electrical engineer

property consultant

graphic designer

project engineer

qa/qc engineer

ai architect

MultiBank Group

<div>Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking a Senior AI Architect to design, build, and scale the AI and data platform that the organization's AI products will run on. This is a hands-on, founding technical position. The Senior AI Architect will produce architecture designs, write production code, build data pipelines, and set the engineering standards the broader AI team will follow. The role requires rare technical breadth: deep data engineering foundations, strong software engineering discipline, AI and ML systems experience, cloud infrastructure fluency, and the architectural vision to make it all coherent at enterprise scale.
Key Responsibilities<ul><li>
Design and build the end-to-end AI platform architecture, covering data ingestion, feature engineering, model training, serving, monitoring, and retraining as a coherent, maintainable production system</li><li>
Design the data lakehouse architecture on AWS using Delta Lake or Apache Iceberg with Databricks as the primary compute layer, and build batch and streaming data pipelines using PySpark, AWS Glue, and Kafka</li><li>
Architect and implement a feature store with online and offline stores, point-in-time joins, and feature versioning</li><li>
Own cloud infrastructure architecture for all AI and data workloads on AWS, including multi-account strategy, EKS cluster design, GPU compute, storage, and cost governance</li><li>
Build and own the MLOps platform covering experiment tracking, training pipeline automation, model packaging and deployment standards, CI/CD for ML, and model monitoring with drift detection</li><li>
Design the AI services layer, including reusable inference APIs, model serving infrastructure, and API gateway configuration with authentication, rate limiting, and cost attribution</li><li>
Integrate AI capabilities into the organization's products and business systems using event-driven and API-based patterns</li><li>
Embed security and compliance into every layer of the AI platform, including network security, IAM, PII handling, secrets management, and audit logging</li><li>
Act as the senior technical authority for the AI Initiative, setting engineering standards, mentoring engineers, and leading technical decisions</li><li>
Produce and maintain architecture documentation including C4 diagrams, Architecture Decision Records, and system integration maps</li></ul>
Requirements<ul><li>
15 or more years of experience spanning data engineering, software engineering, and AI/ML systems, with at least 3 to 5 years in a senior architecture role</li><li>
Demonstrable record of building and shipping production AI systems end-to-end, not solely designing them</li><li>
Deep hands-on data engineering background including production data pipelines, data lakehouses, and feature stores</li><li>
Expert-level AWS skills across multi-service architecture design and build; GCP or Azure familiarity is beneficial</li><li>
Strong software engineering discipline with production-quality Python and SQL, and solid understanding of distributed systems and API design</li><li>
Deep understanding of the AI and ML model lifecycle and the infrastructure required to support it at production scale</li><li>
Experience in high-growth product companies, scale-ups, or enterprise AI teams where significant technical decisions were owned</li><li>
Security-conscious approach as a default, with experience embedding data privacy and compliance requirements into architecture</li><li>
Strong written and verbal communication, including the ability to produce clear architecture documentation and present to senior leadership</li><li>
Experience leading or significantly contributing to technical team building, including mentoring and setting engineering standards</li><li>
Fintech experience is preferred</li></ul>
Technical Skills<ul><li>
Data Engineering and Platform: Python (primary), SQL, Scala, Bash; Apache Spark (PySpark), AWS Glue, dbt, Pandas, Polars; Apache Kafka (AWS MSK), AWS Kinesis, AWS EventBridge, Flink; Delta Lake, Apache Iceberg, AWS S3, Databricks (Unity Catalog); AWS Redshift, Databricks SQL, Snowflake; Feast, AWS SageMaker Feature Store, Tecton; Great Expectations, dbt tests, Soda Core; OpenMetadata, Apache Atlas; Metabase, Redash; Apache Airflow (Astronomer), Dagster, Prefect</li><li>
AI and ML Systems: PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM; AWS SageMaker Training, Kubeflow, Ray Train; BentoML, Seldon Core, Ray Serve, FastAPI, KServe; MLflow, Weights and Biases, ClearML; Evidently AI, Arize AI, WhyLabs; GitHub Actions, DVC, Great Expectations; Hugging Face (Transformers, Datasets, Evaluate, PEFT)</li><li>
Cloud and Infrastructure (AWS Primary): EKS (Karpenter), EC2 (G5, P4d GPU instances), SageMaker, Lambda, Fargate; S3, FSx for Lustre, ElastiCache (Redis), DynamoDB, RDS (PostgreSQL); SageMaker Pipelines, Feature Store, Model Registry, Bedrock, Comprehend, Textract; VPC, Transit Gateway, PrivateLink, Route 53, CloudFront, WAF; IAM (IRSA), Secrets Manager, KMS, Macie, GuardDuty, Security Hub, CloudTrail; Terraform, Terragrunt, CloudFormation, Pulumi; ArgoCD, Flux, Atlantis; Azure ML, Azure Databricks, Azure OpenAI Service (secondary)</li><li>
API, Integration and Solution Architecture: FastAPI, gRPC, REST (OpenAPI 3.1), GraphQL; Kong, AWS API Gateway, Istio (service mesh, mTLS); Docker, Kubernetes (Helm, Kustomize); C4 Model (Structurizr), ADRs, draw.io, Lucidchart; AWS Cost Explorer, Grafana cost dashboards, per-product token attribution</li><li>
Third-Party Data Integrations: Segment, Amplitude, Adjust, Firebase, MoEngage, JourneyFi, Funnel, Debezium, AWS DMS, Fivetran</li><li>
Security and Compliance: OAuth 2.0, JWT, AWS Cognito, mTLS, AWS SSO; AWS Secrets Manager (auto-rotation), HashiCorp Vault; Microsoft Presidio (PII detection), AWS Macie, field-level KMS encryption; NIST AI RMF, GDPR, ISO 27001, SOC 2; Model cards, Fairlearn (bias evaluation), SHAP (explainability), audit logging</li></ul>
Why Join Us?<ul><li>
Work with one of the world&rsquo;s leading financial derivatives institutions.</li><li>
Competitive salary plus performance-based incentives.</li><li>
Access to a dynamic, international, and fast-growing environment.</li><li>
Strong opportunities for career progression within a global financial group.</li><li>
Be part of a business committed to innovation, excellence, and long-term growth.</li></ul>
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.</div>

