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Senior R&D Engineer
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Thông tin cơ bản
Mức lương:
Thỏa thuận
Chức vụ:
Nhân viên
Ngày đăng tuyển:
31/08/2024
Hạn nộp hồ sơ:
01/10/2024
Hình thức:
Toàn thời gian
Kinh nghiệm:
Trên 2 năm
Số lượng:
1
Giới tính:
Không yêu cầu
Nghề nghiệp
Ngành
Địa điểm làm việc
- Địa điểm làm việc: Hồ Chí Minh
Mô tả Công việc
AI/ML Model Development and Deployment: Participate in the development, deployment, and optimization of AI/ML models, particularly in the areas of image processing, natural language processing (NLP), and neural networks. Work with and optimize architectures such as Sklearn, Stats, CNN, RNN, GraphNN, YOLO, Transformer, BERT, T5, and their variants.
Data Processing: Execute data preprocessing steps, including image and text processing, normalization, and extraction of key information from diverse datasets. Be flexible in data usage and optimization to ensure the highest efficiency in model performance.
Source Control and CI/CD: Utilize Git/GitLab for source control and implement CI/CD systems to automate testing and deployment processes for models.
Containerization: Employ Docker for containerizing applications and environments, facilitating consistent and straightforward model deployment.
MLOps: Engage in building and deploying large-scale MLOps systems, using frameworks like MLflow and ClearML to manage the model lifecycle from development to deployment.
Research and Development: Contribute to large-scale AI/ML research and development projects, proposing and testing innovative, optimized solutions for complex problems.
Model Deployment: Perform model quantization and conversion to formats such as ONNX Runtime, TFLite, TensorRT, etc.. to optimize performance across different deployment environments.
Service Development: Develop AI/ML services, with proficiency in at least one technology such as RabbitMQ, Apache Kafka, or SparkML for data processing and model deployment in production environments.
Teamwork and Independence: Demonstrate the ability to work independently as well as collaborate effectively with team members. Be adaptable and proactive in ensuring tasks are completed on time.
AI/ML Model Development and Deployment: Participate in the development, deployment, and optimization of AI/ML models, particularly in the areas of image processing, natural language processing (NLP), and neural networks. Work with and optimize architectures such as Sklearn, Stats, CNN, RNN, GraphNN, YOLO, Transformer, BERT, T5, and their variants.
Data Processing: Execute data preprocessing steps, including image and text processing, normalization, and extraction of key information from diverse datasets. Be flexible in data usage and optimization to ensure the highest efficiency in model performance.
Source Control and CI/CD: Utilize Git/GitLab for source control and implement CI/CD systems to automate testing and deployment processes for models.
Containerization: Employ Docker for containerizing applications and environments, facilitating consistent and straightforward model deployment.
MLOps: Engage in building and deploying large-scale MLOps systems, using frameworks like MLflow and ClearML to manage the model lifecycle from development to deployment.
Research and Development: Contribute to large-scale AI/ML research and development projects, proposing and testing innovative, optimized solutions for complex problems.
Model Deployment: Perform model quantization and conversion to formats such as ONNX Runtime, TFLite, TensorRT, etc.. to optimize performance across different deployment environments.
Service Development: Develop AI/ML services, with proficiency in at least one technology such as RabbitMQ, Apache Kafka, or SparkML for data processing and model deployment in production environments.
Teamwork and Independence: Demonstrate the ability to work independently as well as collaborate effectively with team members. Be adaptable and proactive in ensuring tasks are completed on time.Yêu Cầu Công Việc
Education: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
Experience: A minimum of 2 years of experience in Machine Learning or AI. • Programming Skills: Proficiency in Python. Experience with R or C++ is a plus.
Technical Expertise: Experience in image processing, text processing, preprocessing techniques, and neural networks. Extensive knowledge of architectures like CNN, RNN, GraphNN, YOLO, Transformer, BERT, T5, and their variants. Experience in natural language processing, information extraction, and object detection.
