73 AI Technology jobs in Bahrain
AI Solutions Architect - Deep Learning
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Key Responsibilities:
- Design and architect scalable, robust, and efficient AI/ML solutions, with a strong emphasis on deep learning.
- Translate business requirements into technical AI/ML strategies and roadmaps.
- Lead the selection and implementation of appropriate deep learning frameworks, tools, and platforms.
- Oversee the development and training of deep learning models, including neural networks, CNNs, RNNs, and transformers.
- Ensure the integration of AI solutions with existing systems and infrastructure.
- Collaborate with data scientists, engineers, and product managers to deliver cutting-edge AI applications.
- Provide technical leadership and mentorship to development teams.
- Stay abreast of the latest research and advancements in AI, deep learning, and related fields.
- Evaluate the performance of deployed AI models and identify areas for improvement.
- Develop best practices and guidelines for AI solution development and deployment.
The successful candidate will possess a Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field, with a minimum of 7-9 years of hands-on experience in AI/ML, particularly in deep learning. Proven experience in architecting and deploying complex AI solutions in a production environment is essential. Expertise in programming languages like Python, and proficiency with deep learning libraries such as TensorFlow, PyTorch, or Keras, is a must. Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies is highly desirable. Excellent problem-solving skills, strategic thinking, and strong communication and leadership abilities are critical for this role in Salmabad, Northern, BH .
Machine Learning Engineer
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Machine Learning Engineer
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Responsibilities:
- Design, develop, and implement machine learning algorithms and models.
- Process, clean, and transform large datasets for machine learning tasks.
- Build and maintain data pipelines for model training and evaluation.
- Collaborate with data scientists and software engineers to deploy ML models into production.
- Monitor and optimize the performance of deployed models.
- Conduct experiments to test and validate different ML approaches.
- Stay current with the latest advancements in machine learning and AI.
- Document models, algorithms, and processes clearly and concisely.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
- Proven experience (2+ years) as a Machine Learning Engineer or in a similar role.
- Strong programming skills in Python and experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
- Proficiency in data manipulation and analysis using libraries like Pandas and NumPy.
- Experience with SQL and NoSQL databases.
- Familiarity with cloud platforms (AWS, Azure, GCP) and ML deployment tools.
- Solid understanding of machine learning concepts, algorithms, and best practices.
- Excellent problem-solving abilities and attention to detail.
Machine Learning Engineer
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Key Responsibilities:
- Design, develop, and implement machine learning models and algorithms.
- Build and maintain scalable ML pipelines for data preprocessing, feature engineering, model training, and deployment.
- Collaborate with cross-functional teams to identify business needs and translate them into ML solutions.
- Evaluate and optimize model performance using rigorous testing and validation techniques.
- Stay current with the latest advancements in AI and machine learning research.
- Deploy ML models into production environments, ensuring reliability and efficiency.
- Work with big data technologies and cloud platforms.
- Develop and maintain documentation for ML models and processes.
- Contribute to the overall AI strategy and roadmap of the company.
- Present findings and insights to stakeholders at various levels.
Qualifications:
- Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
- Proven experience in developing and deploying machine learning models in a production setting.
- Proficiency in programming languages such as Python, R, or Scala.
- Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Strong understanding of statistical modeling, data mining, and predictive analytics.
- Familiarity with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.
- Experience with version control systems like Git.
- Ability to work effectively in an agile development environment.
Lead Machine Learning Engineer
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Principal Machine Learning Engineer
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Machine Learning Engineer (AI)
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Senior Machine Learning Engineer
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- Design, develop, and implement machine learning models and algorithms.
- Build and optimize data pipelines for ML model training and deployment.
- Collaborate with data scientists and stakeholders to define project requirements.
- Deploy machine learning models into production environments.
- Monitor and maintain the performance of deployed ML systems.
- Conduct rigorous testing and validation of ML models.
- Research and apply new machine learning techniques and technologies.
- Optimize ML models for scalability, efficiency, and accuracy.
- Develop and maintain MLOps practices and infrastructure.
- Mentor junior machine learning engineers and contribute to team knowledge sharing.
- Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- 6+ years of hands-on experience in machine learning engineering.
- Expertise in Python and popular ML libraries (scikit-learn, TensorFlow, PyTorch).
- Proven experience with cloud ML platforms (e.g., AWS SageMaker, Azure ML).
- Strong understanding of MLOps principles and tools.
- Experience with big data technologies (e.g., Spark, Hadoop).
- Excellent programming skills and software development best practices.
- Strong analytical and problem-solving capabilities.
- Ability to work effectively in a collaborative team environment.
Lead Machine Learning Engineer
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Senior Machine Learning Engineer
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- Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Minimum of 6 years of experience in machine learning engineering or a related role.
- Strong proficiency in Python and relevant ML libraries (e.g., Scikit-learn, Pandas, NumPy).
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
- Proven experience in deploying ML models into production environments using MLOps practices.
- Solid understanding of software development principles, including version control (Git) and CI/CD.
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Familiarity with big data technologies (e.g., Spark, Hadoop).
- Excellent analytical, debugging, and problem-solving skills.
- Strong communication and collaboration abilities.
- Experience in model optimization and performance tuning.