Senior AI Architect

<div>
 
 We help the world run better
 
 
 
 At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging &ndash; but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
 
 
 
 What You'll Build
 
 
 
 <ul>
 <li>
 In this role, you'll define the architecture for intelligent, enterprise-grade applications and platforms with AI built into the core design rather than added as an afterthought.
 </li>
 <li>
 You'll shape end-to-end solutions across application services, integration layers, data architecture, event-driven systems, security, and AI/ML components. That includes designing patterns for model integration, batch and real-time inference, feature and data pipelines, vector search, LLM orchestration, agent frameworks, evaluation services, and responsible AI controls.
 </li>
 <li>
 You&rsquo;ll guide teams on scalability, resilience, interoperability, observability, privacy, and compliance, and ensure architecture choices support both near-term delivery and long-term platform evolution.
 </li>
 <li>
 Your work will directly influence how quickly engineering teams can build, govern, and scale AI-enabled capabilities across products and customer scenarios.
 
 
 </li>
 </ul>
 
 What You Bring
 
 
 
 <ul>
 <li>
 You bring deep expertise in software architecture for large-scale distributed systems, including microservices, event-driven patterns, APIs, integration layers, and data platforms
 </li>
 <li>
 You have a strong understanding of AI and ML system architecture, including training pipelines, inference layers, model lifecycle design, and ML platform capabilities
 </li>
 <li>
 You have experience designing enterprise-grade generative AI solutions using LLMs, embeddings, vector databases, RAG patterns, tool use, and orchestration frameworks
 </li>
 <li>
 You are skilled at designing scalable and secure application architectures that integrate transactional systems, analytical platforms, and AI-powered services
 </li>
 <li>
 You have strong knowledge of cloud-native architecture, including containers, Kubernetes, infrastructure automation, observability, resilience, and performance engineering
 </li>
 <li>
 You have experience defining reference architectures, design standards, and reusable technical patterns for AI-enabled product development
 </li>
 <li>
 You bring a strong understanding of data architecture, governance, metadata, privacy, and access patterns required to support trustworthy AI solutions
 </li>
 <li>
 You evaluate build-versus-buy decisions across models, platforms, data services, and integration tooling, clearly articulating technical and business trade-offs
 </li>
 <li>
 You have knowledge of responsible AI, model governance, security controls, compliance requirements, and architectural guardrails for safe enterprise adoption
 </li>
 <li>
 You have experience leading architecture reviews, influencing engineering roadmaps, and aligning technical direction across multiple teams or product areas
 </li>
 <li>
 You communicate complex architectural decisions clearly to engineers, product leaders, and executive stakeholders
 