Mathematical Foundation: A strong foundation in mathematics, particularly in areas like probability, statistics, linear algebra, and optimization. • Data Flexibility: Flexibility in data usage and optimization to maximize the effectiveness of AI/ML models.
Project Experience: Preference for candidates who have participated in large-scale projects involving image analysis, Natural language processing, Objects detection, Objects recognitions, OCR and the application of Large Language Models (LLMs), RAG.
Model Development: Ability to independently develop, innovate, or optimize models ranging from simple to complex.
Source Control and CI/CD: Experience with Git/GitLab and setting up CI/CD systems.
Containerization and MLOps: Experience with Docker and MLOps frameworks such as MLflow and ClearML to manage and deploy AI/ML models effectively.
Model Deployment: Experience with model quantization and conversion to ONNX Runtime, TFLite, TensorRT to optimize deployment.
Service Development: Experience with messaging and data processing systems like RabbitMQ, Apache Kafka, or SparkML.
Additional Preferences: Candidates with experience in building and deploying MLOps systems, Data Warehouses, Data Lakes, and those who have contributed to AI/ML research are highly preferred.
Academic Contributions: Preference will be given to candidates who have made significant contributions to AI/ML research, including scientific publications.
Supplementary Skills: Creative thinking, quick learning ability, and the capacity to apply new techniques in AI/ML. Strong communication skills and effectiveness in crossdisciplinary collaboration.Chế độ bảo hiểm
Du Lịch
Chế độ thưởng
Chăm sóc sức khỏe
Đào tạo
Tăng lương
Nghỉ phép năm
CLB thể thao
AI/ML Model Development and Deployment: Participate in the development, deployment, and optimization of AI/ML models, particularly in the areas of image processing, natural language processing (NLP), and neural networks. Work with and optimize architectures such as Sklearn, Stats, CNN, RNN, GraphNN, YOLO, Transformer, BERT, T5, and their variants.
Data Processing: Execute data preprocessing steps, including image and text processing, normalization, and extraction of key information from diverse datasets. Be flexible in data usage and optimization to ensure the highest efficiency in model performance.
Source Control and CI/CD: Utilize Git/GitLab for source control and implement CI/CD systems to automate testing and deployment processes for models.
Containerization: Employ Docker for containerizing applications and environments, facilitating consistent and straightforward model deployment.
MLOps: Engage in building and deploying large-scale MLOps systems, using frameworks like MLflow and ClearML to manage the model lifecycle from development to deployment.
Research and Development: Contribute to large-scale AI/ML research and development projects, proposing and testing innovative, optimized solutions for complex problems.
Model Deployment: Perform model quantization and conversion to formats such as ONNX Runtime, TFLite, TensorRT, etc.. to optimize performance across different deployment environments.
Service Development: Develop AI/ML services, with proficiency in at least one technology such as RabbitMQ, Apache Kafka, or SparkML for data processing and model deployment in production environments.
Teamwork and Independence: Demonstrate the ability to work independently as well as collaborate effectively with team members. Be adaptable and proactive in ensuring tasks are completed on time.
AI/ML Model Development and Deployment: Participate in the development, deployment, and optimization of AI/ML models, particularly in the areas of image processing, natural language processing (NLP), and neural networks. Work with and optimize architectures such as Sklearn, Stats, CNN, RNN, GraphNN, YOLO, Transformer, BERT, T5, and their variants.
Data Processing: Execute data preprocessing steps, including image and text processing, normalization, and extraction of key information from diverse datasets. Be flexible in data usage and optimization to ensure the highest efficiency in model performance.
Source Control and CI/CD: Utilize Git/GitLab for source control and implement CI/CD systems to automate testing and deployment processes for models.
Containerization: Employ Docker for containerizing applications and environments, facilitating consistent and straightforward model deployment.
MLOps: Engage in building and deploying large-scale MLOps systems, using frameworks like MLflow and ClearML to manage the model lifecycle from development to deployment.
Research and Development: Contribute to large-scale AI/ML research and development projects, proposing and testing innovative, optimized solutions for complex problems.
