7 Healthcare AI jobs in Egypt

Unifonic is a customer engagement platform that enables organizations to delight customers with remarkable omnichannel experiences. By unifying communication channels, messaging apps, and chatbots, Unifonic streamlines conversations at every touchpoint throughout the customer journey.

**Engineering principle**: We ship robust, high-quality code, written for humans to read and maintain!

The Engineering team at Unifonic is looking for a proactive and dynamic Senior Machine Learning Engineer, to join our diverse team of developers. In this role, you’ll be responsible for delivering ML models to serve use cases like NLP, speech tagging and recognition, text classification, Named Entity Recognition, and semantic extraction.
- Ability to fully understand technical requirements, challenge them and produce the most appropriate implementation.
- Discuss with product managers about product features.
- Design and implement ML pipelines from ideation to production
- Analyze, process, and interpret data.
- Build and train ML models along with tools to update/retrain those models which become a part of customer-facing products.
- Work with other software developers to guarantee Models implementation in production
- Be a role model in agile practices.
- Produce technical documentation for encountered problems and maintain team technical decisions.

**Requirements**:
**Must-Have**
- Bachelor’s degree in a relevant field. (e.g. Computer Science, Computer Engineering, Softwareetc)
- Hands-on 5-7 years of relevant work experience in shipping ML models for NLP, CV, classifiers, and recommenders for large-scale customer-facing projects.
- Experienced in Python with experience in common data science toolkits, such as NumPy, Pandas, PySpark, Scikit-Learn, Tensorflow, PyTorch, Keras, rasa, BERT, spaCy.
- Hands-on experience in NLP is mandatory; e.g. Text representation (n-grams, a bag of words, TF-IDF, etc), feature extraction, part of speech tagging and recognition, text classification, Named Entity Recognition (NER), semantic extraction techniques, Machine Translation, slot filling, Sentiment analysis, etc.
- Familiarity with MLOps best practices, e.g. Model deployment and reproducible research
- Mastering data science needed skills like SQL, hypothesis testing, Data cleansing, data augmentation, data pre-processing techniques, dimensionality reduction, mathematics, probability, and statistics (e.g. conditional probability, likelihood, Bayes rule, and Bayes nets, Hidden Markov Models, etc.).
- 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.
- Familiar with code versioning tools such as GIT, CI/CD concepts, and toolchains.
- Acquainted with agile methodologies like Scrum, and agile tools like Jira.

**Nice to have**
- Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
- Good knowledge of Deep Learning needed skills like Neural network architectures, fully connected networks, CNNs, LSTMs, and RNNs.
- Worked on other ML use cases like:

- Speech Recognition algorithms.
- Recommender Engines.
- Anomaly detection.
- Computer Vision (Face Recognition, OCR,)

Analyzing various ML algorithms that could be used to solve a given problem and ranking them by their success probability.
- Exploring and visualizing data and identifying differences in data distribution that could affect performance in live deployment.
- Data quality validation and cleaning.
- Finding available datasets online that could be used for training
- Defining validation strategies
- Defining the preprocessing or feature engineering to be done on a given dataset
- Defining data augmentation pipelines
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them
- Bachelor’s degree (or pursuing one) in Computer Science, Computer Engineering or equivalent experience.
- Excellent knowledge in Python, SQL
- Experience working with machine learning frameworks such as PyTorch, Tensorflow, scikit-learn
- Experience with web scraping
- Solid understanding of Object-Oriented Programming (OOP)
- Expertise in visualizing and manipulating big datasets
- Familiarity with Git
- Excellent communication and documentation skills

**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:**
1. Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
2. Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
3. Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
4. Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
5. 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.
6. Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
7. 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.
**Qualifications:**
+ Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
+ Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
+ Strong knowledge of machine learning frameworks and libraries.
+ Expertise in data preprocessing, feature engineering, and model selection.
+ Familiarity with large language models and AI agent design.
+ Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
+ Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
+ Experience with vectorized databases and unstructured search engines is a plus.
+ A Master's degree in computer science, Statistics, Data Science, or a related field is a plus.
+ Publications or contributions to open-source projects are a plus.
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 & Al Tamween)
**Time Type:**
Full time
**Job Category:**
Information Technology
Arrow Electronics, Inc.'s policy is to provide equal employment opportunities to all qualified employees and applicants without regard to race, color, religion, age, sex, marital status, gender identity or expression, sexual orientation, national origin, disability, citizenship, veran status, genetic information, or any other characteristics protected by applicable state, federal or local laws. Our policy of equal employment opportunity and affirmative action applies to all employment decisions personnel policies and practices, or programs.

