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Urgent! Webskitters - AI/ML Engineer - PyTorch/Tensorflow Job Opening In Kolkata – Now Hiring Webskitters Technology Solutions Pvt Ltd

Webskitters AI/ML Engineer PyTorch/Tensorflow



Job description

<p><p><b>Description :</b></p><p><p><b><br/></b></p><b>Key Responsibilities :</b></p><p><br/>- Develop, test, and deploy machine learning models and algorithms in production environments.<br/><br/></p><p>- Work with large datasets to perform data preprocessing, feature engineering, and model training.<br/><br/></p><p>- Build scalable pipelines for model training, validation, deployment, and monitoring.<br/><br/></p><p>- Collaborate with software development teams to integrate ML models into applications.<br/><br/></p><p>- Optimize model performance through hyperparameter tuning, ensembling, and algorithm selection.<br/><br/></p><p>- Stay updated with latest ML research and technologies, recommending adoption where appropriate.<br/><br/></p><p>- Mentor junior engineers and participate in code reviews.<br/><br/></p><p>- Develop tools for automating model testing and deployment workflows.<br/><br/><b>Required Skills & Qualifications :</b></p><p><p><b><br/></b></p>- Bachelors or Masters degree in Computer Science, Machine Learning, Statistics, or related fields.<br/><br/></p><p>- 4 to 6 years of professional experience in machine learning or data science roles.<br/><br/></p><p>- Proficiency in Python and ML libraries like TensorFlow, PyTorch, Scikit-learn.<br/><br/></p><p>- Strong understanding of supervised, unsupervised, and reinforcement learning techniques.<br/><br/></p><p>- Experience with deep learning architectures such as CNNs, RNNs, Transformers.<br/><br/></p><p>- Hands-on experience with data pipelines, feature engineering, and model deployment.<br/><br/></p><p>- Familiarity with cloud platforms like AWS, Azure, or GCP.<br/><br/></p><p>- Experience with containerization tools like Docker and orchestration with Kubernetes is a plus.<br/><br/></p><p>- Strong problem-solving skills and ability to work in a collaborative environment.<br/><br/><b>Preferred Qualifications :</b></p><p><p><b><br/></b></p>- Knowledge of NLP, computer vision, or time-series analysis.<br/><br/></p><p>- Experience with ML lifecycle management tools (MLflow, Kubeflow).<br/><br/></p><p>- Familiarity with big data frameworks (Spark, Hadoop).<br/><br/></p><p>- Experience with DevOps/CI-CD pipelines for ML.</p><br/></p> (ref:hirist.tech)


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