machine learning engineer

principal machine learning engineer Jobs in Cairo

principal machine learning engineer

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machine learning intern

Si-Ware Systems

<div>
 Si-Ware Systems is a global leader in semiconductor and spectroscopy solutions. Our innovative devices and software enable material analysis across many industries.
 
 
 At Si-Ware, we foster a culture of innovation, collaboration, and continuous learning, empowering our people to push the boundaries of technology.
 
 
 As a
 
 Machine Learning Engineer
 
 at Si-Ware, you will design, implement, and deploy applied ML solutions that power real-world spectroscopy devices and emerging physical AI systems.
 
 
 You will work at the intersection of machine learning, software engineering, and intelligent hardware integration.
 
 
 initiatives.
 
 
 
 Responsibilities:
 
 
 
 
 Machine Learning &amp; Modeling
 
 
 
 <ul>
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 Perform data cleaning, preprocessing, and transformation for training and evaluation.
 </li>
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 Contribute to the development, training, and improvement of machine learning models.
 </li>
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 Design and execute structured experiments using appropriate validation strategies (cross-validation, hold-out testing, statistical comparison).
 </li>
 <li>
 Evaluate models using appropriate performance metrics (Accuracy, Precision, Recall, F1, RMSE, etc.).
 </li>
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 Optimize models and inference pipelines for performance, memory efficiency, and real-time constraints when required.
 </li>
 <li>
 Ensure reproducibility, traceability, and proper validation of models within regulated or industrial environments.
 </li>
 <li>
 Support chemometrics-related workflows, including spectral preprocessing, feature extraction, multivariate modeling, and validation for spectroscopy-based applications.
 
 
 
 </li>
 </ul>
 
 Production &amp; System Integration
 
 
 
 <ul>
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 Design and implement production-ready ML pipelines integrated with software applications and hardware systems.
 </li>
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 Ensure models are maintainable, version-controlled, and deployable within real-world products.
 </li>
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 Contribute to the design and evolution of ML system architecture and reusable pipeline components.
 </li>
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 Develop unit and integration tests for ML components to ensure reliability.
 </li>
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 Document ML modules and interfaces to support long-term maintainability.
 </li>
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 Work closely with software and firmware teams to integrate ML models into desktop applications, services, and embedded workflows.
 
 
 
 </li>
 </ul>
 
 Tools, Innovation &amp; Growth
 
 
 
 <ul>
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 Participate in the development of internal and customer-facing ML-driven tools and automation utilities.
 </li>
 <li>
 Stay updated with the latest machine learning research, tools, and industry practices.
 </li>
 <li>
 Contribute to exploratory and applied ML solutions in emerging physical AI systems, including robotics and sensor-driven intelligent platforms.
 </li>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, or a related field.
 </li>
 <li>
 1 - 4 years of relevant industry or applied ML experience preferred.
 </li>
 <li>
 Strong focus on applied machine learning and engineering implementation.
 </li>
 <li>
 Hands-on experience with Python and its ML ecosystem (NumPy, Pandas, Matplotlib, Scikit-Learn).
 </li>
 <li>
 Familiarity with at least one deep learning framework (PyTorch or TensorFlow).
 </li>
 <li>
 Solid understanding of software engineering principles (modular design, version control, testing, debugging).
 </li>
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 Experience structuring modular Python codebases.
 </li>
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 Familiarity with packaging, model serialization, and reproducible pipelines.
 </li>
 <li>
 Experience working within larger software systems (not only notebooks).
 </li>
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 Strong analytical and problem-solving skills.
 </li>
 <li>
 Good communication skills and ability to work in a collaborative team environment.
 </li>
 <li>
 Proficiency in English (reading and writing).
 
