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MASTER-WORKS

<div>We are seeking a talented and motivated AI Engineer with expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and Speech-to-Text technologies. 
As part of our dynamic team, you will design, develop, and deploy next-generation AI solutions that enhance our products and services through intelligent automation, language understanding, and seamless communication systems.
Key Responsibilities
LLM Development &amp; Integration<ul><li>
Fine-tune and deploy Large Language Models for chatbots, content generation, and virtual assistants.</li><li>
Evaluate and optimize model performance in real-world use cases.</li><li>
Integrate LLMs into production environments ensuring scalability and reliability.</li></ul>
NLP System Design<ul><li>
Design and implement NLP algorithms for text classification, sentiment analysis, entity recognition, and summarization.</li><li>
Handle large text datasets for model training and validation.</li><li>
Collaborate with cross-functional teams to address language-related challenges.</li></ul>
Speech-to-Text Implementation<ul><li>
Develop and optimize speech-to-text (ASR) pipelines for multiple languages and dialects.</li><li>
Integrate speech recognition systems with NLP and LLM modules for end-to-end conversational experiences.</li><li>
Stay updated with advancements in Automatic Speech Recognition (ASR) technologies.</li></ul>
Performance Optimization<ul><li>
Improve AI model efficiency for real-time performance and scalability.</li><li>
Identify and mitigate biases to ensure model accuracy, fairness, and robustness.</li></ul>
Research &amp; Innovation<ul><li>
Stay current with cutting-edge research in LLMs, NLP, and Speech AI.</li><li>
Experiment with new architectures and techniques to drive innovation.</li></ul>
Documentation &amp; Collaboration<ul><li>
Maintain detailed documentation of models, datasets, and workflows.</li><li>
Collaborate with product managers, software engineers, and other stakeholders to deliver production-grade AI solutions.</li></ul> 
Requirements 
Qualifications<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or related fields.</li><li>
Proven experience in LLM development (e.g., OpenAI GPT, Claude, or similar frameworks).</li><li>
Strong knowledge of NLP libraries (e.g., Hugging Face, spaCy, NLTK).</li><li>
Hands-on experience with speech-to-text tools (e.g., Whisper, Google Speech API, DeepSpeech).</li><li>
Proficiency in Python and frameworks like TensorFlow or PyTorch.</li><li>
Excellent analytical, problem-solving, and communication skills.</li></ul></div>

AI Engineer (Mid-Level)

<div>We are seeking a talented and motivated AI Engineer with expertise in Large Language Models
(LLMs), Natural Language Processing (NLP), and Speech-to-Text technologies.
As part of our dynamic team, you will design, develop, and deploy next-generation AI solutions
that enhance our products and services through intelligent automation, language
understanding, and seamless communication systems.
Key Responsibilities
LLM Development &amp; Integration
 Fine-tune and deploy Large Language Models for chatbots, content generation, and
virtual assistants.
 Evaluate and optimize model performance in real-world use cases.
 Integrate LLMs into production environments ensuring scalability and reliability.
NLP System Design
 Design and implement NLP algorithms for text classification, sentiment analysis, entity
recognition, and summarization.
 Handle large text datasets for model training and validation.
 Collaborate with cross-functional teams to address language-related challenges.
Speech-to-Text Implementation
Develop and optimize speech-to-text (ASR) pipelines for multiple languages and
dialects.
 Integrate speech recognition systems with NLP and LLM modules for end-to-end
conversational experiences.
 Stay updated with advancements in Automatic Speech Recognition (ASR) technologies.
Performance Optimization
Improve AI model efficiency for real-time performance and scalability.
 Identify and mitigate biases to ensure model accuracy, fairness, and robustness.
Research &amp; Innovation
Stay current with cutting-edge research in LLMs, NLP, and Speech AI.
 Experiment with new architectures and techniques to drive innovation.
Documentation &amp; Collaboration
 Maintain detailed documentation of models, datasets, and workflows.
 Collaborate with product managers, software engineers, and other stakeholders to
deliver production-grade AI solutions. 
 
