
</li></ul>What's on Offer
Apart from working with great people, we offer the below:
<ul><li>Salary including housing &amp; transport allowance
</li><li>Stock (RSU's) and performance related bonus
</li><li>16 weeks fully paid Maternity Leave
</li><li>6 weeks fully paid Paternity Leave
</li><li>Employee stock purchase scheme
</li><li>Child Education Allowance
</li><li>Relocation and immigration support (if needed)
</li><li>Life and Medical Insurance
</li><li>Live+ Well Reimbursement for health and recreational membership fees
</li></ul>Minimum Qualifications:
<ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
</li></ul>OR
 
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
 
OR
 
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
 
 
<ul><li>2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul>*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
<div>Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</div>Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
If you would like more information about this role, please contact Qualcomm Careers .</div>

Infrastructure & Site Reliability Engineer – Datacentre AI Engineering - Riyadh, KSA

<div><h2 class="jobSectionHeader">Company:
</h2>Qualcomm Middle East Information Technology Company LLC
<h2 class="jobSectionHeader">Job Area:
</h2>Engineering Group, Engineering Group &gt; Systems Engineering
General Summary:
<div></div><div>About Us
</div><div>Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region . As Saudi Arabia accelerates its digital transformation under Vision 2030, Qualcomm is investing in world‑class computing and data centre capabilities to power AI, cloud, and advanced connectivity at scale. This is a unique opportunity to work in a fast‑growing technology hub, supporting critical environments and helping shape the future of data centre operations in the Kingdom and beyond.
</div><div></div><div>About the Role
</div><div>As a Qualcomm Datacenter AI Solutions Engineer, you will research, develop, optimize, and validate software, hardware, architecture, algorithms, and machine learning solutions that enable the deployment of cutting-edge AI datacenter technology.
Qualcomm Solution Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. This is a great opportunity to innovate and develop leading-edge products and solutions around best-in-class Qualcomm AI inference accelerators for data center, and hybrid AI applications.
Principal Duties and Responsibilities:
<ul><li>Design, develop, and optimize AI/ML solutions leveraging Qualcomm AI hardware, software, and ecosystem to deliver high-performance, power‑efficient, and scalable inference
</li><li>Develop and deploy GenAI and LLM-based applications, including model integration, fine-tuning, and optimization
</li><li>Apply systems-level knowledge to analyze, design, implement, and validate AI software, models, and system architecture
</li><li>Perform AI model benchmarking, functional analysis, and performance characterization to drive requirements and improvements
</li><li>Support customer engagements by optimizing AI models and workloads for deployment and inference efficiency
</li><li>Contribute to system-level design efforts, including requirements definition, interfaces, performance targets, and implementation
</li><li>Collaborate closely with cross-functional teams to implement, test, and validate AI system features
</li><li>Debug and triage system-level issues, perform root-cause analysis, and communicate findings clearly
</li><li>Stay current with advancements in AI/ML models, tools, and hardware, and apply innovative ideas to products and solutions
</li></ul>Preferred Qualifications:
<ul><li>Master&rsquo;s or PhD in Engineering, Computer Science, Information Systems, or a related field
</li><li>Proficiency in Python and experience with ML frameworks, APIs, REST services, and microservice-based architecture
</li><li>Hands-on experience building, deploying, and tuning AI/ML systems
</li><li>Strong understanding of GenAI architectures (e.g., transformers, diffusion models, LLMs, embeddings)
</li><li>Experience with large-scale AI system design, including distributed systems, fault tolerance, and event-driven architectures
</li><li>Familiarity with MLOps practices and ML lifecycle management
</li><li>Experience with containerization and automation tools (Docker, Kubernetes, Git/GitOps)
</li><li>Experience with model fine-tuning and/or reinforcement learning is a plus
</li><li>Familiarity with observability, benchmarking, and performance analysis for ML pipelines is a plus
</li><li>Experience working in large, matrixed organizations and collaborating across teams
</li><li>Strong problem-solving skills and customer-focused mindset
</li><li>Experience with open-source development practices
</li></ul>What's on Offer
Apart from working with great people, we offer the below:
<ul><li>Salary including housing &amp; transport allowance
</li><li>Stock (RSU's) and performance related bonus
</li><li>16 weeks fully paid Maternity Leave
</li><li>6 weeks fully paid Paternity Leave
</li><li>Employee stock purchase scheme
</li><li>Child Education Allowance
</li><li>Relocation and immigration support (if needed)
</li><li>Life and Medical Insurance
</li><li>Live+ Well Reimbursement for health and recreational membership fees
</li></ul></div>Minimum Qualifications:
<ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
</li></ul>OR
 
Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
 
OR
 
PhD in Engineering, Information Systems, Computer Science, or related field.
*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
<div>Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</div>Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
If you would like more information about this role, please contact Qualcomm Careers .</div>

Datacenter AI Solutions Engineer - Riyadh, KSA

Master Works

<div>
 
 Job Description:
 
 
 
 The charge of creating and developing intelligent solutions using Artificial Intelligence technologies with a focus on generative AI and data science.
 
