1 074 Machine Learning jobs in Bahrain
Machine Learning Engineer
Posted today
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Apt Resources is seeking an experienced Machine Learning Engineer for a client in Abu Dhabi's Government & Public Sector. In this role, you will design and deploy cutting-edge AI/ML solutions using Large Language Models (LLMs) like GPT, Llama, and BERT to drive innovation in public services.
This is an exciting opportunity to work on high-impact projects involving Retrieval-Augmented Generation (RAG), fine-tuning, and prompt engineering, ensuring secure, scalable, and compliant AI systems for government applications.
Key Responsibilities:- Develop and optimize AI/ML pipelines for LLMs, focusing on RAG architectures, fine-tuning, and prompt engineering tailored for public sector needs.
- Implement scalable solutions using Python, LangChain, HuggingFace, PyTorch/TensorFlow, and cloud-based ML services (Azure ML preferred).
- Integrate vector/graph databases (Weaviate, Neo4j) into production systems to enhance data retrieval and analysis.
- Deploy and monitor models in production, ensuring adherence to government security and compliance standards.
- Collaborate with cross-functional teams to align AI solutions with public sector objectives (e.g., citizen services, data governance, operational efficiency).
- 6-14 years of hands-on experience in AI/ML, with a strong focus on LLMs and GenAI.
- Expertise in LLM architectures (Transformers), prompt engineering, and RAG implementations.
- Proficiency in Python and ML frameworks (LangChain, LlamaIndex, HuggingFace, Scikit-learn).
- Experience with cloud platforms (Azure ML, AWS, or GCP) and MLOps tools (MLflow, model monitoring).
- Familiarity with vector databases, ETL pipelines, and unstructured data handling.
- Knowledge of government IT standards or secure deployments is a plus.
To be discussed
Machine Learning Engineer
Posted today
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Responsibilities:
- Design, build, and maintain production-ready machine learning models and pipelines.
- Collaborate with data scientists to translate ML models into scalable software solutions.
- Develop and implement strategies for data preprocessing, feature engineering, and model training.
- Optimize ML algorithms for performance, efficiency, and scalability.
- Deploy ML models into production environments and monitor their performance over time.
- Work with software engineering teams to integrate ML capabilities into existing products and services.
- Develop automated testing and validation procedures for ML models.
- Stay current with the latest advancements in machine learning, deep learning, and MLOps.
- Troubleshoot and resolve issues related to model performance and data integrity.
- Contribute to the continuous improvement of our ML infrastructure and best practices.
- Document ML models, code, and deployment processes clearly.
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field.
- Minimum of 3 years of experience 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 tools (e.g., Pandas, SQL).
- Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
- Familiarity with MLOps principles and tools for model deployment and monitoring.
- Solid understanding of machine learning algorithms and statistical modeling.
- Excellent problem-solving and analytical skills.
- Good communication skills and ability to work effectively in a team environment.
- Experience with big data technologies (e.g., Spark) is a plus.
Machine Learning Engineer
Posted 1 day ago
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Responsibilities:
- Develop, implement, and deploy machine learning models and algorithms for various applications.
- Design and build data pipelines for training, testing, and deploying ML models efficiently.
- Collaborate with data scientists and researchers to productionize research prototypes.
- Optimize ML models for performance, scalability, and efficiency in production environments.
- Implement and maintain MLOps practices, including model monitoring, versioning, and automated retraining.
- Work with large, complex datasets, ensuring data quality and integrity.
- Develop APIs and services to integrate ML models into existing applications and platforms.
- Evaluate and select appropriate ML frameworks, tools, and technologies.
- Troubleshoot and debug ML systems, identifying and resolving issues in production.
- Stay up-to-date with the latest advancements in machine learning and software engineering best practices.
- Document ML models, pipelines, and deployment processes.
- Contribute to the overall architecture and design of AI-powered solutions.
- Collaborate with software engineers to integrate ML components into larger systems.
- Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related quantitative field, or equivalent practical experience.
- Proven experience as a Machine Learning Engineer or in a similar role focused on deploying ML models.
- Strong programming skills in Python and proficiency with ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Keras).
- Experience with cloud platforms (AWS, Azure, GCP) and associated ML services.
- Solid understanding of software development best practices, including version control (Git), CI/CD, and testing.
- Experience with data processing frameworks (e.g., Spark, Dask) and database technologies.
- Knowledge of MLOps principles and tools is highly desirable.
- Excellent analytical and problem-solving skills.
- Strong communication and teamwork abilities.
- Ability to work effectively in a fast-paced, collaborative environment.