 
Requirements 
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science,
or related fields.
 Proven experience in LLM development (e.g., OpenAI GPT, Claude, or similar
frameworks).
 Strong knowledge of NLP libraries (e.g., Hugging Face, spaCy, NLTK).
 Hands-on experience with speech-to-text tools (e.g., Whisper, Google Speech API,
DeepSpeech).
 Proficiency in Python and frameworks like TensorFlow or PyTorch.
 Excellent analytical, problem-solving, and communication skills.</div>

Technical Lead

<div>Design, develop, and deploy Arabic-first Large Language Model (LLM) solutions to support AI-driven products and client projects, ensuring high-quality Arabic language understanding, generation, and contextual accuracy across enterprises.
Key Responsibilities1. LLM Development &amp; NLP (Core)<ul><li>
Design and fine-tune LLMs for Arabic language tasks
</li><li><ul><li>Text generation, classification, summarization
</li><li>Arabic grammar correction, dialect handling
</li></ul></li><li>Build and optimize RAG pipelines
</li><li>Develop prompt engineering strategies for Arabic + English contexts
</li></ul>2. Data &amp; Arabic Language Engineering<ul><li>
Build and curate Arabic datasets
</li><li>Handle:
</li><li><ul><li>Dialects (Gulf, MSA, etc.)
</li><li>Data cleaning, normalization
</li></ul></li><li>Define evaluation benchmarks for Arabic LLM quality
</li></ul>3. AI System Architecture<ul><li>
Develop LLM-powered systems using:
</li><li><ul><li>LangChain / LangGraph / Llama / OpenAI APIs
</li><li>Vector databases (ChromaDB, FAISS, etc.)
</li></ul></li><li>Integrate LLMs into:
</li><li><ul><li>APIs
</li><li>Enterprise systems
</li><li>AI agents / copilots
</li></ul></li></ul>4. Production &amp; MLOps<ul><li>
Deploy scalable AI systems using:
</li><li><ul><li>Docker, Kubernetes
</li><li>Cloud platforms (Azure, AWS, GCP)
</li></ul></li><li>Optimize:
</li><li><ul><li>Latency
</li><li>Cost
</li><li>Throughput
</li></ul></li></ul>5. Cross-functional Collaboration<ul><li>
Work with:
</li><li><ul><li>PMs (scope, delivery, timelines)
</li><li>BAs (requirements translation AI logic)
</li><li>QA (model validation &amp; test cases)
</li></ul></li><li>Support client demos and AI solution design
</li></ul>6. Governance Alignment (Critical for Nabeh)<ul><li>
Ensure:
</li><li><ul><li>AI outputs align with client expectations
</li><li>Traceability (data model output)
</li></ul></li><li>Support:
</li><li><ul><li>BRD validation (AI feasibility)
</li><li>UAT and acceptance criteria</li></ul></li></ul> 

Requirements 
 
Required SkillsTechnical<ul><li>
Strong in:
</li><li><ul><li>Python (PyTorch / TensorFlow)
</li><li>NLP &amp; LLMs (Transformers, RAG)
</li></ul></li><li>Experience with:
</li><li><ul><li>LangChain / LLM frameworks
</li><li>Vector databases
</li><li>Prompt engineering
</li></ul></li></ul>Arabic AI (Mandatory)<ul><li>
Native or fluent Arabic
</li><li>Experience in:
</li><li><ul><li>Arabic NLP
</li><li>Dataset preparation for Arabic
</li><li>Handling dialects
</li></ul></li></ul>Engineering &amp; Deployment<ul><li>
APIs (FastAPI / Flask)
</li><li>Microservices architecture
</li><li>Docker, Kubernetes
</li><li>CI/CD pipelines</li></ul>
Language Requirements<ul><li>
Arabic: Native / Fluent (MANDATORY)
</li><li>English: Professional (MANDATORY)
</li></ul>Preferred Qualifications<ul><li>
MSc or higher in AI / Data Science / NLP
</li><li>Experience in:
</li><li><ul><li>Arabic LLMs (high priority)
</li><li>Government or enterprise AI projects
</li></ul></li><li>Certifications:
</li><li><ul><li>Azure AI / ML
</li><li>MLOps / Cloud certifications</li></ul></li></ul></div>

