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Deep Learning Engineer

Job Title : Sr Deep Learning Engineer Location : Remote Experience : 2-5 years Skillset : Must Have : - Languages & Frameworks : Python (Pandas, NumPy, Sklearn, TensorFlow, Keras, Pytorch, Tkinter, Selenium, Beautiful soup, regular expressions, Flask), R Programming, MySQL, Analytics, Data Crawling, Flask API, Statistical Modelling, Visualization. - Proficient in at least a few of the following : Regression, Bayesian methods, Tree-based learners, SVM, RF, XgBoost, Time Series Modeling, Clustering - Problem-solving : Ability to break the problem into small parts and apply relevant techniques to drive required outcomes. - Experience with classical ML algorithms and its underline mathematics for data patterns and profiling. - Experience working with Hyper-parameter optimisation, feature engineering, feature selection, calibration of models and benchmarking performance via AUC/Gini, Capture rates, K-S and other relevant metrics - Should be strong in Data Structures and Algorithms. Should be able to do code complexity analysis/optimisation. - Should be able to read research papers and pick ideas to quickly reproduce research in the most comfortable Deep Learning library. - Good Verbal and Written communication skills Good To Have : - Exposure to Production Deployment of ML models - Exposure to Deep learning technologies like Computer Vision and NLP. - Exposure to Cloud Technologies like AWS or Azure Cloud. - Exposure to deployment tools like Docker and Kubernetes - Exposure to Big Data Technologies like Hadoop, Spark, Hive etc. Responsibilities : - To provide expertise on multiple phases of a ML Project/research lifecycle from design, implementation, optimisation and support. - Analyse real world problems and identify AI and ML solutions - Explore and visualise data to gain an understanding, and then identify differences in data distribution that could affect performance in the real world - Verifying data quality, and/or ensuring it via data cleaning - Find available online datasets that could be used for training - Generate Synthetic data and augmentation pipelines - Define validation strategies - Train and retrain Models and tune their hyper parameters wherever required - Fine tune pertained models via transfer learning. - Design & Develop high-quality products using python, ML Libraries

Remote

Anywhere in India/Multiple Locations

Datatobiz - Senior Deep Learning Engineer (2-5 yrs)

About the Role : We are seeking a highly skilled and motivated Deep Learning Engineer to join our team. The ideal candidate will have a strong background in Machine Learning, Deep Learning, and Python programming, along with the ability to solve real-world problems using data-driven techniques. You will play a critical role in building scalable ML models, researching novel algorithms, and contributing to all phases of the ML lifecycle. Key Responsibilities : - Work across various phases of the ML project lifecycle from design and development to optimization and deployment. - Analyze complex, real-world problems and devise ML/DL solutions. - Explore, visualize, and preprocess data to ensure quality and relevance. - Identify, acquire, or generate training data, including synthetic data and augmentation strategies. - Build and validate models using classical ML algorithms and deep learning frameworks. - Perform hyperparameter tuning, feature engineering, and model calibration. - Implement and optimize solutions using best practices in ML engineering and statistical modeling. - Fine-tune pre-trained models using transfer learning techniques. - Develop APIs and interfaces using Flask or similar frameworks to integrate models with production systems. - Stay updated with the latest research; implement and prototype ideas based on academic papers. Required Skill Set : Languages & Frameworks : - Python (including Pandas, NumPy, Scikit-learn, TensorFlow, Keras, PyTorch, Tkinter, Selenium, BeautifulSoup, Flask) - R Programming - MySQL Core Competencies : - Strong understanding of ML algorithms : Regression, Bayesian methods, Tree-based learners (RF, XGBoost), SVM, Clustering, Time Series Modeling - Proficient in problem decomposition and applying analytical approaches to derive outcomes - Strong knowledge of the mathematical foundations behind ML algorithms - Experience in feature selection, hyperparameter tuning, model evaluation using AUC, Gini, K-S, Capture rates, etc. - Excellent coding skills in data structures and algorithms, including complexity analysis and optimization - Ability to read and implement cutting-edge research papers - Solid communication skills both verbal and written Good to Have : - Experience with production deployment of ML models - Exposure to deep learning applications in NLP and Computer Vision - Familiarity with cloud platforms such as AWS or Azure - Working knowledge of containerization tools like Docker and Kubernetes - Exposure to Big Data technologies (e.g., Hadoop, Spark, Hive)

Datatobiz - Senior Deep Learning Engineer (3-5 yrs)

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