886 Neural Networks jobs in Indonesia

• Assist senior AI engineers and researchers in developing and testing AI models.
• Learn and apply fundamental concepts of machine learning and deep learning.
• Perform data collection, cleaning, and preprocessing tasks.
• Write and execute code for AI algorithms and applications.
• Participate in team projects and contribute to collaborative development efforts.
• Document research findings, experimental results, and code.
• Attend training sessions and workshops to enhance AI knowledge and skills.
• Support the debugging and troubleshooting of AI systems.
• Stay updated with emerging trends and technologies in AI.
• Contribute to the continuous improvement of AI tools and processes.

• Bachelor's degree or current enrollment in a Bachelor's program in Computer Science, Software Engineering, Data Science, Mathematics, Statistics, or a related quantitative field.
• A strong passion for Artificial Intelligence and Machine Learning.
• Basic understanding of programming concepts, preferably in Python.
• Familiarity with basic mathematical concepts (linear algebra, calculus, probability).
• Excellent analytical and problem-solving skills.
• Strong desire to learn and adapt to new technologies.
• Good communication and collaboration skills for remote teamwork.
• Self-motivated with strong time management and organizational abilities.
• Previous project work or academic research in AI/ML is a plus.
• Ability to commit to the full duration of the apprenticeship program.

• Assist senior AI engineers in developing, training, and evaluating machine learning models.
• Collect, clean, and pre-process data for AI projects.
• Write and maintain code for AI algorithms and applications, primarily in Python.
• Contribute to the research and implementation of new AI techniques.
• Participate in code reviews and team discussions.
• Learn and apply best practices in software development and MLOps.
• Document research findings, methodologies, and code.
• Assist in the creation of reports and presentations on project progress.
• Gain exposure to various AI domains, such as natural language processing, computer vision, and reinforcement learning.
• Collaborate effectively with team members in a virtual setting.
• Actively seek feedback and opportunities for professional development.

• Recent graduate with a Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent demonstrable knowledge.
• Foundational understanding of machine learning concepts and algorithms.
• Proficiency in Python programming.
• Familiarity with AI/ML libraries and frameworks such as TensorFlow, PyTorch, scikit-learn.
• Basic knowledge of data structures and algorithms.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills, suitable for a remote team.
• Eagerness to learn and adapt to new technologies.
• Self-motivated and able to manage time effectively in a remote work environment.
• A genuine passion for Artificial Intelligence and its applications.

• Assisting in the development and implementation of machine learning models.
• Supporting data preprocessing, cleaning, and feature engineering tasks.
• Participating in the testing and evaluation of AI algorithms.
• Learning and applying deep learning frameworks (e.g., TensorFlow, PyTorch).
• Contributing to code documentation and project reports.
• Collaborating with senior developers on AI research and development initiatives.
• Exploring and applying techniques in natural language processing or computer vision.
• Troubleshooting and debugging AI systems under guidance.
• Staying updated with the latest advancements in AI and machine learning.
• Learning agile development methodologies in a remote context.

• Currently pursuing or recently completed a degree in Computer Science, Engineering, Data Science, or a related quantitative field.
• Solid understanding of programming languages such as Python.
• Basic knowledge of machine learning concepts and algorithms.
• Familiarity with data structures and algorithms.
• Strong analytical and problem-solving abilities.
• Excellent written and verbal communication skills.
• Ability to work independently and collaboratively in a remote team environment.
• Enthusiasm for Artificial Intelligence and a strong desire to learn.

• Design, train, and evaluate deep learning models for various applications (e.g., computer vision, natural language processing, recommendation systems).
• Implement and optimize ML algorithms using frameworks such as TensorFlow, PyTorch, or Keras.
• Perform data preprocessing, feature engineering, and data augmentation.
• Develop and maintain robust ML pipelines for model training, evaluation, and deployment.
• Collaborate with data scientists and engineers to integrate ML models into production systems.
• Stay current with the latest research and advancements in deep learning and AI.
• Conduct experiments and analyze results to improve model performance.
• Write clean, efficient, and well-documented code.
• Troubleshoot and debug ML models and systems.
• Present findings and model performance to technical and non-technical stakeholders.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
• Minimum of 4 years of experience in machine learning, with a strong focus on deep learning.
• Proficiency in Python and ML libraries (e.g., NumPy, Pandas, Scikit-learn).
• Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
• Solid understanding of deep learning architectures (e.g., CNNs, RNNs, Transformers).
• Experience with data manipulation and analysis tools.
• Strong understanding of statistical modeling and evaluation metrics.
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and ML services is a plus.
• Excellent problem-solving and analytical skills.
• Effective communication and collaboration abilities.

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yang akan mengikuti sesi Pelatihan
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• Akses ke jaringan karier & peluang industri melalui program Job Connector
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• Sertifikat kompetensi resmi dari PT DIKA (berlaku seumur hidup)
• 8 Minggu pelatihan online interaktif + sesi mentoring langsung
• Dibimbing oleh mentor berpengalaman lebih dari 5 tahun
• Akses LMS 24/7 dengan materi seumur hidup
• Pelatihan intensif Hard Skill & Soft Skill sebagai bekal dunia kerja

Note : Skema pendaftaran akan dijelaskan oleh tim Marketing Juara Coding lebih lanjut.