 
 </li>
 </ul>
 
 About You
 
 
 
 <ul>
 <li>
 You bring 6+ years of experience in software engineering, architecture, or a related field, with a strong track record of designing and delivering complex systems
 </li>
 <li>
 You think in systems, with a strong ability to connect architecture decisions to broader platform strategy and business outcomes
 </li>
 <li>
 You are a technical leader who influences without authority and drives alignment across teams and organizations
 </li>
 <li>
 You are passionate about building robust, extensible systems that stand the test of time
 </li>
 <li>
 You stay current with emerging technologies, particularly in AI, cloud, and distributed systems
 
 
 </li>
 </ul>
 
 Where You Belong
 
 
 
 You will be part of a growing AI and industry expert team dedicated to serving customers across the Kingdom of Saudi Arabia / United Arab Emirates. We are building a collaborative, high‑impact environment that brings together deep AI expertise, strong industry knowledge, and regional understanding to help customers innovate, transform, and lead in their markets.
 
 
 This team thrives on working together to turn complex business challenges into practical, scalable solutions. You will find an environment that values curiosity, ownership, and continuous learning, where new ideas are encouraged and real‑world impact matters. This is a place for people who enjoy building something new. You will thrive here if you are customer‑centric, motivated by meaningful outcomes, and comfortable navigating ambiguity in a fast‑evolving AI landscape.
 
 
 
 About The Team
 
 
 
 We work across boundaries, help teams make better design choices, and build foundations that let AI products scale safely and efficiently. We value clarity, system thinking, and practical innovation.
 
 
 
 Bring out your best
 
 
 
 SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
 
 
 
 We win with inclusion
 
 
 
 SAP&rsquo;s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone &ndash; regardless of background &ndash; feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.
 
 
 SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.
 
 
 For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.
 
 
 Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.
 
 
 Successful candidates might be required to undergo a background verification with an external vendor.
 
 
 
 AI Usage in the Recruitment Process
 
 
 
 For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
 
 
 Please note that any violation of these guidelines may result in disqualification from the hiring process.
 
 
 Requisition ID: 450270 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations:
 
 
</div>

AI Architect

NVIDIA

<div>NVIDIA is looking for a Senior Solutions Architect, Customer Success to join its NVIDIA Infrastructure Specialist Team. Academic and commercial organizations around the world are using NVIDIA products to redefine deep learning and data analytics, and to power next-generation data centers. Join the team building and advising on many of the largest and fastest AI/HPC systems in the world!
We are looking for someone who blends deep technical expertise with a consultative, collaborative approach. This role will engage directly with customers, partners, and multi-functional internal teams to assess infrastructure needs, architect scalable solutions, and guide the implementation of large-scale networking and AI infrastructure projects. The scope spans networking, system design, and automation&mdash;serving as a trusted strategic advisor and the technical face of NVIDIA to key accounts.
What You&rsquo;ll Be Doing:<ul><li>
Serve as a senior technical authority and trusted consultant on NVIDIA technologies, contributing to architecture reviews, guiding infrastructure decisions at scale, and providing strategic recommendations aligned with each customer&rsquo;s business objectives.</li><li>
Establish and refine monitoring and optimization methodologies using analytics, telemetry, and automation to proactively detect bottlenecks, improve infrastructure resiliency, and drive continuous operational maturity.</li><li>
Lead and advise on the analysis, optimization, and performance tuning of complex GPU-accelerated systems and AI workloads, ensuring high availability and efficiency across customer data centers.</li><li>
Facilitate post-deployment reviews, incident retrospectives, and strategy sessions to shape the customer experience and deliver actionable insights into NVIDIA&rsquo;s infrastructure roadmap.</li><li>
Own and lead complex technical projects end-to-end&mdash;from initial discovery and solution design through implementation, knowledge transfer, and continuous improvement&mdash;ensuring alignment to SLAs and proactive mitigation of technical risks.</li><li>
Support business growth by identifying AI infrastructure opportunities in cloud and enterprise environments, crafting compelling technical proposals, and driving initiatives that showcase NVIDIA&rsquo;s leadership in this space.</li></ul> 
What We Need to See:<ul><li>
Education &amp; Experience: BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, with 10+ years of professional experience in large-scale data center service operations with a focus on infrastructure.</li><li>
NVIDIA GPU Expertise: Demonstrated hands-on experience deploying, configuring, and optimizing NVIDIA GPU-accelerated infrastructure, including driver and firmware management, CUDA toolkit integration, and GPU workload profiling and fix.</li><li>
Customer Engagement: Track record of building long-term customer relationships and driving adoption through consultative engagement.</li><li>
Analytical &amp; Problem-Solving Skills: Strong analytical and decision-making capabilities, with a demonstrable ability to identify root causes, drive continuous improvement, and deliver resilient technical solutions.</li><li>
System &amp; Infrastructure Proficiency: Expertise in end-to-end data center architecture, spanning operating systems, Linux kernel drivers, GPU and NIC hardware, high-speed networking (InfiniBand, Ethernet, RDMA), and storage systems (Lustre, GPFS, NFS).</li><li>
Leadership &amp; Communication: Good communication, time management, and organizational skills, with the ability to lead complex multi-functional projects, guide technical teams, and present to executive partners.</li><li>
Travel: Willingness to travel up to 25% for customer engagements.</li></ul> 
Ways to Stand Out from the Crowd:<ul><li>
Experience with Kubernetes for container orchestration, resource scheduling, and integration with GPU-accelerated workloads.</li><li>
Familiarity with observability stacks (Grafana, Prometheus, Loki) for monitoring, alerting, and building fault-tolerant systems.</li><li>
Experience with multi-tenant GPU cluster management and workload scheduling frameworks.</li><li>
Experience with NVIDIA Base Command Manager (BCM) for provisioning, managing, and monitoring GPU clusters at scale.</li><li>
Background with RDMA-based fabrics (InfiniBand or RoCE) in HPC or AI environments as well as knowledge of CI/CD pipelines, Infrastructure-as-Code (Terraform, Ansible), and GitOps workflows for infrastructure automation.</li></ul></div>

