About Tejas Networks:
Tejas Networks is an R&D-driven organization focused on being at the forefront of technological advancements in the field of telecommunications. With an R&D team comprising of more than 50% of the organization strength, we have continued to invest in the development of new product capabilities. Our products include carrier-grade optical transmission (based on DWDM/PTN/OTN technologies), fiber broadband (based on GPON/NG-PON), broadband wireless (based on LTE 4G/5G) as well as multi-gigabit Ethernet/IP switching and routing products that are fully designed and manufactured in India…a true pioneer of “Make in India” initiative.
Job Profile:
- Designation - Lead/ Staff Engineer, R&D
- Location: Bangalore
- Experience - 5 to 14 Years
- Key Skills - Machine Leaning/Deep learning/NLP, Reinforcement Learning, time-series (LSTM,ARIMA,SARIMA)
Responsibilities:
- · Interfacing with PLM to understand problem statement and business requirements
- · Interfacing with Optical and wireless domain experts for formulating the problem and solution design
- · Interfacing with the Network Management(NMS) team to understanding the Data Ingest mechanism and UI representation
- · Working with the Field Support team and the Network Element engineers to understand the network performance data.
- · Designing and implementing the Data collection, Feature Engineering, Model selection and evaluation parameters
- · Designing and implementing the customer troubleshooting, debugging interface by Interactive Chatbots
- · Designing and implementing Network/Resource Fault remediation/optimization using AI methodologies
- · Designing and implementing Data/Training/Inference pipelines for Data Ingest/Model Training and Inference
- · Designing and implementing Model Cycle management, Drift Management and Re-training strategy
- · Collecting, cleaning, and organizing network performance data from various sources, including network/element management systems, network elements, and logs.
- · Identifying and extracting patterns in network performance data for efficient use in fault prediction, Anomaly Detection and Forecasting/Trending
- · Contribute to building predictive models and using machine learning/Deep learning techniques to proactively identify network issues.
- · Fine-tuning, debugging, enhancing explainability of models to obtain consistent performance
Skills Required:
- · Deep knowledge and hands-on experience in various Data preparation techniques for Machine Leaning/Deep learning/NLP
- · Deep knowledge and hands-on experience in Machine Learning(Decision Trees, SVM, XBOOST, Random Forest)/Deep learning(MLP,LSTM,RNN)/ Reinforcement Learning/time-series(LSTM,ARIMA,SARIMA) methodologies and modelling techniques
- · Hands-on experience in Data Engineering Tools like Kafka, Storm/Flink, Spark
- · Programming skills in Python with hands-on experiences in libraries, specifically NumPy, Pandas, Matpoltlib, Tensorflow, Keras, Pytorch, Reinforcement Learning libraries
- · Hands-on Experience with SQL and NoSQL Databases like SQL, Elastic, Cassandra, distributed systems and shell scripting using awk etc.
- · Familiarity with Machine learning pipeline tools like Kubeflow, MLflow, Databricks, SeldonCore
- · Familiarity with a public cloud platform like AWS, Azure
- · Excellent problem-solving and communication skills
- · Knowledge of NMS platforms is desirable
- · Knowledge of Optical/Enterprise Switches/Wireless(5G) domains wrt Fault Management/Anomaly identification/ optimization in various domains
- · Hands-on experience in chatbot design and development using NLP open-source frameworks like RASA, Huggingface
- · Hands-on experience in Large Language Model Training, fine-tuning, evaluation for Opensource and Closed Source models like Llama, GPT etc