2 516 AI Intern jobs in Bahrain
AI/Machine Learning Engineer - Data Science
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Experienced Data Engineer with Data Science & Ai
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**Responsibilities**:
- Design, build and maintain scalable and robust data architecture to support our e-commerce platform.
- Develop and implement systems for collecting, analyzing, verifying, and reporting large sets of data.
- Create and manage data pipelines and integrate complex data sources.
- Ensure the integrity, availability, and security of data.
- Collaborate with cross-functional teams to identify and solve data-related problems.
- Communicate findings and insights to stakeholders in Arabic and English.
- Keep abreast of new technologies and methodologies in data engineering, data science, and AI.
**Required Skills**:
- Proven experience as a Data Engineer with a deep understanding of database architecture.
- Proficient in Python and familiar with data science and machine learning concepts.
- Strong experience with SQL and NoSQL databases, data modeling, and ETL processes.
- Ability to process and analyze large volumes of data in Arabic & English.
- Excellent command of the Arabic language (native) and proficiency in English.
- Familiarity with cloud services (AWS, Azure) and data visualization tools.
**Preferred Qualifications**:
- Knowledge of advanced analytics and predictive modeling.
- Understanding of big data technologies (Hadoop, Spark).
- Experience with Docker, Kubernetes, and CI/CD pipelines.
- Agile methodology experience.
**Join the HIGHBASE TRADING W.L.L team and contribute to shaping the future of B2B e-commerce through data-driven innovation!**
This job has been sourced from an external job board.
AI/Machine Learning Engineer
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- Developing and implementing machine learning models
- Designing AI algorithms and solutions
- Preprocessing and analyzing large datasets
- Evaluating model performance and optimizing parameters
- Deploying AI systems into production
AI/Machine Learning Engineer
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AI/Machine Learning Engineer
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- Designing, developing, and implementing machine learning algorithms and models for various applications.
- Collecting, cleaning, and pre-processing large datasets for model training.
- Evaluating and optimizing model performance using appropriate metrics.
- Deploying machine learning models into production environments and monitoring their performance.
- Collaborating with data scientists, software engineers, and product managers to integrate AI solutions.
- Researching and staying current with the latest advancements in AI and machine learning.
- Developing and maintaining ML pipelines, including data ingestion, feature engineering, and model deployment.
- Building and testing predictive models, classification algorithms, and recommendation systems.
- Utilizing deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Ensuring the scalability, efficiency, and reliability of AI solutions.
- Documenting model architectures, code, and experimental results.
- Contributing to the development of AI strategies and roadmaps.
We are seeking candidates with a Master's or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field. A minimum of 4-6 years of professional experience in machine learning engineering or a related role is required. Strong programming skills in Python, along with experience in ML libraries (e.g., Scikit-learn, Pandas, NumPy), are essential. Proven experience with deep learning frameworks and cloud platforms (AWS, Azure, GCP) is highly desirable. Excellent understanding of statistical modeling, data mining, and algorithm development is critical. Strong analytical and problem-solving skills, coupled with the ability to work independently and as part of a team, are paramount. Experience with big data technologies (e.g., Spark, Hadoop) is a plus. This is an exceptional opportunity to work at the forefront of AI and make a significant impact on developing innovative technological solutions.
AI Solutions Architect - Machine Learning
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AI Research Scientist - Machine Learning
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Key Responsibilities:
- Conduct cutting-edge research in artificial intelligence and machine learning.
- Develop and implement novel machine learning algorithms and models.
- Experiment with deep learning architectures and neural networks.
- Analyze and process large-scale datasets for model training and evaluation.
- Collaborate with cross-functional teams to integrate AI solutions into products.
- Stay current with AI research advancements and emerging technologies.
- Publish research findings in reputable journals and conferences.
- Contribute to the development of intellectual property (patents, trade secrets).
- Design and execute experiments to validate research hypotheses.
- Optimize model performance, efficiency, and scalability.
- Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Proven experience in machine learning research and development.
- Strong background in statistical modeling, deep learning, and data analysis.
- Proficiency in programming languages such as Python, and libraries like TensorFlow, PyTorch, or scikit-learn.
- Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and big data technologies.
- Strong analytical, problem-solving, and critical thinking skills.