Senior Solutions Architect, Customer Success

<div>Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking a Senior Machine Learning Engineer to join our AI team as a technical owner of ML products and infrastructure. This is a deeply hands-on engineering position for someone who builds and scales production AI systems used by real users in real-time environments. The right candidate operates across the full ML lifecycle &mdash; from model design through deployment, optimization, and ongoing performance in production &mdash; and contributes to the technical direction of the AI platform.
Key Responsibilities<ul><li>
Architect and implement robust ML systems in production environments, ensuring scalability, reliability, and performance from day one</li><li>
Build and deploy supervised, unsupervised, deep learning, and generative AI models into live production environments at scale</li><li>
Own technical design for ML pipelines, feature stores, training infrastructure, and inference systems, driving decisions that balance performance, cost, and maintainability</li><li>
Design and deliver RAG systems, fine-tuning pipelines, prompt engineering frameworks, and evaluation pipelines for production-grade LLM applications</li><li>
Implement and maintain CI/CD for ML, model versioning, monitoring, drift detection, and automated retraining pipelines</li><li>
Continuously optimize model performance, inference latency, cost efficiency, and reliability across live systems</li><li>
Collaborate with product managers, engineers, and data teams to translate business problems into scalable, maintainable AI solutions</li><li>
Mentor junior and mid-level ML engineers, establish best practices, and contribute to technical standards across the team</li><li>
Contribute to strategic decisions around data architecture, AI infrastructure, and cloud platform direction</li><li>
Work with mobile attribution and customer engagement data sources including Adjust, MoEngage, and Firebase for ML use cases such as churn prediction, personalization, and campaign optimization</li></ul>
Requirements<ul><li>
7 to 15 or more years of experience in software engineering, data science, or ML engineering</li><li>
Strong background in product companies, scale-ups, or enterprise AI platforms</li><li>
Proven track record of building production-grade AI systems, not solely notebooks or proof-of-concept work</li><li>
Comfortable owning systems end-to-end from data through model through deployment through monitoring</li><li>
Product-first engineering approach, not research-only profiles</li><li>
Advanced Python engineering skills with strong systems thinking and a focus on production quality</li><li>
Comfortable with fast iteration cycles and deploying models into live environments</li><li>
Ability to work directly and confidently with stakeholders and product owners</li><li>
Fintech or financial services experience is an advantage</li></ul>
Technical Skills
Machine Learning and AI: PyTorch, TensorFlow, XGBoost, LightGBM, Hugging Face (Transformers, Datasets, Diffusers)
LLM and GenAI: OpenAI and Anthropic APIs, LangChain, LlamaIndex; RAG architectures with vector DB and retrieval pipelines; embedding models (OpenAI, Cohere, open-source); Pinecone, Weaviate, Milvus, FAISS; fine-tuning via LoRA and PEFT frameworks; evaluation using RAGAS and custom pipelines
MLOps and Production: Docker, Kubernetes, MLflow, Weights and Biases, Airflow, Dagster, Prefect, GitHub Actions, GitLab CI, Evidently AI, Arize, custom observability stacks
Cloud: AWS (SageMaker, EKS, S3, Lambda), Azure ML, Azure Databricks, GCP
Data Stack: Databricks, Spark, PySpark, Delta Lake, Apache Iceberg, Lakehouse architectures
Why Join Us?<ul><li>
Work with one of the world&rsquo;s leading financial derivatives institutions.</li><li>
Competitive salary plus performance-based incentives.</li><li>
Access to a dynamic, international, and fast-growing environment.</li><li>
Strong opportunities for career progression within a global financial group.</li><li>
Be part of a business committed to innovation, excellence, and long-term growth.</li></ul>
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.</div>