• Develop and implement comprehensive ethical guidelines, policies, and best practices for AI development and deployment.
• Conduct ethical risk assessments and impact analyses for new AI products and features.
• Advise engineering and research teams on mitigating bias, ensuring fairness, and promoting transparency in AI algorithms.
• Design and oversee ethical review processes for AI projects.
• Stay current with evolving AI ethics research, regulations, and industry standards globally.
• Develop training materials and conduct workshops to foster an ethical AI culture within the organization.
• Collaborate with external stakeholders, including academics, policymakers, and civil society groups, on AI ethics matters.
• Contribute to public discourse and thought leadership on responsible AI.
• Investigate and resolve ethical concerns raised regarding AI systems.

• Advanced degree (Master's or Ph.D.) in a relevant field such as AI Ethics, Philosophy, Computer Science with an AI Ethics focus, Law, or Social Sciences.
• Demonstrated experience in AI ethics, responsible AI, or a related field.
• Deep understanding of AI concepts, machine learning, and their societal implications.
• Familiarity with ethical frameworks, bias detection and mitigation techniques, and AI governance models.
• Exceptional analytical, critical thinking, and problem-solving skills.
• Excellent written and verbal communication skills, with the ability to explain complex ethical issues to diverse audiences.
• Proven ability to influence and collaborate effectively across interdisciplinary teams in a remote environment.
• Experience in policy development or ethical review boards is a plus.

• Develop and implement ethical frameworks and policies for AI development and deployment.
• Conduct ethical risk assessments and bias audits for AI models and datasets.
• Advise engineering and product teams on ethical AI best practices and regulatory compliance.
• Lead research into emerging ethical challenges in AI and propose solutions.
• Develop and deliver AI ethics training programs for internal stakeholders.
• Collaborate with legal, policy, and external stakeholders on AI governance matters.
• Communicate complex ethical concepts clearly and effectively to diverse audiences.
• Contribute to the company's thought leadership in responsible AI.

• Advanced degree (Master's or Ph.D.) in Philosophy, Ethics, Computer Science, Law, Sociology, or a related interdisciplinary field with a focus on technology ethics.
• Demonstrated experience in AI ethics, responsible AI, or technology policy.
• Strong understanding of machine learning concepts and AI systems.
• Proven ability to develop and implement ethical guidelines and frameworks.
• Excellent analytical, critical thinking, and problem-solving skills.
• Exceptional communication, presentation, and interpersonal skills.
• Experience in a remote work environment, demonstrating strong self-discipline and collaboration abilities.
• Familiarity with relevant AI regulations and standards (e.g., GDPR, AI Act).
• Ability to translate abstract ethical principles into practical guidance for technical teams.

• Design, develop, and implement advanced deep learning models and algorithms.
• Conduct research on new deep learning architectures and techniques.
• Prepare and preprocess large datasets for model training.
• Train, evaluate, and fine-tune deep learning models for optimal performance.
• Deploy models into production environments, ensuring scalability and reliability.
• Collaborate with cross-functional teams to define AI project requirements and goals.
• Stay current with the latest advancements in deep learning, machine learning, and AI research.
• Write clean, efficient, and well-documented code in Python or other relevant languages.
• Optimize model performance for various hardware platforms.
• Mentor junior engineers and contribute to knowledge sharing within the team.
• Evaluate and integrate third-party AI tools and libraries.
• Document research findings, model designs, and implementation details.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 5+ years of experience in deep learning research and development, with a strong portfolio of successful projects.
• Expertise in neural network architectures (CNNs, RNNs, Transformers, etc.).
• Proficiency in deep learning frameworks like TensorFlow, PyTorch, or Keras.
• Strong programming skills in Python and experience with relevant libraries (NumPy, Pandas, Scikit-learn).
• Solid understanding of statistical modeling, data mining, and machine learning principles.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Excellent analytical, problem-solving, and debugging skills.
• Strong communication and collaboration skills, with the ability to work effectively in a remote team.

• Conduct advanced research in deep learning, machine learning, and artificial intelligence.
• Develop and implement novel deep learning models, algorithms, and techniques.
• Design and execute experiments to validate research hypotheses and evaluate model performance.
• Analyze large datasets and interpret complex results to extract meaningful insights.
• Publish research findings in leading academic journals and present at international conferences.
• Collaborate with other researchers and engineers on interdisciplinary projects.
• Stay abreast of the latest advancements and trends in AI and deep learning research.
• Contribute to the development of intellectual property and potential product applications.
• Mentor junior researchers and contribute to a collaborative research environment.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Demonstrated experience in deep learning research, evidenced by publications in top-tier venues.
• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong programming skills in Python and experience with relevant libraries (e.g., NumPy, SciPy, Pandas).
• Solid understanding of various neural network architectures and machine learning algorithms.
• Excellent analytical, mathematical, and problem-solving skills.
• Ability to work independently and drive research projects in a remote setting.
• Strong communication and presentation skills.
• Experience with large-scale data processing and distributed computing is a plus.