720 Junior AI jobs in Indonesia
Machine Learning Engineer - AI Development
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Lead Machine Learning Engineer - AI Platform Development
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- Lead the design and development of our core AI/ML platform infrastructure.
- Build and maintain robust, scalable ML pipelines for model training and deployment.
- Implement MLOps best practices for continuous integration, continuous delivery, and monitoring of ML models.
- Develop and optimize machine learning algorithms and models for various applications.
- Collaborate with data scientists to translate research models into production-ready code.
- Ensure the reliability, performance, and scalability of our AI services.
- Contribute to the selection and implementation of ML tools and technologies.
- Mentor and guide junior machine learning engineers.
- Stay current with advancements in ML engineering and AI technologies.
- Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
- Extensive experience in Machine Learning Engineering, with a focus on MLOps and production deployment.
- Proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn.
- Strong experience with cloud platforms (AWS, Azure, GCP) and related ML services.
- Expertise in containerization (Docker) and orchestration (Kubernetes).
- Solid understanding of software development principles and CI/CD pipelines.
- Experience with data pipelines and big data technologies.
- Excellent problem-solving, analytical, and communication skills.
- Demonstrated ability to lead technical projects and mentor team members.
Senior AI/Machine Learning Engineer
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Key responsibilities include researching and implementing state-of-the-art ML techniques, developing robust and scalable AI solutions, and optimizing model performance. You will work with large datasets, utilizing various data mining and statistical analysis techniques. Collaboration is key; you will partner with data scientists, software engineers, and product managers to translate business needs into AI-driven solutions. This involves evaluating and selecting appropriate ML models, performing hyperparameter tuning, and implementing efficient data pipelines. You will also be responsible for documenting code, experiments, and results, and presenting findings to technical and non-technical audiences.
The ideal candidate will have a Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field, with at least 5 years of hands-on experience in developing and deploying ML models in a production environment. Proficiency in programming languages such as Python, along with experience in ML frameworks like TensorFlow, PyTorch, or scikit-learn, is essential. Strong understanding of data structures, algorithms, and software engineering best practices is required. Experience with cloud platforms (AWS, Azure, GCP) and big data technologies is a significant plus. Excellent problem-solving, analytical, and communication skills are necessary for success in this remote role. If you are a seasoned AI/ML professional eager to drive innovation and build impactful AI solutions, we invite you to apply.
AI Research Scientist, Machine Learning
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Key Responsibilities:
- Conduct cutting-edge research in machine learning, deep learning, and related AI fields.
- Develop, implement, and evaluate novel AI algorithms and models for various applications.
- Design and execute experiments to test hypotheses and validate research findings.
- Process and analyze large datasets to extract insights and train AI models.
- Collaborate with engineering teams to integrate research prototypes into production systems.
- Stay abreast of the latest advancements in AI and machine learning through literature review and conference participation.
- Publish research findings in top-tier conferences and journals.
- Mentor junior researchers and contribute to a collaborative research environment.
- Contribute to the intellectual property portfolio through patent applications.
- Present research results to both technical and non-technical audiences.
Qualifications:
- Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
- Proven track record of research in machine learning, evidenced by publications in reputable venues.
- Strong theoretical foundation in machine learning, deep learning, reinforcement learning, and other AI subfields.
- Proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, etc.
- Experience with data processing, feature engineering, and model evaluation.
- Familiarity with cloud computing platforms (AWS, GCP, Azure) and big data technologies is a plus.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and interpersonal skills, with the ability to articulate complex technical concepts clearly.
- Ability to work independently and collaboratively in a remote research setting.
- Experience with specific AI domains such as NLP, computer vision, or robotics is advantageous.
AI Research Scientist - Machine Learning
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AI Research Scientist - Machine Learning
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Responsibilities:
- Conduct cutting-edge research in artificial intelligence and machine learning.
- Design, develop, and implement advanced machine learning algorithms and models.
- Analyze large, complex datasets to identify patterns and build predictive models.
- Evaluate and optimize the performance of AI systems and applications.
- Collaborate with cross-functional teams to integrate AI solutions into products and services.
- Stay current with the latest research and advancements in AI and machine learning.
- Publish research findings in reputable conferences and journals.
- Develop and maintain code for AI models and experiments.
- Contribute to the overall AI strategy and roadmap.
- Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related field.
- Proven experience in machine learning, deep learning, and natural language processing.
- Proficiency in Python and major machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of algorithms, data structures, and statistical modeling.
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong written and verbal communication skills.
- Ability to work independently and collaboratively in a hybrid research environment.
AI Research Scientist - Machine Learning
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Responsibilities:
- Conduct original research in machine learning, deep learning, and related AI fields.
- Design, develop, and implement novel AI algorithms and models.
- Experiment with various machine learning frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python).
- Analyze large datasets to extract insights and train AI models.
- Collaborate with other researchers and engineers to translate research findings into practical applications.
- Publish research findings in leading academic conferences and journals.
- Stay current with the latest advancements in AI and machine learning literature.
- Contribute to the development of intellectual property and patents.
- Evaluate and benchmark the performance of AI models.
- Present research ideas and results to technical and non-technical audiences.
- Mentor junior researchers and contribute to a collaborative research environment.
- Develop prototypes and proof-of-concepts for new AI-driven features and products.
- Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
- Proven track record of research and publication in AI/ML conferences (e.g., NeurIPS, ICML, ICLR) or top journals.
- Strong theoretical understanding of machine learning concepts, including supervised, unsupervised, and reinforcement learning.
- Proficiency in programming languages such as Python and experience with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with data manipulation, analysis, and visualization tools.
- Excellent analytical, mathematical, and problem-solving skills.
- Strong communication and collaboration skills, with the ability to articulate complex technical concepts clearly.
- Ability to work independently and drive research projects from conception to completion in a remote setting.
- Experience with distributed computing frameworks and large-scale data processing is a plus.
- Familiarity with cloud platforms (AWS, Azure, GCP) for AI/ML development is advantageous.
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AI Research Scientist - Machine Learning
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AI Engineer - Machine Learning Specialist
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Key Responsibilities:
- Design, develop, and implement machine learning models and algorithms.
- Process and analyze large datasets for training and evaluation.
- Build and optimize deep learning models using frameworks like TensorFlow or PyTorch.
- Develop NLP and computer vision solutions.
- Deploy ML models into production environments.
- Collaborate with cross-functional teams to integrate AI solutions into products.
- Conduct research on state-of-the-art AI and ML techniques.
- Monitor and maintain deployed ML models for performance and accuracy.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Minimum of 3 years of experience in Machine Learning Engineering or Data Science.
- Strong proficiency in Python and ML libraries (e.g., scikit-learn, pandas, NumPy).
- Hands-on experience with deep learning frameworks (TensorFlow, PyTorch).
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Knowledge of data structures, algorithms, and software engineering principles.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills for remote teamwork.
Senior AI Engineer - Machine Learning
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Responsibilities:
- Design, develop, and implement machine learning models and algorithms.
- Preprocess and clean large datasets for model training.
- Perform feature engineering and selection to improve model performance.
- Evaluate model performance using appropriate metrics and techniques.
- Deploy ML models into production environments.
- Collaborate with data scientists and software engineers to integrate AI solutions.
- Research and apply state-of-the-art ML techniques and tools.
- Optimize model performance and scalability.
- Contribute to the development of AI strategy and roadmaps.
- Document AI models, processes, and methodologies.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
- Minimum of 4 years of experience in AI and machine learning development.
- Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
- Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, deep learning).
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
- Ability to work effectively in a hybrid work environment.
- Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.