Senior Machine Learning Engineer

<div>Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking an AI Engineer to design, build, and deploy intelligent AI agents and automated workflows that address real business problems. This is a hands-on, high-impact role within the Artificial Intelligence and Advanced Analytics team. The successful candidate will own end-to-end delivery of AI agents from scoping and architecture through integration, testing, and production deployment, enabling the organization to automate complex processes and unlock value from generative AI.
Key Responsibilities<ul><li>
Design, build, and deploy AI agents using frontier LLMs including Claude (Anthropic API), OpenAI, Gemini, and other frontier models</li><li>
Architect multi-agent systems and agentic workflows using frameworks including LangChain, LangGraph, CrewAI, AutoGen, and Semantic Kernel</li><li>
Build and manage automated business workflows using n8n, Make (Integromat), Zapier, and custom API integrations</li><li>
Implement RAG pipelines with vector databases including Pinecone, Weaviate, Qdrant, and pgvector to give agents access to organizational knowledge bases</li><li>
Design tool-use and function-calling integrations, connecting agents to internal systems, APIs, databases, and third-party services</li><li>
Fine-tune and prompt-engineer LLMs to optimize agent behavior, reliability, and task accuracy</li><li>
Collaborate with business stakeholders to identify automation opportunities and translate requirements into agent-based solutions</li><li>
Monitor, evaluate, and continuously improve deployed agents across quality, latency, cost, and safety metrics</li><li>
Establish and maintain best practices for agent safety, guardrails, human-in-the-loop controls, and responsible AI deployment</li><li>
Develop MCP (Model Context Protocol) server integrations to extend agent capabilities</li></ul>
Requirements<ul><li>
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field; equivalent practical experience will be considered</li><li>
2 or more years of hands-on experience building production AI systems or intelligent automation solutions</li><li>
Demonstrated experience building agents or workflows with LangChain, LangGraph, CrewAI, n8n, or comparable frameworks</li><li>
Proven ability to integrate LLM APIs including Anthropic Claude and OpenAI into real-world applications</li><li>
Experience with vector databases and semantic search implementations is strongly preferred</li><li>
Portfolio or demonstrable projects showing deployed agents, automation workflows, or RAG-based applications</li><li>
Proficiency in Python as the primary language; JavaScript or TypeScript is beneficial</li><li>
Familiarity with cloud platforms, Docker, FastAPI, and CI/CD practices for AI pipelines</li></ul>
Technical Skills
LLM APIs: Anthropic Claude (claude-opus-4, claude-sonnet-4), OpenAI GPT-4o, Google Gemini, Mistral
Agent Frameworks: LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, Haystack
Workflow Automation: n8n, Make (Integromat), Zapier, Apache Airflow
Vector Databases and RAG: Pinecone, Weaviate, Qdrant, pgvector, Chroma, LlamaIndex
Programming: Python (primary), JavaScript/TypeScript, REST API design
Cloud and MLOps: AWS, Azure, GCP, Docker, FastAPI, CI/CD for AI pipelines
Observability and Evaluation: LangSmith, Helicone, Weights and Biases, custom evaluation harnesses
AI Agent Focus Areas<ul><li>
Autonomous and semi-autonomous agents for customer service, operations, marketing, and data analysis</li><li>
Multi-agent orchestration including planner, executor, critic, and memory agent patterns</li><li>
Knowledge retrieval systems including enterprise RAG, document Q&amp;A, and semantic search</li><li>
Process automation integrating CRM, ERP, and communication tools end-to-end</li><li>
Agent safety, guardrails, and human-in-the-loop oversight mechanisms</li><li>
MCP server development for extending agent capabilities</li></ul>
Soft Skills<ul><li>
Strong problem-solving ability and analytical thinking</li><li>
Ability to translate complex business needs into practical technical solutions</li><li>
Effective collaboration and communication in a team-oriented environment</li><li>
Intellectual curiosity and commitment to staying current with AI research and trends</li></ul>
Why Join Us?<ul><li>
Work with one of the world&rsquo;s leading financial derivatives institutions.</li><li>
Competitive salary plus performance-based incentives.</li><li>
Access to a dynamic, international, and fast-growing environment.</li><li>
Strong opportunities for career progression within a global financial group.</li><li>
Be part of a business committed to innovation, excellence, and long-term growth.</li></ul>
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.</div>