- Excellent communication and presentation skills.
- Ability to work independently and as part of a collaborative research team.
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Principal AI Engineer - Machine Learning
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Responsibilities:
- Architect, develop, and deploy advanced machine learning models and AI systems.
- Lead the design and implementation of end-to-end ML pipelines.
- Identify and prototype new AI applications and solutions.
- Mentor and guide junior AI and ML engineers.
- Collaborate with cross-functional teams to integrate AI into products.
- Conduct research on state-of-the-art AI algorithms and techniques.
- Optimize model performance and ensure scalability and reliability.
- Contribute to the company's AI strategy and roadmap.
- Present findings and technical solutions to stakeholders.
- Master's or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
- Minimum of 8 years of experience in AI/ML engineering and development.
- Proven expertise in deep learning, NLP, computer vision, or reinforcement learning.
- Strong programming skills (Python, Java, C++).
- Experience with ML frameworks (TensorFlow, PyTorch) and MLOps.
- Knowledge of cloud computing platforms and big data technologies.
- Excellent problem-solving, analytical, and leadership skills.
- Strong communication and collaboration abilities.
- Ability to lead technical teams and manage complex projects remotely.
Lead AI Engineer - Machine Learning
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Key responsibilities include:
- Designing, developing, and implementing scalable machine learning algorithms and AI models using Python, TensorFlow, PyTorch, or similar frameworks.
- Leading the end-to-end machine learning lifecycle, including data preprocessing, feature engineering, model training, evaluation, and deployment.
- Architecting and building robust AI systems and pipelines for various applications.
- Collaborating with data scientists, software engineers, and product managers to translate business requirements into AI solutions.
- Conducting research on state-of-the-art AI techniques and technologies, identifying opportunities for innovation.
- Mentoring and guiding junior AI engineers, fostering a culture of learning and technical excellence.
- Evaluating and selecting appropriate tools, technologies, and methodologies for AI projects.
- Ensuring the performance, scalability, and reliability of AI models in production environments.
- Writing clean, efficient, and well-documented code.
- Staying abreast of the latest advancements in AI, machine learning, and deep learning.
The ideal candidate will hold a Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. A minimum of 7 years of experience in AI and machine learning development, with at least 2 years in a leadership or senior engineering role, is required. Proven expertise in developing and deploying machine learning models in production environments is essential. Strong programming skills in Python and experience with ML libraries (e.g., scikit-learn, Keras) and cloud platforms (AWS, Azure, GCP) are mandatory. Excellent understanding of statistical modeling, algorithms, and data structures is critical. Exceptional problem-solving, communication, and teamwork skills are a must. This role demands a visionary leader who can drive innovation, solve complex technical challenges, and contribute significantly to the advancement of AI technologies in a fully remote, collaborative setting.
Lead AI Engineer - Machine Learning
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Responsibilities:
- Lead the design, development, and implementation of advanced AI and Machine Learning models.
- Architect scalable and efficient ML pipelines and infrastructure.
- Apply cutting-edge deep learning techniques and algorithms to solve complex problems.
- Collaborate with product managers and stakeholders to define AI product roadmaps and requirements.
- Mentor and guide a team of AI engineers and data scientists.
- Oversee the deployment and monitoring of ML models in production environments.
- Conduct rigorous experimentation, evaluation, and validation of AI models.
- Stay abreast of the latest research and advancements in AI/ML.
- Ensure the ethical and responsible development and deployment of AI systems.
- Contribute to technical strategy and foster a culture of innovation.
- Optimize AI models for performance, accuracy, and scalability.
- Present findings and solutions to technical and non-technical audiences.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related field.
- 5+ years of experience in AI/ML development and deployment.
- Proven experience leading AI/ML projects and teams.
- Expertise in programming languages like Python and libraries such as TensorFlow, PyTorch, Scikit-learn.
- Strong understanding of machine learning algorithms, deep learning architectures (CNNs, RNNs, Transformers), and NLP.
- Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
- Proficiency in data manipulation, statistical analysis, and big data technologies.
- Excellent problem-solving, analytical, and critical thinking skills.
- Strong communication, presentation, and interpersonal skills.
- Experience with MLOps practices is a plus.