Senior Machine Learning Engineer Viavi Solutions

4.0 - 8.0 years

0 Lacs

chennai, tamil nadu

On-site

As a Machine Learning Engineer, you will play a key role in developing and enhancing a Telecom Artificial Intelligence Product. This role requires a strong background in machine learning and deep learning, along with extensive experience in implementing advanced algorithms and models to solve complex problems. You will be working on cutting-edge technologies to develop solutions for anomaly detection, forecasting, event correlation, and fraud detection. Your responsibilities will include developing production-ready implementations of proposed solutions using various machine learning and deep learning algorithms. You will test these solutions on live customer data to ensure efficacy and robustness. Additionally, you will research and test novel machine learning approaches for large-scale distributed computing applications. In this role, you will be responsible for implementing and managing the full machine learning operations lifecycle using tools such as Kubeflow, MLflow, AutoML, and Kserve for model deployment. You will develop and deploy machine learning models using PyTorch and TensorFlow to ensure high performance and scalability. Furthermore, you will run and manage PySpark and Kafka on distributed systems with large-scale, non-linear network elements. To excel in this position, you should be proficient in Python programming and experienced with machine learning libraries such as Scikit-Learn and NumPy. Experience in time series analysis, data mining, text mining, and creating data architectures will be beneficial. You should also be able to utilize batch processing and incremental approaches to manage and analyze large datasets. As a Machine Learning Engineer, you will experiment with multiple algorithms, optimizing hyperparameters to identify the best-performing models. You will execute machine learning algorithms in cloud environments, leveraging cloud resources effectively. Continuous feedback gathering, model retraining, and updating will be essential to maintain and improve model performance. Moreover, you should have expertise in network characteristics, transformer architectures, GAN AI techniques, and end-to-end machine learning projects. Experience with leading supervised and unsupervised machine learning methods and familiarity with Python packages like Pandas, Numpy, and DL frameworks like Keras, TensorFlow, PyTorch are required. Knowledge of Big Data tools and environments, as well as MySQL/NoSQL databases, will be advantageous. You will collaborate with cross-functional teams of data scientists, software engineers, and stakeholders to integrate implemented systems into the SaaS platform. Your innovative thinking and creative ideas will contribute to improving the overall platform. Additionally, you will create use cases specific to the domain to solve business problems effectively. Ideally, you should have a Bachelor's degree in Science/IT/Computing or equivalent with at least 4 years of experience in a QA Engineering role. Strong quantitative and applied mathematical skills are essential, along with certification courses in Data Science/ML. In-depth knowledge of statistical techniques, machine learning techniques, and experience with Telecom Product development are preferred. Experience in MLOps is a plus for deploying developed models, and familiarity with scalable SaaS platforms is advantageous for this role.,

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