V
Deep Learning Engineer
Vriba
Remote · India Full-time Lead 2w ago
About the role
Position
Deep Learning Engineer (Remote)
Required Experience
7–10 years.
Job Summary
Data Scientist with good hands‑on experience in developing state of the art and scalable Machine Learning models and their operationalization, leveraging off‑the‑shelf workbench production.
Key Responsibilities
- Hands on experience in Python data‑science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib
- Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.)
- Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence
- Good understanding of any of the cloud platform – AWS, Azure or GCP
- Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self‑motivation and self‑driven to find solutions for problems.
- Should be able to mentor and guide mid to large sized teams under him/her
Job Requirements
- Strong experience on Spark with Scala/Python/Java
- Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment
- Proficiency in Statistical and Probabilistic methods such as SVM, Decision‑Trees, Bagging and Boosting Techniques, Clustering
- Proficiency in Core NLP techniques like Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc. Understanding of Generative AI / Large Language Models / Transformers would be a plus
Must have Skills
- Real‑world experience in implementing machine learning/statistical/econometric models/advanced algorithms
- Breadth of machine learning domain knowledge
- Experience in application of machine learning algorithms (classification, regression, deep learning, NLP, etc.)
- Experience with a ML/data‑centric programming language (such as Python, Scala, or R) and ML libraries (pandas, numpy, scikit‑learn, etc.)
- Experience with Apache Hadoop / Spark (or equivalent cloud‑computing/map‑reduce framework)
Educational Requirements
B.E./B.Tech/MCA
Application
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Requirements
- Strong experience on Spark with Scala/Python/Java
- Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment
- Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering
- Proficiency in Core NLP techniques like Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc.
- Real-world experience in implementing machine learning/statistical/econometric models/advanced algorithms
- Breadth of machine learning domain knowledge
- Experience in application of machine learning algorithms (classification, regression, deep learning, NLP, etc.)
- Experience with a ML/data-centric programming language (such as Python, Scala, or R) and ML libraries (pandas, numpy, scikit-learn, etc.)
- Experience with Apache Hadoop / Spark (or equivalent cloud-computing/map-reduce framework)
Responsibilities
- Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib
- Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.)
- Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence
- Good understanding of any of the cloud platform – AWS, Azure or GCP
- Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines.
- Should be able to mentor and guide mid to large sized teams under him/her
Skills
AWSAzureCaffeConfluenceDockerGCPGITJiraKerasLing PipeMatplotlibNLTKNumPyOpenAIPandasPyCaretPythonPyTorchRScalaSeabornSparkSparkMLSQLStanford NLPTensorFlow
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