AI Engineer – Generative AI and Automation

Tether Operations Limited

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
We are developing a highly scalable media intelligence platform that processes, analyzes, and structures large volumes of multimedia content across text, image, video, and audio. As a Senior Applied ML Engineer, you will architect and build the core backend systems that power media ingestion, processing workflows, metadata generation, AI-based analysis, semantic search, and retrieval across large media libraries.
We are looking for a Senior Applied ML Engineer who can design, implement, optimize, and evaluate a production-grade moderation pipeline using open-source models.
This role requires deep backend engineering expertise, strong system design capability, and practical experience integrating AI/ML systems into production workflows. You will work on complex media-processing pipelines, video/audio analysis, OCR, speech-to-text, embedding generation, vector search, multimodal model integrations, and high-throughput asynchronous workloads. You will collaborate closely with engineering leadership to define backend architecture, improve reliability and scalability, and guide other engineers in delivering secure, observable, and high-performance systems.
Responsibilities
Backend Architecture &amp; System Ownership<ul><li>
Architect, build, and operate scalable backend services for a media intelligence platform, with a focus on clean, maintainable, and production-ready systems.</li><li>
Own critical backend components end to end, from system design and API contracts through implementation, deployment, monitoring, and iteration.</li><li>
Drive architectural decisions across APIs, processing pipelines, distributed compute, storage, search, observability, cloud infrastructure, and model-serving workflows.</li><li>
Design data models and storage patterns for media assets, generated metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails.</li><li>
Design high-throughput media ingestion and processing pipelines for large volumes of video, audio, image, and text content.</li><li>
Build distributed, event-driven workflows for media processing using queues and pub/sub systems such as SQS, Kafka, Pub/Sub, or equivalent technologies.</li><li>
Implement reliable asynchronous processing patterns, including retries, idempotency, dead-letter queues, backpressure handling, and fault-tolerant job execution.</li></ul>
AI/ML Integration &amp; Model Workflows<ul><li>
Lead the development and optimization of metadata extraction, content analysis, scene detection, transcription, embedding generation, and multimodal AI inference workflows.</li><li>
Integrate and optimize AI/ML services within backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene analysis, multimodal inference, batching, caching, and fallback strategies.</li><li>
Collaborate with ML engineers, data scientists, or external model providers to benchmark models, compare quality/latency trade-offs, and safely roll out model upgrades.</li></ul>
Model Serving &amp; Performance Optimization<ul><li>
Optimize AI/ML inference workflows for latency, throughput, reliability, and cost across both real-time and batch-processing paths.</li><li>
Work with model-serving systems such as vLLM, Triton, TGI, SageMaker, Vertex AI, or custom inference services to improve batching, concurrency, warmup behavior, timeout handling, autoscaling, and GPU utilization.</li><li>
Evaluate and apply practical model optimization techniques such as quantization, model distillation, batching, caching, prompt optimization, and routing to smaller or cheaper models where appropriate.</li><li>
Design and maintain vector search and indexing systems using technologies such as Pinecone, Weaviate, Qdrant, Elastic Vectors, FAISS, pgvector, or similar tools.</li><li>
Build retrieval workflows that support semantic search, similarity matching, duplicate detection, media discovery, and structured metadata search.</li><li>
Monitor model and system performance in production, including API latency, queue depth, processing time, model error rates, GPU utilization, confidence distributions, drift signals, and cost per processed item.Search, Indexing &amp; Data Retrieval</li></ul>
Infrastructure, Reliability &amp; Observability<ul><li>
Deploy and operate systems on AWS, GCP, Azure, or equivalent cloud platforms, including compute, storage, networking, queues, model-serving infrastructure, and monitoring systems.</li><li>
Ensure system reliability through logging, metrics, tracing, alerting, dashboards, operational runbooks, and incident-response best practices.</li></ul>
Collaboration &amp; Engineering Leadership<ul><li>
Collaborate with product, design, data, and ML teams to deliver media-rich, AI-powered product features.</li><li>
Mentor junior and mid-level engineers, support technical planning, review designs, and raise engineering quality across the team.</li><li>