Model Deployment: Perform model quantization and conversion to formats such as ONNX Runtime, TFLite, TensorRT, etc.. to optimize performance across different deployment environments.
Service Development: Develop AI/ML services, with proficiency in at least one technology such as RabbitMQ, Apache Kafka, or SparkML for data processing and model deployment in production environments.
Teamwork and Independence: Demonstrate the ability to work independently as well as collaborate effectively with team members. Be adaptable and proactive in ensuring tasks are completed on time.Yêu Cầu Công Việc
Education: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
Experience: A minimum of 2 years of experience in Machine Learning or AI. • Programming Skills: Proficiency in Python. Experience with R or C++ is a plus.
Technical Expertise: Experience in image processing, text processing, preprocessing techniques, and neural networks. Extensive knowledge of architectures like CNN, RNN, GraphNN, YOLO, Transformer, BERT, T5, and their variants. Experience in natural language processing, information extraction, and object detection.
Mathematical Foundation: A strong foundation in mathematics, particularly in areas like probability, statistics, linear algebra, and optimization. • Data Flexibility: Flexibility in data usage and optimization to maximize the effectiveness of AI/ML models.
Project Experience: Preference for candidates who have participated in large-scale projects involving image analysis, Natural language processing, Objects detection, Objects recognitions, OCR and the application of Large Language Models (LLMs), RAG.
Model Development: Ability to independently develop, innovate, or optimize models ranging from simple to complex.
Source Control and CI/CD: Experience with Git/GitLab and setting up CI/CD systems.
Containerization and MLOps: Experience with Docker and MLOps frameworks such as MLflow and ClearML to manage and deploy AI/ML models effectively.
Model Deployment: Experience with model quantization and conversion to ONNX Runtime, TFLite, TensorRT to optimize deployment.
Service Development: Experience with messaging and data processing systems like RabbitMQ, Apache Kafka, or SparkML.
Additional Preferences: Candidates with experience in building and deploying MLOps systems, Data Warehouses, Data Lakes, and those who have contributed to AI/ML research are highly preferred.
Academic Contributions: Preference will be given to candidates who have made significant contributions to AI/ML research, including scientific publications.
Supplementary Skills: Creative thinking, quick learning ability, and the capacity to apply new techniques in AI/ML. Strong communication skills and effectiveness in crossdisciplinary collaboration.Chế độ bảo hiểm
Du Lịch
Chế độ thưởng
Chăm sóc sức khỏe
Đào tạo
Tăng lương
Nghỉ phép năm
CLB thể thao
Khu vực
Quy mô:
200 - 500 nhân viên
Địa điểm:
Tầng 3, số 184 Lê Đại Hành, Phường 15, Quận 11, Thành phố Hồ Chí Minh, Việt Nam
Công TY TNHH Một Thành Viên EKINO VIETNAM, công ty CNTT của Pháp chuyên cung cấp các giải pháp kỹ thuật số xuất sắc, là một công ty của Pháp chuyên về Conception, Design, Development và Maintenance các giải pháp kỹ thuật số: Nền tảng kỹ thuật số, website, các ứng dụng di động.
Ekino xây dựng các giải pháp sáng tạo với công nghệ mở. Các giải pháp của chúng tôi được tích hợp với các hệ thống kế thừa (thương mại điện tử, thanh toán, CRM, ...) và hỗ trợ các nhà quản lý kinh doanh và kỹ thuật số đạt được các mục tiêu mà họ đã đề ra.
Vào năm 2013 tại Việt Nam, Ekino đã thành lập một nhóm nghiên cứu tại Việt Nam để mở rộng khả năng mình.
Vào năm 2016, văn phòng ở Pháp của chúng tôi được công nhận là một trong những nơi làm việc tốt nhất (Greatest Place to Work), đây là một nguồn cảm hứng tuyệt vời cho team Việt Nam tiếp tục phát triển mạnh mẽ bằng niềm đam mê, sự nhiệt huyết và hợp tác của họ.
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