 
 The role entails converting data into useful insights and developing AI powered applications that improve decision making and enhance operational efficiency.
 
 
 
 Tools &amp; Technologies:
 
 Dataiku, Sql server, Power bi, and aws bedrock
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Design, develop, train, and optimize machine learning models for real applications or use cases
 </li>
 <li>
 Translate business and product requirements into scalable ML/AI solutions
 </li>
 <li>
 Implement feature engineering, model selection, tuning, and evaluation techniques
 </li>
 <li>
 Develop, and deploy ML models into production environments with high availability and performance
 </li>
 <li>
 Build and maintain ML pipelines (training, validation, deployment, monitoring)
 </li>
 <li>
 Monitor model performance, data drift, and model decay; retrain models as needed
 </li>
 <li>
 Ensure models meet reliability, scalability, and security standards
 </li>
 <li>
 Work closely with Data Scientists, Product Managers, and Software Engineers
 </li>
 <li>
 Collaborate with data engineering teams to ensure high-quality, reliable data pipelines
 </li>
 <li>
 Participate in design and code reviews, ensuring engineering best practices
 </li>
 <li>
 Optimize models for latency, throughput, and cost
 </li>
 <li>
 Implement experimentation frameworks (A/B testing, offline evaluation)
 </li>
 <li>
 Apply responsible AI principles, including fairness, explainability, and governance where required
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Requirements &amp; Qualifications
 
 :
 
 
 <ul>
 <li>
 +4 years of hands-on experience in Machine Learning or applied AI roles
 </li>
 <li>
 Strong programming skills in Python (and/or Java, Scala)
 </li>
 <li>
 Solid understanding of ML algorithms (supervised, unsupervised, deep learning)
 </li>
 <li>
 Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn
 </li>
 <li>
 Experience deploying models using Docker, Kubernetes, or cloud ML services
 </li>
 <li>
 Strong knowledge of data structures, algorithms, and software engineering principles
 </li>
 <li>
 Experience working in agile, cross-functional teams
 </li>
 <li>
 Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services
 </li>
 <li>
 Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML)
 </li>
 <li>
 Experience with big data technologies (Spark, Kafka, Databricks)
 </li>
 <li>
 Background in NLP, Computer Vision, or Generative AI
 </li>
 <li>
 Strong problem-solving and analytical thinking
 </li>
 <li>
 Production-first mindset
 </li>
 <li>
 Data-driven decision making
 </li>
 <li>
 High Collaboration and communication skills
 </li>
 </ul>
</div>

AI developer

MASTER-WORKS

<div>Job Description:
The charge of creating and developing intelligent solutions using Artificial Intelligence technologies with a focus on generative AI and data science.
The role entails converting data into useful insights and developing AI powered applications that improve decision making and enhance operational efficiency.
Tools &amp; Technologies: Dataiku, Sql server, Power bi, and aws bedrock
Key Responsibilities:<ul><li>
Design, develop, train, and optimize machine learning models for real applications or use cases.</li><li>
Translate business and product requirements into scalable ML/AI solutions.</li><li>
Implement feature engineering, model selection, tuning, and evaluation techniques.</li></ul><ul><li>
Develop, and deploy ML models into production environments with high availability and performance.</li><li>
Build and maintain ML pipelines (training, validation, deployment, monitoring).</li><li>
Monitor model performance, data drift, and model decay; retrain models as needed.</li><li>
Ensure models meet reliability, scalability, and security standards.</li><li>
Work closely with Data Scientists, Product Managers, and Software Engineers.</li><li>
Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.</li><li>
Participate in design and code reviews, ensuring engineering best practices.</li><li>
Optimize models for latency, throughput, and cost.</li><li>
Implement experimentation frameworks (A/B testing, offline evaluation).</li><li>
Apply responsible AI principles, including fairness, explainability, and governance where required.</li></ul> 
Requirements 
Requirements &amp; Qualifications:<ul><li>
+4 years of hands-on experience in Machine Learning or applied AI roles.</li><li>
Strong programming skills in Python (and/or Java, Scala).</li><li>
Solid understanding of ML algorithms (supervised, unsupervised, deep learning).</li><li>
Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn.</li><li>
Experience deploying models using Docker, Kubernetes, or cloud ML services.</li><li>
Strong knowledge of data structures, algorithms, and software engineering principles.</li><li>
Experience working in agile, cross-functional teams.</li><li>
Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.</li><li>
Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).</li><li>
Experience with big data technologies (Spark, Kafka, Databricks).</li><li>
Background in NLP, Computer Vision, or Generative AI.</li><li>
Strong problem-solving and analytical thinking</li><li>
Production-first mindset</li><li>
Data-driven decision making</li><li>
High Collaboration and communication skills</li></ul></div>