 
 
 </li>
 </ul>
 
 Nice to Have:
 
 
 
 <ul>
 <li>
 Basic understanding of chemometrics concepts (multivariate analysis, regression/classification, spectral data handling).
 </li>
 <li>
 Exposure to spectroscopy data (NIR, IR) and common preprocessing techniques (normalization, smoothing, baseline correction).
 </li>
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 Experience contributing to ML tools, internal platforms, or data analysis software.
 </li>
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 Knowledge of MLOps practices (Git, CI/CD, Docker).
 </li>
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 Experience with cloud platforms (AWS, GCP, Azure).
 </li>
 <li>
 Experience with robotics frameworks (ROS).
 </li>
 <li>
 Experience with sensor fusion.
 </li>
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 Experience with real-time ML inference.
 </li>
 <li>
 Basic understanding of control systems.
 </li>
 <li>
 Exposure to data visualization or BI tools.
 </li>
 <li>
 Contributions to Kaggle competitions, research projects, or open-source initiatives.
 </li>
 </ul>
</div>

Machine Learning Engineer

Smart Eye

<div>
 Smart Eye is the leading provider of Human Insight AI, technology that understands, supports and predicts human behavior in complex environments. The company is on a mission to bridge the gap between humans and machines for a safe and sustainable future. Supported by Affectiva and iMotions &ndash; companies it acquired in 2021 &ndash; Smart Eye&rsquo;s multimodal software and hardware solutions provide unparalleled insight into human behavior.
 
 
 In automotive, Smart Eye&rsquo;s driver monitoring systems and interior sensing solutions improve road safety and the mobility experience. The company&rsquo;s eye tracking technology and iMotions biosensor software platform are also used in behavioral research to enable advanced research in academic and commercial sectors. In media analytics, Affectiva&rsquo;s Emotion AI provides the world&rsquo;s largest brands and market researchers with a deeper understanding of how consumers engage with content, products, and services.
 
 
 Founded in 1999, Smart Eye is a global company headquartered in Sweden, with customers including NASA, Nissan, Boeing, Honeywell, Volvo, GM, BMW, Polestar, Geely, Harvard University, 26 percent of the Fortune Global 500 companies, and over 1,300 research organizations around the world.
 
 
 Visit
 
 www.smarteye.ai
 
 for more information.
 
 
 You will be part of one of Smart Eye's algorithm development teams responsible for development in key areas such as head- and eye-tracking, attentiveness and drowsiness, face identification and interior sensing for our Automotive Cabin and Driving Monitoring product. We work in an international environment with colleagues in Gothenburg (SE) and Boston (US).
 
 
 We are building safety features in novel technology that will significantly improve road safety and will transform our transportation experiences. Safety features such as determining people&rsquo;s seating locations in a vehicle, if they are wearing seat belts, and detection of left-behind children, as well as features that enhance comfort, wellness, and entertainment by detecting occupants&rsquo; emotions and gestures.
 
 
 Development activities range from early-stage prototyping to porting and deployment to a wide set of automotive embedded platforms. And you will be responsible for the complete chain of development activities including protocols for data collection, network architecture, training of networks, exploratory data analysis and visualization, but also integration into and validation of the model in the production software.
 
 
 We solve these challenging problems by utilizing state-of-the-art algorithms in the fields of image processing, the latest machine learning techniques, mathematics, and accelerated computing.
 
 
 You will have an active impact on the processes and projects and will work in close cooperation with other talented team members. Your contribution to how we can meet our customers' needs with tomorrow's technology will be of crucial importance.
 
 
 Who are you?
 
 
 <ul>
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 We welcome all types of personalities and believe in a true mix of people to create a dynamic work environment.
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 You're able to work independently in an environment that changes rapidly.
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 Exhibit a positive, enthusiastic, open, entrepreneurial attitude and a willingness to work closely with customers or other teams within Smart Eye.
 </li>
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 Possess strong analytical, creative skills with a strong interest in new technologies.
 
 
 </li>
 </ul>
 
 Must-have-skills
 
 
 
 <ul>
 <li>
 Degree in Electrical Engineering, Computer Sciences, or Mathematics with specialization in computer vision or machine learning.
 </li>
 <li>
 Experience using end-to-end development of machine learning based systems (design, planning, evaluation, deployment).
 </li>
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 3+ years of software development experience.
 </li>
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 3+ years of work experience in C++ and Python development.
 </li>
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 Strong communication and team collaboration skills.
 