Participate in code reviews, documentation, technical planning, and continuous improvement of engineering practices.</li><li>
Ensure code quality through testing, peer review, clear documentation, and maintainable implementation patterns.</li></ul> 
Education &amp; Experience<ul><li>
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.</li><li>
5-7+ years of backend engineering experience, ideally building scalable distributed systems, media platforms, data pipelines, or high-throughput backend services.</li><li>
Prior experience owning major backend modules end to end, including architecture, implementation, deployment, monitoring, and production operations.</li><li>
3 + years of experience integrating AI/ML inference systems into backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene detection, or multimodal model outputs.</li><li>
Hands-on experience creating AI-powered processing pipelines for image, video, audio, or text analysis.</li><li>
Practical experience with production model optimization, especially for image, video, embedding, or multimodal models, including batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost optimization.</li><li>
Prior experience with vector search, semantic search, media retrieval, or similarity-matching systems is strongly preferred.</li><li>
Experience mentoring engineers, leading technical discussions, and influencing architectural decisions across backend, infrastructure, and AI/ML workflows.</li></ul>
Technical Skills<ul><li>
Strong expertise in Python and/or Node.js with Deep understanding of building scalable RESTful APIs and backend architectures</li><li>
Experience with HuggingFace transformers ecosystem and deep learning frameworks such as PyTorch and TensorFlow.</li><li>
Strong experience with SQL/NoSQL databases, schema design, and data modeling</li><li>
Preferred Exposure to distributed systems, microservices, asynchronous processing, and event-driven patterns with SQS, Pub/Sub, Kafka, or other queueing/pub-sub systems</li><li>
Experience deploying production systems on AWS, GCP, or similar cloud platforms</li><li>
Knowledge of infrastructure patterns (compute, storage, networking, observability)</li></ul>
AI/ML Integration<ul><li>
Experience orchestrating embedding generation, scene detection, OCR, speech-to-text, image classification, video analysis, and multimodal model integrations.</li><li>
Experience optimizing inference workflows for latency, throughput, reliability, and cost.</li><li>
Experience working with scalable and optimized inference settings, including tuning sampling parameters, managing output‑length formats, and configuring reasoning‑related behaviors.</li><li>
Familiarity with practical model optimization techniques such as batching, caching, quantization, model distillation, prompt optimization, fallback routing, and use of smaller models where appropriate.</li><li>
Experience working with model-serving systems such as vLLM, Triton, TGI, SageMaker, Vertex AI, or custom inference services is preferred.</li><li>
Experience working with LLM and Multi-modal evaluation and benchmarking frameworks and domain‑specific benchmarks with the ability to interpret results and optimize model performance accordingly.</li></ul>
System Design &amp; Architecture<ul><li>
Preferred understanding of distributed systems, scaling patterns, and performance engineering</li><li>
Ability to design modular, maintainable, and efficient architectures</li><li>
Experience with API versioning, modularization, and designing long-running workflows</li><li>
Understanding of performance bottlenecks and low-latency backend patterns</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

Machine Learning Systems Engineer

COBBLESTONE

<div>Employment Type: Full-time &amp; Permanent

Location: Dubai, UAE (Visa sponsorship and relocation assistance provided)

Annual Base Salary: range of $80,000 - $110,000 per annum + performance-based bonus - 0% tax environment + opportunity to join our employee share scheme

Annual Leave: 30 Calendar Days

Public Holidays: As declared by UAE Government annually (8 to 14 days)

Working Days: Monday &ndash; Friday

Probation Period: 3 to 6 Months (As per UAE Labour Law)

Health Insurance: Comprehensive Private Health Insurance (IPD, OPD &amp; Dental)

Residency Visa Sponsorship: Provided by the Company

Relocation Support: Available for candidates relocating to Dubai

End of Service Gratuity: As per UAE Labour Law 

About Cobblestone Energy

Cobblestone Energy is an energy trading company specialising in the European Gas, Power and Emissions markets. Established in 2018, we combine deep analytics, advanced data science and agile technology to drive profitable trading decisions. Our flat organisational structure empowers every team member with autonomy and ownership. Our diverse global team of extraordinary talent is united by a relentless pursuit of excellence. 