Machine Learning Engineer
Posted 6 days ago
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Location: Busaiteen, Muharraq, BH
Machine Learning Engineer
Posted 6 days ago
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Job Description
Key Responsibilities:
- Design, develop, and implement machine learning models and algorithms.
- Process, clean, and transform large datasets for ML applications.
- Train, evaluate, and optimize ML models for performance and accuracy.
- Collaborate with cross-functional teams to define and deploy ML solutions.
- Stay current with advancements in AI and machine learning research.
- Develop and maintain production-level ML pipelines.
- Communicate technical findings and insights to stakeholders.
- Contribute to the development of the company's AI strategy.
- Master's or Ph.D. in Computer Science, Data Science, or a related quantitative field.
- Proven experience in developing and deploying machine learning models.
- Strong programming skills in Python and proficiency with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with data manipulation and analysis tools.
- Knowledge of statistical modeling and data mining techniques.
- Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies.
- Excellent problem-solving and analytical abilities.
- Strong communication and interpersonal skills.
Machine Learning Engineer
Posted 15 days ago
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Machine Learning Engineer
Posted 15 days ago
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Machine Learning Engineer
Posted 24 days ago
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In this exciting position, you will work with large datasets, applying advanced algorithms and techniques to solve complex problems. Your responsibilities will span the entire machine learning lifecycle, from data preprocessing and feature engineering to model training, evaluation, and deployment. You will collaborate closely with data scientists, software engineers, and product managers to bring innovative AI-powered features to life. We are looking for a candidate with a strong theoretical foundation in machine learning, practical experience in implementing models, and a passion for staying abreast of the latest advancements in AI.
Key responsibilities include:
- Developing and implementing machine learning algorithms and models using Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Processing and analyzing large datasets to extract meaningful features and insights.
- Designing, training, and evaluating machine learning models for various applications.
- Deploying machine learning models into production environments.
- Collaborating with software engineers to integrate ML models into existing systems and applications.
- Conducting research on new AI and ML techniques and exploring their potential applications.
- Monitoring and maintaining deployed models, iterating as needed.
- Communicating complex technical concepts and results to both technical and non-technical stakeholders.
- Staying current with academic research and industry trends in machine learning and AI.
- Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience.
- Proven experience in building and deploying machine learning models.
- Strong programming skills in Python and expertise in ML libraries.
- Solid understanding of machine learning algorithms, statistical modeling, and data mining techniques.
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps principles.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
- Ability to work effectively in a hybrid work environment.
Machine Learning Engineer
Posted 24 days ago
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Key Responsibilities:
- Develop, train, and evaluate machine learning models using various algorithms and techniques.
- Implement and optimize ML pipelines for data preprocessing, feature engineering, model training, and deployment.
- Collaborate with data scientists to understand model requirements and performance metrics.
- Build and maintain scalable ML infrastructure and systems.
- Deploy ML models into production environments, ensuring their reliability and efficiency.
- Monitor model performance in production and implement necessary updates or retrainings.
- Work with large datasets, ensuring data quality and integrity for ML applications.
- Contribute to the design and architecture of AI-powered products and services.
- Stay current with the latest advancements in machine learning and artificial intelligence research.
- Write clean, well-documented, and maintainable code.
- Troubleshoot and resolve issues related to ML models and systems.
- Collaborate with software engineers to integrate ML models into existing applications.
- Present findings and results to technical and non-technical stakeholders.
- Contribute to the company's strategy for leveraging AI and machine learning.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
- 2+ years of professional experience in machine learning engineering or a similar role.
- Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
- Solid understanding of various ML algorithms (e.g., regression, classification, clustering, deep learning).
- Experience with data processing and manipulation tools (e.g., Pandas, Spark).
- Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
- Knowledge of MLOps principles and practices is a plus.
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
- Ability to work effectively in a fast-paced, collaborative office environment.
Machine Learning Engineer - AI
Posted today
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Responsibilities:
- Design, develop, and implement machine learning models and algorithms.
- Collect, clean, and preprocess large datasets for model training.
- Evaluate and optimize model performance using appropriate metrics.
- Deploy ML models into production environments and monitor their performance.
- Collaborate with data scientists and software engineers to integrate ML solutions.
- Stay updated with the latest research and advancements in machine learning.
- Develop and maintain documentation for ML models and systems.
- Contribute to the company's AI strategy and roadmap.
- Master's or Ph.D. in Computer Science, Data Science, Statistics, or a related quantitative field.
- 3+ years of experience in machine learning engineering or a related role.
- Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of statistical modeling, algorithms, and data structures.
- Experience with data processing and database technologies.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) is a plus.
- Excellent problem-solving and analytical skills.
- Strong communication and teamwork abilities.