3,688 AI Software Engineer jobs in Indonesia
Deep Learning
Posted today
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Our mission is to create innovative, robust, and user-friendly digital identity solutions. We are looking for a passionate and skilled Deep Learning AI Scientist specializing in Liveness Detection and Biometrics to join our dynamic team. Your work will directly impact the security and reliability of VIDA's identity verification systems.
Responsibilities:
- Liveness Detection Development: Design, train, and deploy advanced deep learning models to ensure robust liveness detection, preventing spoofing attacks using photos, videos, masks, or other methods.
- Design, train and deploy biometric models to correctly identify users
- Own the full lifecycle of deploying models: from data labelling, working with engineers to design scalable APIs, to monitoring and A/B testing new model versions
- Stay updated with the latest research in biometrics, computer vision, and deep learning, incorporating new techniques to improve VIDA's products
- Collaborate with business, product, operations and engineering teams to deliver impact for our customers
- Work independently or in a team to solve complex problem statements
Requirements:
- An advanced degree in a quantitative field, and 3+ years of hands-on experience in deep learning model development for biometrics or liveness detection or a similar field.
- Deep understanding of modern computer vision techniques, deep learning and machine learning
- Experience developing and deploying machine learning models in production
- Experience with adversarial training to enhance model robustness
- Proficient in Python, C++, Scala, or Java
- Familiarity with modern deep learning frameworks such as TensorFlow, PyTorch, MXNet
- Familiarity with cloud platforms like AWS, GCP, or Azure for model deployment.
- Experience in on-device inference for machine learning models is a plus
- Take pride in taking ownership and driving projects to have business impact
- Thrive in a fast moving collaborative environment
What are we trying to solve?
We have 7.5 billion people on Earth, of which over 1 billion cannot securely prove their identity right now.
Every year, 140 million babies are born, of which 40 million go unregistered.
Simply put, these people are deprived of social benefits, such as education and health, their civil rights to vote and travel; and are excluded from the economy because they cannot sign up for bank accounts, loans, welfare programs etc. We believe this is unacceptable, and needs to change.
At VIDA , We are creating a frictionless digital identity system. One that fulfills the needs and expectations of our times, and is available anywhere, for everyone.
Why are we solving this problem?
The United Nations (UN) and World Bank ID4D initiatives aim to provide everyone on the planet with a legal identity by 2030. This deadline is just 9 years away, we are expecting a digital identity to be a legal human right by then and we at VIDA want to be pioneers in leading this change.
Who are we?
We are a highly driven bunch of people to solve this problem for our own reasons. Whether it is to solve for misleading doctors, or because we didn't get access to fair ration due to corruption - Our collective goal aligns.
Lead AI Software Engineer (Remote)
Posted 8 days ago
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Machine Learning Engineer (Deep Learning)
Posted 5 days ago
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Key Responsibilities:
- 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.
Qualifications:
- 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.
Senior Deep Learning Engineer
Posted 8 days ago
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Responsibilities:
- 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.
Qualifications:
- 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.
AI & Machine Learning Engineer - Deep Learning Specialist
Posted 8 days ago
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AI Research Scientist - Deep Learning
Posted 2 days ago
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Key Responsibilities:
- 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.
AI Research Scientist - Deep Learning
Posted 6 days ago
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AI Research Scientist (Deep Learning)
Posted 8 days ago
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Key Responsibilities:
- Conduct state-of-the-art research in deep learning and artificial intelligence.
- Develop, implement, and optimize novel deep learning algorithms and architectures.
- Design and execute experiments to validate research hypotheses and evaluate model performance.
- Analyze large datasets and extract meaningful insights to inform model development.
- Collaborate with a global team of researchers and engineers to advance AI capabilities.
- Publish research findings in top-tier academic conferences and journals.
- Contribute to the development of AI-powered products and services.
- Stay abreast of the latest advancements in AI, machine learning, and related fields.
- Mentor junior researchers and contribute to the intellectual property of the company.
- Develop and maintain robust, scalable, and efficient AI systems.
- Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Proven track record of significant research contributions in deep learning, demonstrated through publications, patents, or open-source projects.
- Expertise in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).
- Strong programming skills in Python and experience with scientific computing libraries (e.g., NumPy, SciPy, Pandas).
- Deep understanding of various deep learning models, including CNNs, RNNs, Transformers, GANs, etc.
- Experience with cloud computing platforms (AWS, GCP, Azure) and distributed training is a plus.
- Excellent analytical, critical thinking, and problem-solving skills.
- Exceptional communication and collaboration skills, with the ability to articulate complex technical concepts effectively.
- Ability to work independently, self-motivate, and thrive in a fast-paced, remote research environment.
- Experience in areas such as computer vision, NLP, or reinforcement learning is highly desirable.
AI Research Scientist - Deep Learning
Posted 8 days ago
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AI Research Scientist - Deep Learning
Posted 8 days ago
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Job Description
Key Responsibilities:
- Conduct advanced research in deep learning, machine learning, and artificial intelligence.
- Design, develop, and implement novel deep learning architectures and algorithms.
- Experiment with various machine learning techniques and models to solve challenging problems.
- Analyze and interpret large datasets to extract meaningful insights and train models.
- Collaborate with cross-functional teams, including software engineers and product managers, to integrate AI solutions into products.
- Stay current with the latest research papers, trends, and advancements in AI and deep learning.
- Publish research findings in top-tier conferences and journals.
- Develop and maintain high-quality, well-documented code for AI models and experiments.
- Evaluate and benchmark the performance of AI models.
- Contribute to the intellectual property and technical roadmap of the AI division.
- Present research findings and project progress to stakeholders.
- Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 5+ years of relevant research experience in deep learning.
- Strong theoretical understanding of machine learning and deep learning principles.
- Proficiency in programming languages such as Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
- Experience with data preprocessing, feature engineering, and model evaluation.
- Proven ability to conduct independent research and deliver publishable results.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills, with the ability to articulate complex technical concepts clearly.
- Experience with cloud computing platforms (AWS, Azure, GCP) is a plus.
- Demonstrated ability to work effectively in a remote, collaborative team environment.