LLM Engineer - Arabic Speaker

<div>Master Works is seeking an AI Engineer with strong generative AI prototyping experience to rapidly turn ideas into working AI-powered demos, proofs of concept, and early-stage products. The role sits between research and production engineering &mdash; combining hands-on use of large language models, multimodal models, retrieval-augmented generation, and agent frameworks to validate feasibility, explore new capabilities, and de-risk feature delivery. The role is central to accelerating AI innovation across the data, analytics, and intelligence portfolio, with a particular emphasis on bilingual (Arabic/English) AI use cases.<ul><li>
Rapidly design and build generative-AI prototypes and proofs of concept &mdash; from initial idea to working demo &mdash; using modern LLM APIs, open-source models, and prototyping frameworks.</li><li>
Design and implement retrieval-augmented generation (RAG) pipelines, including document ingestion, chunking strategies, embedding generation, vector storage, and retrieval orchestration.</li><li>
Build agentic systems that use tool/function calling, planning, and multi-step reasoning to automate complex tasks; integrate AI agents with internal APIs, databases, and external services.</li><li>
Engineer prompts, system instructions, and structured-output schemas; iterate on prompt design through measurable evaluation rather than guesswork.</li><li>
Work with multimodal AI capabilities &mdash; text, vision, speech (STT/TTS), and document understanding &mdash; and combine them into coherent end-to-end AI pipelines.</li><li>
Build and run AI evaluation frameworks (offline benchmarks, LLM-as-judge, golden-set regression testing) to measure quality, accuracy, latency, and cost across model and prompt variants.</li><li>
Adapt and fine-tune open-source models (LoRA, QLoRA, full fine-tuning) when proprietary or domain-specific behaviour is required, especially for Arabic-language tasks.</li><li>
Apply responsible-AI practices &mdash; safety filtering, hallucination mitigation, prompt-injection defence, PII handling, and bias awareness &mdash; especially for sensitive or regulated environments.</li><li>
Hand off mature prototypes to production engineering teams, providing clear documentation, evaluation results, deployment notes, and migration guidance.</li><li>
Demo prototypes and AI capabilities to internal stakeholders and clients; explain technical concepts, limitations, and risks to non-technical audiences.</li><li>
Track and evaluate fast-moving developments in the generative-AI ecosystem (new models, tools, techniques, and providers) and recommend adoption where they materially improve outcomes.</li><li>
Collaborate cross-functionally with product, design, data, and software engineering teams to shape AI features end-to-end and ensure they deliver real user value.</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related discipline.
</li><li>Postgraduate qualification (MSc/PhD) in Machine Learning, Artificial Intelligence, Natural Language Processing, or a related field is preferred.</li><li>
Recognised certifications in machine learning, deep learning, generative AI, or cloud AI platforms (AWS, Azure, GCP) are a strong plus.</li><li>
3&ndash;5+ years of AI/ML engineering experience, with at least 1&ndash;2 years hands-on building generative-AI applications using modern LLMs.</li><li>
Demonstrable portfolio of shipped prototypes or production AI features &mdash; ideally including RAG systems, AI agents, or multimodal pipelines.</li><li>
Hands-on experience with leading LLM APIs (e.g., Anthropic Claude, OpenAI GPT, Google Gemini) and open-source model serving (e.g., Hugging Face, vLLM, Ollama).</li><li>
Strong Python proficiency, including modern AI libraries such as PyTorch, Hugging Face Transformers, LangChain or LlamaIndex, and standard data tooling.</li><li>
Working experience with embedding models, vector databases (e.g., Pinecone, Weaviate, Qdrant, FAISS), and retrieval evaluation techniques.</li><li>
Familiarity with rapid-prototyping tools (Streamlit, Gradio, Jupyter), API integration, and lightweight web back-ends.</li><li>
Experience designing AI evaluation harnesses (offline benchmarks, LLM-as-judge, golden sets) and using observability/tracing tools for AI systems.</li></ul><ul><li>
Exposure to fine-tuning techniques (LoRA, QLoRA, instruction tuning) and to Arabic-language NLP is strongly preferred.</li><li>
Working knowledge of containerisation (Docker), version control (Git), and cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI) is a strong plus.</li><li>
Excellent leadership and team development skills.</li><li>
Strong bias for action and a rapid-prototyping mindset; able to ship a working demo in days, not months.</li><li>
Comfortable working under uncertainty &mdash; rapidly forming hypotheses, running experiments, and iterating based on evidence.</li><li>
Strong analytical and problem-solving skills, with the discipline to evaluate AI behaviour quantitatively rather than relying on intuition alone.</li><li>
Excellent verbal and written communication, with the ability to demo AI capabilities and explain technical concepts, limitations, and risks to non-technical audiences.</li><li>
Curiosity and continuous-learning mindset; actively follows the rapidly evolving generative-AI landscape and brings new ideas back to the team.</li><li>
Collaborative team player; comfortable in cross-functional teams of researchers, software engineers, designers, and client business owners.</li><li>
Cultural awareness and sensitivity, particularly when designing AI experiences for Arabic-speaking users in regional contexts.</li></ul></div>

AI engineer

Master Works

<div>
 Master Works is seeking an AI Engineer with strong generative AI prototyping experience to rapidly turn ideas into working AI-powered demos, proofs of concept, and early-stage products. The role sits between research and production engineering &mdash; combining hands-on use of large language models, multimodal models, retrieval-augmented generation, and agent frameworks to validate feasibility, explore new capabilities, and de-risk feature delivery. The role is central to accelerating AI innovation across the data, analytics, and intelligence portfolio, with a particular emphasis on bilingual (Arabic/English) AI use cases.
 