 
 </li>
 </ul>
 
 Good-to-have-skills
 
 
 
 <ul>
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 Experience in optimizing Deep Learning model architectures and inference runtimes (ex. Tensorflow, Tensorflow Lite, PyTorch).
 </li>
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 Experience in one or more fields of image processing or graphics programming.
 </li>
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 Experience with CI/CD (Continuous Integration and Deployment).
 </li>
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 Experience in developing software for the Automotive industry.
 </li>
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 Familiar with Agile methodologies (has worked with Git, Jira and alike).
 </li>
 </ul>
</div>

Siemens

<div>
 Siemens Digital Industries (DI) is a global leader in automation and digitalization. In close collaboration with partners and customers, we drive digital transformation across process and discrete industries. Our Digital Enterprise portfolio delivers an end-to-end ecosystem of products, solutions, and services that help organizations of all sizes integrate and digitalize their entire value chain.
 
 
 Our industry-focused portfolio enables customers to achieve greater efficiency, flexibility, and innovation. We continuously evolve our technology stack by integrating groundbreaking future technologies. Siemens Digital Industries Software is headquartered in Nuremberg, Germany, and employs approximately 75,000 people worldwide.
 
 
 We offer a role that combines responsibility, autonomy, and the opportunity to contribute proactively. Our culture promotes teamwork, ownership, and continuous individual development.
 
 
 Learn more: https://siemensneo.com/disw/
 
 
 We're looking for a
 
 Principal Machine Learning Engineer
 
 to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and deliver RAG pipelines, prompt workflows, agent tools, safety guardrails, and evaluation frameworks &mdash; optimizing for performance, cost, and quality.
 </li>
 <li>
 Own the ML lifecycle end-to-end: From data prep and feature engineering to fine-tuning (LoRA/QLoRA), testing, deployment, monitoring, and continuous improvement.
 </li>
 <li>
 Productionize on AWS: Launch scalable ML services using AWS infrastructure and ML tooling, with strong observability and cost efficiency.
 </li>
 <li>
 Scale training &amp; inference: Apply distributed training, quantization, caching, and vector databases to improve performance and efficiency.
 </li>
 <li>
 Drive MLOps &amp; governance: Build CI/CD pipelines for ML, manage model/version registries, track experiments, and enforce responsible AI practices.
 </li>
 <li>
 Partner cross-functionally: Work with product and engineering teams to turn real asset-management problems into customer-facing ML solutions.
 </li>
 <li>
 Mentor &amp; lead: Provide technical guidance, review designs, and elevate ML engineering standards across the team.
 </li>
 <li>
 Analyze data deeply: Perform EDA on structured and unstructured data to uncover insights, patterns, and quality issues.
 </li>
 <li>
 Research domain signals: Investigate operational and asset datasets to identify trends, root causes, and predictive opportunities.
 
 
 </li>
 </ul>
 Qualifications:
 
 
 <ul>
 <li>
 B.Sc. in Computer Engineering or Electronics Engineering.
 </li>
 <li>
 10+ years in software/ML engineering, including 3+ years running production ML systems end-to-end.
 </li>
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 Hands-on experience building LLM applications (RAG, fine-tuning, prompt engineering, evaluators/guardrails, agent workflows) using tools like LangChain/LangGraph.
 </li>
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 Strong AWS background (3+ years), including core infrastructure and ML services such as SageMaker and Bedrock.
 </li>
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 Solid modeling stack: Python, PyTorch, Hugging Face, embeddings/vector databases, and LLM evaluation techniques.
 </li>
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 Proven MLOps experience: CI/CD for ML, experiment tracking, model registries, monitoring, and automated retraining pipelines.
 </li>
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 Good data engineering foundations: ETL/ELT pipelines, streaming/batch processing (Spark/Flink), and data governance practices.
 </li>
 <li>
 Experience with distributed training, RLHF, or optimization on specialized AI hardware is a plus!
 </li>
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 Preferrably has background in asset, sustainability, or intelligent operations domains.
 </li>
 <li>
 Familiarity with enterprise ML security and compliance practices is nice to have.
 