Unifonic is a customer engagement platform that enables organizations to delight customers with remarkable omnichannel experiences. By unifying communication channels, messaging apps, and chatbots, Unifonic streamlines conversations at every touchpoint throughout the customer journey.

**Engineering principle**: We ship robust, high-quality code, written for humans to read and maintain!

The Engineering team at Unifonic is looking for a proactive and dynamic Machine Learning Engineering Lead, to join our diverse team of developers. In this role, you’ll be playing an active part in the hands-on process of building Machine Learning models and putting them into production, managing a team, and contributing to production-facing code on a regular basis.
- Design and lead the implementation of AI/ML/NLP pipelines from ideation to production
- Support with recruitment & hiring of team talents and facilitate their onboarding.
- Work with product managers, designers, and engineers to prioritize, plan, and schedule work.
- Communicate status, risks, and requirements to other groups.
- Provide technical and non-technical guidance to the team, both individually and as a group.
- Facilitate continuous learning and improvement for the team and its members.

**Must-Have**
- Hands-on 10+ years of relevant engineering work experience and 4+ years of hands-on technical management experience in shipping Machine Learning Models and large-scale projects with multiple dependencies across teams.
- Bachelor’s degree in a related field. (e.g. Computer Science, Computer Engineering,etc)
- Expert in Python with experience in common data science toolkits, such as NumPy, Pandas, PySpark, Scikit-Learn, Tensorflow, PyTorch, Keras, rasa, BERT, spaCy.
- Hands-on experience in NLP is mandatory; e.g. Text representation (n-grams, a bag of words, TF-IDF, etc), feature extraction, part of speech tagging and recognition, text classification, Named Entity Recognition (NER), semantic extraction techniques, Machine Translation, slot filling, Sentiment analysis, etc.
- Familiarity with MLOps best practices, e.g. Model deployment and reproducible research
- Mastering data science needed skills like SQL, hypothesis testing, Data cleansing, data augmentation, data pre-processing techniques, dimensionality reduction, mathematics, probability, and statistics (e.g. conditional probability, likelihood, Bayes rule, and Bayes nets, Hidden Markov Models, etc.).
- 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.
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, etc.
- Experience with data visualization tools, such as Grafana, Tableau, matplotlib, and seaborn.
- Proficiency in using query engines and languages such as SQL, Hive, and Pig.
- Experience with NoSQL databases, such as MongoDB, Cassandra, and Hbase.
- Solid experience with full Software Development Lifecycle, Distributed Architectures (REST, SOAP, Queue-based), and Microservices Architecture.
- Familiarity with famous Python ORM (Object Relational Mapper) libraries
- Ability to design systems that integrate with multiple data storage solutions including relational databases, key-value stores, and different cloud-based services.
- Solid understanding and hands-on experience in concurrency patterns, and event-driven architecture.
- Strong unit test and debugging skills.
- Proficient understanding of code versioning tools such as GIT, CI/CD concepts, and toolchains.
- Experience with the Agile Framework and Project Management tools such as Jira

**Nice to have**
- Experience building large scale data-driven systems in Java
- Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
- Good knowledge of Deep Learning needed skills like Neural network architectures, fully connected networks, CNNs, LSTMs, and RNNs.
- Worked on other ML use cases like:

- Speech Recognition algorithms.
- Recommender Engines.
- Anomaly detection.
- Computer Vision (Face Recognition, OCR,)
- Basic understanding of front-end technologies, such as JavaScript, HTML5, and CSS3
- Understanding of accessibility and security compliance
- Knowledge of user authentication and authorization between multiple systems, servers, and environments. (e.g. Basic Auth, SAML, Keys, OAuth, JWT, and Tokens)
- Practical experience in queuing systems/message brokers like ActiveMQ, RabbitMQ, Kafka, Beanstalk, SQS, etc
- Able to create database schemas that represent and support business processes.
- Practical experience with cache technologies such as Memcached, and Redis.
- Experienced with using cloud hosting technologies such as AWS.
- General knowledge in telecommunications (SMSC, VOIP, SMPP, etc.).