 
 <ul>
 <li>
 Rapidly design and build generative-AI prototypes and proofs of concept &mdash; from initial idea to working demo &mdash; using modern LLM APIs, open-source models, and prototyping frameworks
 </li>
 <li>
 Design and implement retrieval-augmented generation (RAG) pipelines, including document ingestion, chunking strategies, embedding generation, vector storage, and retrieval orchestration
 </li>
 <li>
 Build agentic systems that use tool/function calling, planning, and multi-step reasoning to automate complex tasks; integrate AI agents with internal APIs, databases, and external services
 </li>
 <li>
 Engineer prompts, system instructions, and structured-output schemas; iterate on prompt design through measurable evaluation rather than guesswork
 </li>
 <li>
 Work with multimodal AI capabilities &mdash; text, vision, speech (STT/TTS), and document understanding &mdash; and combine them into coherent end-to-end AI pipelines
 </li>
 <li>
 Build and run AI evaluation frameworks (offline benchmarks, LLM-as-judge, golden-set regression testing) to measure quality, accuracy, latency, and cost across model and prompt variants
 </li>
 <li>
 Adapt and fine-tune open-source models (LoRA, QLoRA, full fine-tuning) when proprietary or domain-specific behaviour is required, especially for Arabic-language tasks
 </li>
 <li>
 Apply responsible-AI practices &mdash; safety filtering, hallucination mitigation, prompt-injection defence, PII handling, and bias awareness &mdash; especially for sensitive or regulated environments
 </li>
 <li>
 Hand off mature prototypes to production engineering teams, providing clear documentation, evaluation results, deployment notes, and migration guidance
 </li>
 <li>
 Demo prototypes and AI capabilities to internal stakeholders and clients; explain technical concepts, limitations, and risks to non-technical audiences
 </li>
 <li>
 Track and evaluate fast-moving developments in the generative-AI ecosystem (new models, tools, techniques, and providers) and recommend adoption where they materially improve outcomes
 </li>
 <li>
 Collaborate cross-functionally with product, design, data, and software engineering teams to shape AI features end-to-end and ensure they deliver real user value
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related discipline.
 </li>
 <li>
 Postgraduate qualification (MSc/PhD) in Machine Learning, Artificial Intelligence, Natural Language Processing, or a related field is preferred
 </li>
 <li>
 Recognised certifications in machine learning, deep learning, generative AI, or cloud AI platforms (AWS, Azure, GCP) are a strong plus
 </li>
 <li>
 3-5+ years of AI/ML engineering experience, with at least 1-2 years hands-on building generative-AI applications using modern LLMs
 </li>
 <li>
 Demonstrable portfolio of shipped prototypes or production AI features &mdash; ideally including RAG systems, AI agents, or multimodal pipelines
 </li>
 <li>
 Hands-on experience with leading LLM APIs (e.g., Anthropic Claude, OpenAI GPT, Google Gemini) and open-source model serving (e.g., Hugging Face, vLLM, Ollama)
 </li>
 <li>
 Strong Python proficiency, including modern AI libraries such as PyTorch, Hugging Face Transformers, LangChain or LlamaIndex, and standard data tooling
 </li>
 <li>
 Working experience with embedding models, vector databases (e.g., Pinecone, Weaviate, Qdrant, FAISS), and retrieval evaluation techniques
 </li>
 <li>
 Familiarity with rapid-prototyping tools (Streamlit, Gradio, Jupyter), API integration, and lightweight web back-ends
 </li>
 <li>
 Experience designing AI evaluation harnesses (offline benchmarks, LLM-as-judge, golden sets) and using observability/tracing tools for AI systems
 </li>
 <li>
 Exposure to fine-tuning techniques (LoRA, QLoRA, instruction tuning) and to Arabic-language NLP is strongly preferred
 </li>
 <li>
 Working knowledge of containerisation (Docker), version control (Git), and cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI) is a strong plus
 </li>
 <li>
 Excellent leadership and team development skills
 </li>
 <li>
 Strong bias for action and a rapid-prototyping mindset; able to ship a working demo in days, not months
 </li>
 <li>
 Comfortable working under uncertainty &mdash; rapidly forming hypotheses, running experiments, and iterating based on evidence
 </li>
 <li>
 Strong analytical and problem-solving skills, with the discipline to evaluate AI behaviour quantitatively rather than relying on intuition alone
 </li>
 <li>
 Excellent verbal and written communication, with the ability to demo AI capabilities and explain technical concepts, limitations, and risks to non-technical audiences
 </li>
 <li>
 Curiosity and continuous-learning mindset; actively follows the rapidly evolving generative-AI landscape and brings new ideas back to the team
 </li>
 <li>
 Collaborative team player; comfortable in cross-functional teams of researchers, software engineers, designers, and client business owners
 </li>
 <li>
 Cultural awareness and sensitivity, particularly when designing AI experiences for Arabic-speaking users in regional contexts
 </li>
 </ul>
</div>