 
 </li>
 </ul>
 We&rsquo;re Siemens. A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit and business need. Bring your curiosity and creativity and help us shape tomorrow!
 
 
 Siemens is an equal opportunities employer and do not discriminate unlawfully on any grounds. We are committed to providing access and equal opportunity.
</div>

Principal Machine Learning Engineer

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 8&ndash;10 years total software/ML engineering experience, with 5+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 
 How You&rsquo;ll Work
 
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

Agoda

<div>
 
 About Agoda
 
 
 
 At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
 
 
 Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
 
 
 No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you&rsquo;re ready to begin your best journey and help build travel for the world, join us.
 
 
 Agoda is an online travel booking platform for accommodation, flights, and more. We build and deploy cutting edge technology that connects travelers with more than 2.5 million accommodations globally. Based in Asia and part of Booking Holdings, our 4,000+ talents coming from 90+ different nationalities foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enabling our customers to experience the world.
 
 
 
 Get to Know Our Team
 
 
 
 The Engineering department oversees all Agoda&rsquo;s ML and software related requirements. Our goal is to enable and increase Agoda&rsquo;s business through creative approaches and the implementation of powerful resources such as operational and analytical databases, ML driven solutions, queue systems and data monitoring tools. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company&rsquo;s culture of diversity and experimentation. The role the engineering team plays at Agoda is critical as business users, product managers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the ML engineering squad, but also the reward. We work across structured and non-structured data at scale. For example, our current ML models process millions of images every day to try and enhance the experience that our users get from our app.
 
 
 
 Why Agoda Engineering Team (ML role)?
 
 
 
 Our engineering teams are at the intersection of business analytics, ml engineering, data warehousing and software engineering. Our job involves dealing with distributed systems, stream processing, ml modeling and computation at tens of PB Scale. We focus on software engineering related to data replication, storage, centralized computation, and Data API&rsquo;s. By providing our users with ML products/tools, shared frameworks, and ML services, we enable our company to validate strategic decisions, make smarter choices, and react to the fast-changing world. We are a small but passionate team with people from different nationalities working together on a single goal.
 
 
 
 This role is based in Gurgaon, India.
 
 
 
 
 In this Role, you will get to:
 
 
 
 <ul>
 <li>
 Lead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes.
 </li>
 <li>
 Build, administer and scale ML processing pipelines.
 </li>
 <li>
 Be comfortable navigating the following technology stack: Python3, Pyspark, scripting (Bash/Python), Hadoop, SQL, S3 etc.
 </li>
 <li>
 Should be able to understand internals of ML models such as Random Forest, CNN, Regression models, etc
 </li>
 <li>
 Design, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality.
 </li>
 <li>
 Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks.
 </li>
 <li>
 We believe in end-to-end ownership; this role will involve taking ML models to production at a scale.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll need to Succeed:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science /information systems/engineering/related field
 </li>
 <li>
 8+ years of experience in software engineering with a minimum of 4+ years in ML
 </li>
 <li>
 Good experience in Pyspark
 </li>
 <li>
 Expert level understanding of Python with design patterns and object-oriented programming.
 </li>
 <li>
 Experience debugging and reasoning about production issues is desirable.
 </li>
 <li>
 A good understanding of data architecture principles preferred.
 </li>
 <li>
 Any other experience with Big Data technologies / tools
 </li>
 <li>
 SQL experience
 </li>
 <li>
 Analytical problem-solving capabilities &amp; experience.
 </li>
 <li>
 Systems administration skills in Linux
 </li>
 <li>
 A strong engineering driven mindset will be required to succeed in this role.
 
