180 Machine Learning jobs in Bahrain
Machine Learning Engineer
Posted today
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Job Description
Key Responsibilities:
- Design, build, and maintain production-grade machine learning systems and pipelines.
- Develop and implement data processing, feature engineering, and model training strategies.
- Optimize ML models for performance, scalability, and efficiency.
- Deploy ML models into production environments using CI/CD and MLOps practices.
- Collaborate with data scientists to translate research models into deployable applications.
- Monitor and maintain deployed ML models, ensuring accuracy and reliability.
- Stay up-to-date with the latest advancements in ML research and technology.
Qualifications:
- Master's or Ph.D. in Computer Science, Data Science, or a related quantitative field.
- 3+ years of experience in machine learning engineering or a similar role.
- Strong programming skills in Python and experience with ML libraries (e.g., Scikit-learn, XGBoost).
- Proficiency with deep learning frameworks (TensorFlow, PyTorch).
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools.
- Solid understanding of software development best practices.
- Excellent problem-solving and analytical skills.
Machine Learning Engineer
Posted 1 day ago
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Job Description
Key responsibilities include developing, training, and evaluating machine learning models using various algorithms and frameworks. You will be responsible for optimizing model performance, ensuring scalability, and integrating ML models into existing software systems and production environments. The Machine Learning Engineer will also contribute to data pipeline development, feature engineering, and model deployment strategies. Collaboration with cross-functional teams to understand project requirements, identify challenges, and propose effective ML-driven solutions is paramount. Staying abreast of the latest advancements in machine learning research and applying them to practical problems will be a core aspect of the role.
The ideal candidate will have a Master's or Ph.D. in Computer Science, Engineering, Mathematics, or a related quantitative field, with a specialization in Machine Learning. A minimum of 3-5 years of professional experience in machine learning engineering or a related role is required. Proficiency in programming languages such as Python, along with extensive experience with ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn), is essential. Strong understanding of software engineering principles, MLOps practices, and experience with cloud platforms (AWS, Azure, GCP) are highly desirable. Excellent problem-solving, analytical, and communication skills are necessary. This hybrid role offers a dynamic work environment in **Tubli, Capital, BH**, with the flexibility to work remotely on certain days, contributing to groundbreaking AI projects.
AI & Machine Learning Engineer
Posted 2 days ago
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Principal AI Engineer - Machine Learning & Deep Learning
Posted today
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Lead Machine Learning Engineer
Posted today
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Job Description
Responsibilities:
- Lead the design, development, and deployment of machine learning models.
- Manage and mentor a team of machine learning engineers.
- Develop and implement data preprocessing and feature engineering pipelines.
- Train, evaluate, and optimize ML models for performance and scalability.
- Deploy ML models into production environments using MLOps best practices.
- Conduct research on new ML algorithms and technologies.
- Collaborate with data scientists and software engineers to integrate ML solutions.
- Ensure the ethical and responsible use of AI and ML.
- Monitor and maintain deployed ML models.
- Communicate technical findings and recommendations to stakeholders.
- Master's or Ph.D. in Computer Science, Machine Learning, AI, or a related quantitative field.
- 5+ years of experience in machine learning engineering or a related role.
- Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
- Strong understanding of ML algorithms, deep learning, and statistical modeling.
- Experience with MLOps and deploying models to production.
- Experience with cloud platforms (AWS, Azure, GCP).
- Excellent problem-solving and analytical skills.
- Strong leadership and team management abilities.
- Excellent communication and presentation skills.
Senior Machine Learning Engineer
Posted today
Job Viewed
Job Description
Responsibilities:
- Design, develop, and deploy machine learning models and algorithms.
- Implement and maintain ML pipelines for data processing, model training, and evaluation.
- Optimize ML models for performance, scalability, and efficiency.
- Collaborate with data scientists and engineers to integrate ML solutions into production systems.
- Conduct research and experimentation to explore new ML techniques and applications.
- Ensure the quality, reliability, and maintainability of ML code and systems.
- Monitor and analyze the performance of deployed ML models.
- Stay current with the latest advancements in machine learning and AI.
- Document ML processes, models, and code.
- Master's or Ph.D. in Computer Science, Data Science, or a related quantitative field.
- Minimum of 5 years of experience in machine learning engineering or data science.
- Strong proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn).
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Knowledge of various ML algorithms, including supervised, unsupervised, and deep learning.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Solid understanding of software engineering principles and version control (e.g., Git).
- Excellent problem-solving, analytical, and communication skills.
- Proven ability to work effectively in a remote, collaborative team environment.
Principal Machine Learning Engineer
Posted 2 days ago
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Job Description
Responsibilities:
- Lead the design, implementation, and optimization of advanced machine learning models and algorithms.
- Develop scalable and robust ML pipelines for data processing, feature engineering, model training, and deployment.
- Collaborate with data scientists, software engineers, and product managers to translate business requirements into technical solutions.
- Mentor junior machine learning engineers and contribute to team growth and knowledge sharing.
- Evaluate and integrate new ML technologies and tools to enhance our ML capabilities.
- Ensure the performance, scalability, and reliability of ML systems in production.
- Conduct research and stay abreast of the latest advancements in machine learning and artificial intelligence.
- Optimize model performance and resource utilization.
- Develop and maintain comprehensive documentation for ML models and systems.
- Contribute to architectural decisions and technical strategy for ML initiatives.
- Present findings and technical designs to cross-functional teams and leadership.
- Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- 7+ years of experience in machine learning engineering, with a significant focus on developing and deploying production-level ML systems.