<div><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.</div> 
What you&rsquo;ll build 
In this role, you'll lead the design and delivery of production-grade ML and generative AI systems that solve complex product and business problems at scale. You'll own architecture and implementation across data pipelines, feature stores, training workflows, model-serving infrastructure, online experimentation, and observability.
You'll drive advanced use cases across deep learning, NLP, ranking, recommendation, forecasting, semantic retrieval, and LLM applications, including RAG, tool use, evaluation harnesses, and safety controls. Your work will directly shape performance, reliability, latency, and cost efficiency in live environments. You&rsquo;ll guide technical direction on topics such as model selection, distributed training and inference, GPU utilization, model compression, prompt and retrieval optimization, drift detection, retraining strategy, and responsible AI controls. You&rsquo;ll mentor other engineers and turn best practices into reusable patterns and platform capabilities. 
What you bring: 
<ul><li>
You bring expert-level programming skills in Python, along with strong software engineering expertise in languages such as Java or Go, enabling you to build scalable, production-grade systems</li><li>
You have deep knowledge of machine learning, deep learning, and optimization techniques across structured data, NLP, search, ranking, and recommendation problems</li><li>
You have extensive experience designing and operating end-to-end ML systems, from data ingestion and experimentation to deployment, observability, and lifecycle management</li><li>
You bring strong hands-on experience with modern ML and LLM tooling (e.g., PyTorch, TensorFlow, scikit-learn), including fine-tuning, evaluation, orchestration, and model serving</li><li>
You have practical experience building generative AI applications using embeddings, vector databases, RAG pipelines, agent workflows, prompt engineering, and guardrails</li><li>
You bring deep expertise in MLOps and platform engineering, including model registries, feature stores, CI/CD, infrastructure as code, experiment tracking, and automated validation</li><li>
You have a strong architectural understanding of distributed systems, event-driven services, streaming data, and cloud-native ML platforms, with the ability to optimize for performance, scalability, reliability, and cost</li><li>
You define robust evaluation and governance strategies, including offline benchmarking, online experimentation, hallucination analysis, model risk assessment, and responsible AI practices</li></ul> 
About You<ul><li>
You bring 7-9+ years of experience in software engineering and machine learning, with a track record of leading and delivering complex, production-scale AI systems</li><li>
You combine strong product judgment with technical depth, translating ambiguous business problems into scalable, high-impact AI solutions</li><li>
You thrive in complex, fast-moving environments and bring clarity, ownership, and strategic thinking to drive long-term platform success</li></ul> 
Where you belong: 
You will be part of a growing team of AI and industry experts 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 are a team of engineers passionate about building valuable, scalable AI frameworks that drive real business impact. We thrive on solving challenging problems, innovating
with cutting-edge technologies, and collaborating closely to deliver AI systems that are reliable, high-performing, and ready for production. Our team values ownership, technical excellence, and creating solutions that stand the test of scale and complexity.<div> 
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.</div><div></div><div> 
AI Usage in the Recruitment Process</div><div>
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.
</div>Please note that any violation of these guidelines may result in disqualification from the hiring process. 
 
Requisition ID: 450218 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid</div>

Senior Machine Learning Engineer

<div>This is a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems. This role sits at the intersection of data science, software engineering, and MLOps, and requires strong hands-on experience turning models into production-ready solutions, programming experience in Python or R.
<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 
<ul><li>
3&ndash;7+ 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, and 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 Engineer

Explore 314+ Nlp engineer in Riyadh this May. Find roles across top companies and apply now to boost your career.

314 nlp engineer jobs In Riyadh

AI Engineer (Mid-Level)

Technical Lead

LLM Engineer - Arabic Speaker

AI engineer

AI engineer

Senior Machine Learning Engineer

AI Engineer