Cobblestone Values
<ul>
<li>Excellence in Hiring &amp; Teamwork</li>
<li>Lifelong Learning Through Continuous Reflection</li>
<li>Independent Thinking Through a Meritocracy of Ideas</li>
<li>Winning</li></ul> 
 
Role Description:

We are seeking a highly motivated and talented Data Scientist to join our dynamic team. With a passion for data-driven solutions and a strong academic background, the successful candidate will play a critical role in shaping business decisions and driving operational excellence through advanced analytics, predictive modelling, and the strategic implementation of Generative AI/LLM technologies. 

What we offer in this role
<ul>
<li>A full-time, high-impact position within our dynamic Commercial team.</li>
<li>A team of exceptional colleagues, committed to continuous learning and pushing the boundaries of what's possible.</li>
<li>A career that challenges you to solve complex problems and rewards your drive for continuous innovation.</li>
<li>A unique opportunity to work on impactful projects, making independent decisions that drive real-world outcomes.</li>
<li>The chance to take full ownership of new projects, making high-impact decisions in a dynamic environment.</li>
<li>Equity participation, ensuring long-term alignment</li></ul> 
 
Key Responsibilities:
<ul>
<li>Analyse large, complex datasets to generate actionable insights that inform trading and commercial decisions.</li>
<li>Develop, deploy, and maintain predictive models to support market forecasting and trading strategy optimisation (e.g., time-series models, regression, tree-based methods).</li>
<li>Architect and implement production-ready AI/LLM solutions, such as Retrieval-Augmented Generation (RAG) pipelines or task-specific agents, integrated programmatically into analytical workflows (e.g., via APIs, LangChain, LlamaIndex).</li>
<li>Build, automate, and own end-to-end data workflows covering data ingestion, cleaning, feature generation, and model training, leveraging tools such as Python, SQL, Airflow, pandas, and workflow orchestration platforms (e.g., n8n or similar).</li>
<li>Apply advanced data science techniques, including synthetic data generation where appropriate, to improve model robustness, scalability, and operational efficiency.</li>
<li>Collaborate closely with traders and cross-functional stakeholders to translate business problems into high-quality, data-driven solutions.</li>
<li>Communicate insights and model outputs clearly and concisely, ensuring analytical work drives measurable trading and commercial impact.</li></ul> 
 
Requirements:
<ul>
<li>2-3 years of experience in data science or a related field, with a demonstrated record of achieving exceptional results.</li>
<li>Strong academic background in computer science, mathematics, statistics, or a related field</li>
<li>Outstanding problem-solving and critical thinking skills, capable of addressing complex, high-impact challenges.</li>
<li>Expertise in Python programming, with an ability to apply it to advanced data science problems.</li>
<li>Applied AI Proficiency: Demonstrated practical experience programmatically integrating LLMs (via APIs or frameworks like LangChain/LlamaIndex) into data pipelines or analytical applications.</li>
<li>Automation Focus: Proven ability to design and implement automated, end-to-end data workflows that leverage AI for efficiency gains.</li>
<li>Knowledge of machine learning algorithms and data visualization tools</li>
<li>Exceptional communication and collaboration skills, with a demonstrated ability to excel in fast-paced, cross-functional environments</li>
</ul>
This is an outstanding opportunity for a driven and talented Data Scientist to join an innovative trading company and make a significant impact on our business operations. If you possess a passion for data science and a proven track record of success, we encourage you to apply.

Note: Experience in the power trading domain is highly desirable but not essential. We value exceptional talent and the ability to learn quickly. 


Learn more about Cobblestone Energy careers: 
https://cobblestoneenergy.com/careers/

Why work with us: 
https://cobblestoneenergy.com/why-work-with-us/

Recruitment process: 
https://cobblestoneenergy.com/careers/vacancies/#process</div>

Data Scientist - Dubai, UAE

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