- Expertise in core ML algorithms, including deep learning (CNNs, RNNs, Transformers), reinforcement learning, and classical ML techniques.
- Proficiency in programming languages such as Python, with extensive experience using ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of software engineering principles, including version control (Git), CI/CD, and testing methodologies.
- Experience with cloud platforms (AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark, Dask).
- Proven ability to architect and build scalable ML infrastructure.
- Excellent problem-solving, analytical, and critical thinking skills.
- Strong communication and leadership skills, with the ability to guide technical teams.
- Experience with MLOps practices and tools is highly desirable.
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Senior Machine Learning Engineer
Posted 2 days ago
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Job Description
Responsibilities:
- Design, develop, and implement scalable machine learning models and algorithms.
- Build and maintain robust ML pipelines for data preprocessing, feature engineering, model training, and deployment.
- Collaborate with data scientists to translate research prototypes into production-ready systems.
- Optimize model performance for accuracy, efficiency, and scalability.
- Develop and manage MLOps practices, including model monitoring, versioning, and automated retraining.
- Work with large datasets, ensuring data quality and integrity throughout the ML lifecycle.
- Stay current with the latest advancements in machine learning and AI technologies.
- Contribute to the design and architecture of our ML platform.
- Troubleshoot and resolve issues related to ML models and infrastructure.
- Mentor junior engineers and share best practices within the team.
- Effectively communicate technical concepts and findings to both technical and non-technical stakeholders.
- Master's degree or Ph.D. in Computer Science, Engineering, Statistics, or a related quantitative field.
- 5+ years of experience in machine learning engineering or a related role.
- Proficiency in Python and deep understanding of ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Strong experience with cloud platforms (AWS, Azure, GCP) and their ML services.
- Expertise in building and deploying machine learning models in production environments.
- Solid understanding of data structures, algorithms, and software engineering principles.
- Experience with MLOps tools and methodologies (e.g., MLflow, Kubeflow, Docker, Kubernetes).
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
- Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
Senior Machine Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
Responsibilities:
- Design, develop, and implement scalable machine learning models and algorithms for various applications, including natural language processing, computer vision, and predictive analytics.
- Collaborate with data scientists and software engineers to translate machine learning models into production-ready systems.
- Process, clean, and transform large and complex datasets to prepare them for model training.
- Evaluate model performance, tune hyperparameters, and iterate on model development to achieve optimal results.
- Stay abreast of the latest research and advancements in machine learning and artificial intelligence.
- Develop and maintain robust data pipelines and ML infrastructure to support model deployment and monitoring.
- Implement and manage MLOps best practices for version control, testing, and deployment of machine learning models.
- Conduct experiments and feasibility studies for new AI/ML approaches and technologies.
- Work closely with product management to understand business requirements and translate them into technical specifications.
- Provide technical leadership and mentorship to junior machine learning engineers.
- Ensure the ethical and responsible development and deployment of AI systems.
- Document research findings, model architectures, and implementation details thoroughly.
- Contribute to the company's intellectual property through patents and publications.
- Debug and resolve issues in production ML systems.
- Present findings and progress to both technical and non-technical audiences.
This is a key on-site role, requiring a strong collaborative presence within our state-of-the-art research facilities. Our client is committed to fostering a culture of innovation and providing its employees with challenging and rewarding projects. The ideal candidate will possess a Master's or Ph.D. in Computer Science, Data Science, or a related quantitative field, with significant experience in machine learning engineering. Proven expertise in programming languages such as Python and libraries like TensorFlow, PyTorch, scikit-learn, and Keras is essential. Strong understanding of distributed computing frameworks (e.g., Spark) and cloud platforms (AWS, Azure, GCP) is required. Experience with MLOps tools and practices is highly desirable. Excellent problem-solving, analytical, and communication skills are critical. You should be adept at working with large datasets and tackling complex algorithmic challenges. We are looking for an innovative thinker with a passion for AI and a track record of delivering impactful machine learning solutions. Join a team that is shaping the future of artificial intelligence and making a real-world difference.
Location: This role is based in Manama, Capital, BH .
Senior Machine Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
Responsibilities:
- Design, develop, and implement robust machine learning models and algorithms.
- Collaborate closely with data scientists and software engineers to integrate ML models into production systems.
- Build and maintain scalable ML pipelines for data preprocessing, model training, evaluation, and deployment.
- Perform feature engineering, model selection, hyperparameter tuning, and performance optimization.
- Implement MLOps best practices for version control, testing, monitoring, and continuous integration/deployment of ML models.
- Analyze large datasets to identify patterns, extract insights, and inform model development.
- Stay up-to-date with the latest research and advancements in machine learning and artificial intelligence.
- Troubleshoot and debug ML systems, ensuring their reliability and performance.
- Document technical designs, experiments, and model performance.
- Communicate technical findings and recommendations to cross-functional teams and stakeholders.
- Contribute to the overall AI strategy and roadmap.
- Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- 5+ years of professional experience in machine learning engineering or a similar role.
- Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, Keras.
- Experience with deep learning architectures and frameworks.
- Solid understanding of statistical modeling, data mining, and data analysis techniques.
- Experience with cloud platforms (AWS, Azure, GCP) and their ML services (e.g., SageMaker, Azure ML, Vertex AI).
- Familiarity with big data technologies (e.g., Spark, Hadoop) and distributed computing.
- Proficiency in software engineering principles, including version control (Git) and CI/CD.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
- Experience with MLOps tools and practices is highly desirable.