**Introduction**
In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.
You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
**Your role and responsibilities**
We are seeking an experienced Data Scientist. The ideal candidate will have a deep understanding of Machine Learning, Generative AI, and Large Language Models, combined with strong leadership abilities. This role will be responsible for business development, overseeing the development and implementation of advanced data-driven solutions as well as mentor a team of talented data scientists.
Technical Oversight:
* Oversee the design, development, and deployment of Machine Learning models and AI solutions.
* Ensure the use of best practices in data science, including model validation, performance monitoring, and continuous improvement.
* Stay informed about the latest developments in AI/ML and drive the adoption of relevant technologies within the team.
Team Development:
* Provide mentorship and professional development opportunities to project and practice team members.
* Actively support in recruitment efforts to attract top talent and grow the team as needed.
* Help Foster a culture of learning and continuous development within the AI/Data Science team.
**Required technical and professional expertise**
Experience:
* 7+ years of experience in Data Science and Machine Learning with at least 1 year of experience in conversational solutions design and development using Watson Assistant or similar conversational AI platforms.
* Proven track record of delivering AI/ML projects.
* Experience with Generative AI and Large Language Models is highly desirable
Technical Skills:
* Proficiency in programming languages such as Python, R, or Scala.
* Deep understanding of Machine Learning frameworks (e.g., TensorFlow, PyTorch) and data processing tools (e.g., SQL, Pandas).
* Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and machine learning deployment.
* Strong knowledge of Natural Language Processing (NLP) and AI ethics.
Leadership Skills:
* Leadership skills with the ability to inspire and motivate junior team members.
* Strategic thinking with the ability to align data science initiatives with business objectives.
* Very good communication skills, capable of conveying complex ideas to a variety of audiences.
* Proven ability to work collaboratively in projects with cross-functional teams.
* Experience in building/scaling data science teams and implementing AI solutions in a large (preferably, consulting) organization.
IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

**Introduction**
In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.
You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
**Your role and responsibilities**
We are seeking an experienced Data Scientist. The ideal candidate will have a deep understanding of Machine Learning, Generative AI, and Large Language Models, combined with strong leadership abilities. This role will be responsible for business development, overseeing the development and implementation of advanced data-driven solutions as well as mentor a team of talented data scientists.
Technical Oversight:
* Oversee the design, development, and deployment of Machine Learning models and AI solutions.
* Ensure the use of best practices in data science, including model validation, performance monitoring, and continuous improvement.
* Stay informed about the latest developments in AI/ML and drive the adoption of relevant technologies within the team.
Team Development:
* Provide mentorship and professional development opportunities to project and practice team members.
* Actively support in recruitment efforts to attract top talent and grow the team as needed.
* Help Foster a culture of learning and continuous development within the AI/Data Science team.
**Required technical and professional expertise**
* 7+ years of experience in Data Science and Machine Learning with at least 1 year of experience in conversational solutions design and development using Watson Assistant or similar conversational AI platforms.
* Proven track record of delivering AI/ML projects.
* Experience with Generative AI and Large Language Models is highly desirable
Technical Skills:
* Proficiency in programming languages such as Python, R, or Scala.
* Deep understanding of Machine Learning frameworks (e.g., TensorFlow, PyTorch) and data processing tools (e.g., SQL, Pandas).
* Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and machine learning deployment.
* Strong knowledge of Natural Language Processing (NLP) and AI ethics.
Leadership Skills:
* Leadership skills with the ability to inspire and motivate junior team members.
* Strategic thinking with the ability to align data science initiatives with business objectives.
* Very good communication skills, capable of conveying complex ideas to a variety of audiences.
* Proven ability to work collaboratively in projects with cross-functional teams.
* Experience in building/scaling data science teams and implementing AI solutions in a large (preferably, consulting) organization.Less
IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.