MA'ADEN

<div>Job Purpose
Lead and develop end-to-end machine learning and Generative AI solutions, ensuring architectural integrity, technical excellence, and business alignment while mentoring team members and driving successful delivery. 
Key Accountabilities
<div><ul><li>Lead and actively develop ML, deep learning, and Generative AI solutions.
</li></ul><ul><li>Design and implement LLM-based applications including RAG pipelines and embeddings strategies.
</li></ul><ul><li>Own solution architecture from problem framing to production deployment.
</li></ul><ul><li>Establish MLOps and LLMOps practices for deployment, monitoring, and retraining.
</li></ul><ul><li>Define evaluation standards, guardrails, and AI safety controls.
</li></ul><ul><li>Mentor team members and drive cross-functional collaboration.
</li></ul><ul><li>Ensure compliance with data governance and responsible AI standards.
</li></ul></div>Minimum Qualification, Experience and Competencies
<div><ul><li>Minimum Qualification
</li></ul></div><ul><li>Bachelor&rsquo;s degree in Data Science, Artificial Intelligence, Computer Science, or a related quantitative field
</li></ul>Minimum Experience
<ul><li>7&ndash;9 years of experience in data science and AI, including leading end-to-end ML and Generative AI initiatives.
</li></ul>Skills:
<ul><li>Advanced ML &amp; deep learning
</li><li>LLM architecture design
</li><li>API orchestration &amp; system integration
</li><li>AI safety &amp; risk mitigation
</li><li>Enterprise AI deployment
</li><li>Cloud AI platforms (Azure, AWS, GCP)
</li><li>Technical leadership &amp; stakeholder engagement
</li><li>Solution architecture thinking</li></ul></div>

Lead Specialist, Data Science & Artificial Intelligence II

Gathern

<div>JOB PURPOSE: 
Lead the design, development, and scaling of advanced machine learning systems that power Gathern&rsquo;s marketplace intelligence across discovery, pricing, personalization, and trust domains. The role combines deep technical expertise with strategic thinking to translate complex data into production-grade predictive and decisioning systems. Focuses on architecting scalable ML infrastructure, ensuring model robustness and reliability, and driving measurable business impact through experimentation, optimization, and cross-functional leadership 
 
KEY ACCOUNTABILITIES:<ul><li>
Architect ML systems / end-to-end pipelines / scalable and production-ready solutions</li><li>
Lead model development/pricing and ranking algorithms / improved conversion and revenue yield</li><li>
Design forecasting solutions/demand and supply models / optimized inventory and occupancy planning</li><li>
Enhance risk models/fraud detection systems / reduce cancellations and policy violations</li><li>
Establish MLOps standards/deployment and monitoring frameworks / reliable and maintainable model operations</li><li>
Drive experimentation / A/B testing and validation frameworks / data-driven product improvements</li><li>
Collaborate cross-functionally / product, engineering, and data teams / aligned metrics and business impact</li><li>
Define data strategy/feature engineering and data sourcing / improved model performance and coverage</li><li>
Ensure model governance/data quality and integrity / trusted and compliant ML systems</li><li>
Mentor team members / technical guidance and best practices / elevated team capability and output quality</li><li>
Optimize model performance/tuning and retraining strategies / sustained accuracy and efficiency</li><li>
Evaluate new approaches/algorithms and technologies / continuous innovation and competitive advantage</li><li>
Communicate insights/model performance and impact / informed stakeholder decision-making.</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, or a related field</li></ul><ul><li>
5&ndash;8+ years of experience in applied machine learning, data science, or ML engineering roles</li><li>
Proven experience designing, deploying, and scaling ML systems in production environments</li><li>
Strong experience with large-scale data processing and distributed systems (e.g., Spark, Beam)</li><li>
Advanced proficiency in Python and ML frameworks such as TensorFlow or PyTorch</li><li>
Deep understanding of MLOps practices (CI/CD, model lifecycle management, feature stores, monitoring)</li><li>
Strong expertise in SQL and data engineering tools (Airflow, Kafka, DBT, etc.)</li><li>
Experience with experimentation frameworks and causal inference methods is a plus</li><li>
Strong system design and architecture skills for ML-driven products</li><li>
Excellent problem-solving skills with a strong analytical and business-oriented mindset</li><li>
Ability to lead initiatives, influence stakeholders, and mentor junior team members</li></ul></div>

Senior Machine Learning Engineer

Explore 160+ Ml engineer in Riyadh this April. Find roles across top companies and apply now to boost your career.

160 ml engineer jobs In Riyadh

Senior Data Engineer (Saudi National)

Infrastructure & Site Reliability Engineer – Datacentre AI Engineering - Riyadh, KSA

Datacenter AI Solutions Engineer - Riyadh, KSA

AI developer

AI developer

Lead Specialist, Data Science & Artificial Intelligence II

Senior Machine Learning Engineer