DEEP LEARNING RESEARCHER SKILLS, EXPERIENCE, AND JOB REQUIREMENTS
Updated: Mai 21, 2025 - The Deep Learning Researcher applies deep learning to tackle complex, real-world challenges. Develops advanced machine learning solutions using Python-based frameworks such as TensorFlow and Keras, with expertise in object-oriented programming, data structures, and algorithms. Demonstrates a strong research track record with high-quality publications and practical software development experience.
Essential Hard and Soft Skills for a Standout Deep Learning Researcher Resume
- Deep Learning Frameworks
- Machine Learning Algorithms
- Python Programming
- Data Structures and Algorithms
- Computer Vision
- Natural Language Processing
- Neural Network Design
- Model Optimization
- Statistical Analysis
- Big Data Tools.
- Problem-Solving
- Critical Thinking
- Creativity
- Adaptability
- Communication
- Team Collaboration
- Time Management
- Attention to Detail
- Research Skills
- Continuous Learning.
Summary of Deep Learning Researcher Knowledge and Qualifications on Resume
1. BA in Computer Science with 5 years of Experience
- Prior experience with the application of deep learning to solve a nontrivial problem
- Solid understanding of theory, practice, and limitations of deep learning
- Experience with at least one mainstream deep learning framework
- Proficiency in at least one object-oriented programming language
- Practical understanding of data structures and algorithms
- Experience building complex and extensible software
- Track record of research excellence and high-quality publications (e.g. ICLR, NeurIPS, CVPR, ICML, ICCV, etc.)
- Hands-on development of complex machine learning projects using python-based frameworks and tools.
- Hands-on experience with deep learning using common open source frameworks and tools (Keras, TensorFlow, etc.)
- Familiarity with signal processing, computer vision and computer graphics.
2. BA in Electrical Engineering with 6 years of Experience
- Track record of coming up with new ideas, as demonstrated by projects or first author publications conferences
- Software skills spanning from conceptual stage (like Python, R, MATLAB) to deployment stage (feature release, version control)
- Good oral and written communication skills
- Hands-on experience with Machine Learning frameworks (like Tensorflow, PyTorch, and JAX)
- Experience in the agile development process
- Experience with style transfer tasks
- Experience with porting networks to mobile
- Experience with DL models for portrait editing
- Experience with GANs and C++
- Experience with classic computer vision approaches
3. BA in Mathematics with 3 years of Experience
- Extensive experience in modeling, implementing, and training neural networks in high-level languages and frameworks like PyTorch or TensorFlow
- Excellent verbal and written communication
- Significant prior experience with CNNs and other common computer vision network architectures
- Intensive hands-on experience with TensorFlow or other ML frameworks
- Good understanding of common image processing algorithms
- Proficient in C/C++, and OpenCV.
- Deep and wide understanding and knowledge of deep learning algorithms and software.
- Experience in designing and training deep learning models (almost) from scratch.
- Familiarity with generative models such as GANs, flow-based generative models, diffusion probabilistic models and so on.
- Familiarity with cross-modal (vision, language, audio etc.) deep learning or graph neural networks. (3D vision, relation data, etc.)
4. BA in Physics with 2 years of Experience
- Excellent knowledge of Deep Learning
- Strong software engineering skills in C++ and Python
- Experience in object detection, segmentation, classification, and re-identification
- Familiar with scientific computing and systems and have quick model prototyping experience in TensorFlow (preferred)/PyTorch with GPUs
- Experience with GPU acceleration for AI
- English level B2 or higher
- Command of written and spoken Chinese is nice to have
- A proven record of implementing deep learning methods and familiarity with scientific computing frameworks.
- Experience in TensorFlow/PyTorch
- Strong interest in conducting fundamental research.
5. BA in Data Science with 4 years of Experience
- Hands-on development of complex machine learning models using modern frameworks and tools (ideally python based)
- Hands on experience with Deep learning using common open source frameworks and tools (Keras, TensorFlow, Theano, Caffe etc.)
- Strong communication and collaboration skills
- Team player, positive and driven, fast learner
- Practical experience in machine learning (including deep learning) and computer vision/image processing
- Familiar with architectures, modeling, capabilities and limitations of deep neural networks
- Experience in C++ and Python (or a similar language)
- Hands-on experience with current frameworks (e.g., TensorFlow, PyTorch, or DyNet).
- Excellent knowledge of Deep Learning
- Expert understanding of state-of-the-art deep learning techniques, evidenced by a strong publication record in relevant conferences (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, …) or product development.
6. BA in Computer Science with 7 years of Experience
- Deep Learning experience and Machine learning experience targeted to product development
- Expert knowledge of deep learning techniques such as CNN, RNN, LSTM and GAN
- Familiarity with Neural architecture search and network quantization
- Expert-level experience in at least one of TensorFlow, PyTorch, or Caffe
- Expert level in Python (programming and debugging)
- Knowledge of C/C++ and parallel computing paradigms such as OpenCL and CUDA
- Knowledge of software optimization and embedded programming
- Familiarity with AI ethics and its techniques.
- Strong software engineering skills either in Python, C++, distributed computing, GPGPU, or API design.
- Strong research records in top AI conferences.
7. BA in Electrical Engineering with 4 years of Experience
- Passion to create excellent, well-researched algorithms, with a focus on getting ideas to be deployed in products for thousands of doctors.
- Strong analytical and problem solving skills.
- Strong organization skills, delivering work with proper documentation.
- Strong communication and collaboration skills.
- Team player, positive and driven, fast learner
- Python data science and deep learning tools, such as Pytorch and Tensorflow.
- Solid understanding of convolutional neural networks.
- Ability to explain basic principles and decipher new research papers in the field.
- Solid understanding of statistical and strong data analysis skills.
- Broad knowledge of software engineering concepts needed to solve day-to-day challenges in deep learning implementation such as data management, software tools, and software development practice.
8. BA in Mathematics with 4 years of Experience
- Systems Engineering or related work experience.
- Extensive experience in deep neural networks (e.g. CNN, RNN, Attention, ) or deep reinforcement learning.
- Proficiency in designing, implementing, and training DL/RL algorithms in high-level languages/frameworks (e.g. PyTorch, TensorFlow, Caffe).
- Track record of research excellence and high-quality publications (e.g. NeurIPS, CVPR, ICML, ICLR, ICCV, ).
- Expertise in at least one of the following fields: Machine learning theory / optimization methods, Model compression/quantization / optimization for embedded devices, Neural Architecture Search / kernel optimization, Computer vision, Audio and speech / NLP, Deep Generative Models (VAE, Normalizing-Flow, ARM, etc)
- Have theoretical or hands-on experience in computer vision and deep learning algorithms
- Algorithms problem-solver, open-mind thinker
- Able to work independently as well as part of a team
- Experience in 3D Reconstruction algorithms
- Familiar with a variety of deep learning algorithms: detection, segmentation, etc.