 
 </li>
 </ul>
 
 It&rsquo;s great if you have:
 
 
 
 <ul>
 <li>
 Good understanding of Hadoop ecosystems
 </li>
 <li>
 Experience working with Open-source products
 </li>
 <li>
 Experience with Scala development
 </li>
 <li>
 Working in an agile environment using test driven methodologies
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Hybrid Working Model
 </li>
 <li>
 WFH Set Up Allowance
 </li>
 <li>
 30 Days of Remote Working from anywhere globally every year
 </li>
 <li>
 Employee discount for accommodation globally
 </li>
 <li>
 Global team of 90+ nationalities
 </li>
 <li>
 40+ offices and 25+ countries
 </li>
 <li>
 Annual CSR / Volunteer Time off
 </li>
 <li>
 Benevity Subscription for employee donations
 </li>
 <li>
 Volunteering opportunities globally
 </li>
 <li>
 Free Headspace subscription
 </li>
 <li>
 Free Odilo &amp; Udemy subscriptions
 </li>
 <li>
 Access to Employee Assistance Program (third party for personal and workplace support)
 </li>
 <li>
 Enhanced Parental Leave
 </li>
 <li>
 Life, TPD &amp; Accident Insurance
 
 
 </li>
 </ul>
 #telaviv #jerusalem #IT #ENG #4 #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #budapest #bali #dublin #telaviv #milan #rome #venice #florence #naples #turin #palermo #bologna #osaka #malta #amsterdam #oslo #warsaw #krakow #alrayyan #riyadh #jeddah #mecca #medina #singapore #seoul #barcelona #madrid #stockholm #zurich #taipei #tainan #taichung #kaohsiung #bangkok #Phuket #istanbul #london #manchester #edinburgh #hcmc #hanoi #lodz #wroclaw #poznan #katowice #rio #salvador #newdelhi #bangalore #bandung #yokohama #nagoya #okinawa #fukuoka #jerusalem #IT #4 #bangalore #delhi #hyderabad #pune #singapore #beijing #shanghai #shenzhen #tokyo #seoul #hongkong #taipei #kualalumpur #jakarta #hochiminh #hochiminhcity #manila #instanbul #makati #dubai #riyadh #gurgaon #noida
 
 
 
 Discover More About Working At Agoda
 
 
 
 <ul>
 <li>
 Agoda Careers https://careersatagoda.com
 </li>
 <li>
 Facebook https://www.facebook.com/agodacareers/
 </li>
 <li>
 LinkedIn https://www.linkedin.com/company/agoda
 </li>
 <li>
 YouTube https://www.youtube.com/agodalife
 
 
 </li>
 </ul>
 
 Equal Opportunity Employer
 
 
 
 At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person&rsquo;s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
 
 
 We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.
 
 
 
 Disclaimer
 
 
 
 We do not accept any terms or conditions, nor do we recognize any agency&rsquo;s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.
 
 
</div>

Staff Machine Learning Engineer (India based, relocation provided)

Arrow Electronics

<div>
 
 Position
 
 
 
 Data Scientist / Senior Machine Learning Engineer
 
 
 
 Job Description
 
 
 
 
 Position Overview:
 
 
 
 As Data Scientist / Senior Machine Learning Engineer at Arrow Electronics, you will assume a pivotal role in driving our data science and machine learning initiatives to reach unprecedented heights. Collaborating closely with cross-functional multinational teams, your responsibilities will encompass the end-to-end machine learning lifecycle, including stakeholder communications, data analysis, designing, development, deployment, and optimization of cutting-edge models aimed at addressing intricate challenges and generating actionable insights. Your expertise in data analysis, model development, and deployment will be crucial in shaping the future of our company.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
 </li>
 <li>
 Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
 </li>
 <li>
 Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
 </li>
 <li>
 Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
 </li>
 <li>
 Cross-functional Collaboration: Collaborate closely with business stakeholders, software engineers, data engineers, and domain experts to integrate machine learning solutions into our products and services.
 </li>
 <li>
 Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
 </li>
 <li>
 Research and Innovation: Stay up-to-date with the latest advancements in the field of data science and machine learning and apply innovative techniques to solve complex challenges.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
 </li>
 <li>
 Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
 </li>
 <li>
 Strong knowledge of machine learning frameworks and libraries.
 </li>
 <li>
 Expertise in data preprocessing, feature engineering, and model selection.
 </li>
 <li>
 Familiarity with large language models and AI agent design.
 </li>
 <li>
 Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
 </li>
 <li>
 Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
 </li>
 <li>
 Experience with vectorized databases and unstructured search engines is a plus.
 </li>
 <li>
 A Master&rsquo;s degree in computer science, Statistics, Data Science, or a related field is a plus.
 </li>
 <li>
 Publications or contributions to open-source projects are a plus.
 
 
 </li>
 </ul>
 If you are a passionate and experienced Data Scientist / Senior Machine Learning Engineer who thrives on solving challenging problems and wants to make a significant impact in the field, we encourage you to apply and join our dynamic team at Arrow Electronics Together, we will drive innovation and shape the future of data science and machine learning.
 
 
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Data Scientist / Senior Machine Learning Engineer

Unifonic

<div>
 
 Job Description
 
 
 
 Proudly voted a Great Place to Work&reg;, we are a dynamic startup in the SaaS space that is revolutionizing the way businesses communicate. Our team is made up of 500 energetic and passionate Unifones who are dedicated to delivering the best possible experience to 5000+ customer-centric companies.
 
 
 We pride ourselves on our fun and collaborative work environment, where creativity and new ideas are constantly encouraged. As shareholders in the business, we&rsquo;re so much more than a group of passionate communicators. We are Unifones. Join our team and be a part of something big!
 
 
 
 Meet the team!
 
 
 
 Our Engineering team is responsible for designing, developing, and maintaining the systems and technologies that drive Unifonic&rsquo;s solutions. We work closely with other departments to ensure our products and services meet the needs of our customers. If you are passionate about technology and are excited about working on cutting-edge communication and engagement solutions, we want you on our team.
 
 
 As a Senior Machine Learning (AI) Engineer, you will be responsible for designing, developing, and deploying advanced machine learning solutions across various domains, including NLP, Text Classification, RAG, LLMs, Recommender engines, and Anomaly detection. This role involves end-to-end project ownership, from data preprocessing to the creation of service APIs, and offers opportunities to work on cutting-edge AI technologies.
 
 
 
 Help Us Shape The Future Of Communication By
 
 
 
 <ul>
 <li>
 Leading the end-to-end design, development, and deployment of robust and scalable machine learning solutions, with a strong emphasis on NLP and RAG architectures.
 </li>
 <li>
 Architecting and implementing RAG systems, combining large language models (LLMs) with robust retrieval mechanisms to improve the accuracy, factual grounding, and interpretability of generated content.
 </li>
 <li>
 Applying advanced NLP techniques for tasks such as text classification, entity recognition, sentiment analysis, summarization, question answering, and information extraction.
 </li>
 <li>
 Researching, evaluating, and integrating state-of-the-art NLP models and RAG frameworks (e.g., Transformers, BERT, GPT variants, Vector Databases, Semantic Search).
 </li>
 <li>
 Mentoring junior team members on the team, sharing knowledge, and advising the best machine learning and software engineering practices and approaches.
 </li>
 <li>
 Establishing and maintaining robust communication channels with other cross-functional teams to facilitate the integration of machine learning solutions into other Unifonic products.
 </li>
 <li>
 Developing and optimizing highly confident machine learning algorithms and models and creating/exposing the service APIs using frameworks such as Flask, FastAPIs, or other relevant frameworks.
 </li>
 <li>
 Staying up to date with the latest machine learning research papers, and AI trends (i.e. Generative AI).
 </li>
 <li>
 Collaborating with the data engineering team and other teams to collect and analyze extensive datasets, extracting insights and patterns, in real-time, near-real-time, or batch processing mode.
 </li>
 <li>
 Implementing proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations.
 </li>
 <li>
 Building scalable, maintainable machine learning services, which should handle thousands of requests per second, and help to perform the required load tests to meet the SLA.
 </li>
 <li>
 Reviewing the code of other team members and suggesting improvements to ensure the SOLID principles and clean architecture.
 </li>
 <li>
 Assisting in the project documentation and demos.
 
 
 </li>
 </ul>
 Job requirements
 
 
 
 What You'll Bring
 
 
 
 <ul>
 <li>
 Proven experience designing and implementing RAG systems, including familiarity with various retrieval strategies (e.g., BM25, dense retrieval, hybrid approaches) and knowledge graph integration.
 </li>
 <li>
 Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar tools for building and managing autonomous agents.
 </li>
 <li>
 Deep expertise in various NLP techniques and models, including but not limited to:
 
 
 </li>
 </ul>
 Transformer architectures (e.g., BERT, GPT, T5, LLama, Mistral)
 
 
 Large Language Models (LLMs) and their fine-tuning/adaptation
 
 
 Vector embeddings and similarity search
 
 
 Text classification, named entity recognition (NER), sentiment analysis, summarization, and question answering.
 
 
 <ul>
 <li>
 Hands-on 3-5 years of relevant work experience as a Machine Learning Engineer.
 </li>
 <li>
 Hands-on 3+ years of experience with Python.
 </li>
 <li>
 Excellent analytical abilities, with the capacity to collect, organize, and analyze large datasets to glean valuable insights.
 </li>
 <li>
 End-to-end experience in training, evaluating, testing, and deploying machine learning products in production.
 </li>
 <li>
 Ability to write world-class code in Python (SOLID principles), considering the best software engineering fundamentals, i.e. data structures, algorithms, and data modeling
 </li>
 <li>
 Solid experience in ML frameworks such as NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow, and similar.
 </li>
 <li>
 Familiarity with MLOps best practices, e.g. Model deployment and reproducible research.
 </li>
 <li>
 Mastering data science needed skills like SQL, hypothesis testing, Data cleansing, data augmentation, data pre-processing techniques, and dimensionality reduction.
 </li>
 <li>
 Basic knowledge of Kubernetes and Docker is nice to have.
 </li>
 <li>
 Excellent understanding of Machine learning techniques like Naive Bayes classifiers, SVM, Decision Tree, KNN, K-means, Random Forest, modeling and optimization, evaluation metrics, classification, and clustering.
 </li>
 <li>
 Experience with the Hugging Face libraries (i.e. transformers).
 </li>
 <li>
 Experience fine-tuning pre-trained models and using vector search to enhance LLMs results.
 </li>
 <li>
 Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques.
 </li>
 <li>
 Familiar with code versioning tools such as GIT, CI/CD concepts, and toolchains.
 </li>
 <li>
 Familiar with Agile methodologies i.e. scrum and kanban.
 </li>
 <li>
 Ability to develop high-level architecture and low-level design, End-to-end for a specific project.
 </li>
 <li>
 Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is a plus.
 </li>
 <li>
 Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques is nice to have.
 </li>
 <li>
 Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is nice to have.
 </li>
 <li>
 General knowledge of Data warehouse tools e.g. Vertica is a plus.
 </li>
 <li>
 A Bachelor&rsquo;s degree in a relevant field. (e.g. Computer Science, Computer Engineering, Software, etc).
 </li>
 <li>
 Excellent communication and collaboration skills.
 </li>
 <li>
 Good level of spoken and written Arabic and English.
 
 
 </li>
 </ul>
 
 As a Unifone you will receive a range of benefits:
 
 
 
 <ul>
 <li>
 Competitive salary and bonus.
 </li>
 <li>
 Unifonic share scheme (we are all owners!).
 </li>
 <li>
 30 holiday days after the first anniversary.
 </li>
 <li>
 Your Birthday off!
 </li>
 <li>
 Spend up to 25 days per year working from anywhere in the world!
 </li>
 <li>
 Paid leave for new parents.
 </li>
 <li>
 LinkedIn learning license.
 </li>
 </ul>
</div>

Senior Machine Learning Engineer

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