Summary
Overview
Work History
Education
Skills
Technicaltalksworkshops
Areas Of Interest
Personal Information
Projects
Interests
Timeline
Work Availability
Accomplishments
Work Preference
Generic
Andalam  SeshuPhani

Andalam SeshuPhani

AI/ML Engineer
Pulivendula

Summary

Meticulous Technical Lead strictly adheres to both client-provided technical requirements and internal business goals. Balances project prioritization to fulfill both contractual obligations and internal revenue requirements. Provides foresight and management designed to grow satisfied customer bases and revenue figures.

Overview

12
12
years of professional experience
2
2
years of post-secondary education

Work History

Technical Lead

EFI
08.2023 - 04.2024
  • Worked as Technical Lead for ChatBot Development, AI/ML model building using NLP & Fine tuning of LLM & Data Preparing dealing with EFI customers of Industrial Printing across globe.
  • Mentored junior developers through regular 1-on-1 meetings, providing guidance on best practices, coding standards, and career growth opportunities.
  • Maintained close communication with clients throughout project life cycles for accurate progress reporting and prompt issue resolution.

Senior SoftwareEngineer

CommScope Networks (R&D-Telecommunication-5G Onecell)
12.2021 - 07.2023
  • Worked on AI/ML models like NLP for chatbot creation for Internal Organizational purpose.
  • Worked across various functional teams for there required ChatBot creation along with pdf , document uploader.

Software Engineer

HSBC Electronic Data Processing
01.2019 - 12.2021
  • Worked on Linear regression & Logistic models for data processing before it moves other departments.
  • Also gained enough experience working on Decision trees & random forest models for data processing.
  • Worked with spacy & nltk models of NLP model for pre processing a Generative AI model.


Devops Engineer

Virtusa
01.2016 - 01.2019
  • Improved code deployment efficiency by automating processes with CI/CD pipelines.
  • Maintained version control systems like Git or SVN for seamless collaboration among developers and engineers during project lifecycles.
  • Designed and implemented containerization strategies using Docker and Kubernetes, improving resource utilization and management.
  • Worked on Ansible playbooks for automating several tasks like central cloud implentation & upgradation.

AWS Cloud Engineer

NTT Data
06.2013 - 01.2016

· Working as a part of AWS build team in launching Ec2 Linux instances in Amazon cloud

· Associating Elastic ip's to the Instances and resizing the volumes of Ec2 Instances

· Creating EBS volumes and attaching to Instances and creating partitions and drives

· Creating security groups, changing rules and restricting access of Amazon Linux Instances

· Setup and managed security groups, Nat gateways specific to VPC environment & Setup Auto Scaling to scale-in and scale-out the Ec2 Instances according to the need of web traffic

· Setup Application & Elactic Load Balancing to check the healthy instances and routing the web traffic


Linux Administrator

CtrlS Datacenters
01.2011 - 05.2013

· Experience in Remote Infrastructure System Tasks using Ticket based architecture to perform day-to-day System admin activities

· Application software installations upon clients request

· Experience on Disk Quota ,providing disk quota/inode quota to the client machines

· Experience on File system and Disk management using Linux LVM

· User management, Creating user-accounts and groups using Shell scripts

· Administering (Creating, Mount/Umount) the File Systems

· Trouble shooting and configuring NIS client- server & FTP client-server in Linux

· Processes administration and management like monitoring, start/stop/kill various processes

· Scheduled various regular, future queue tasks by using crontab

Implementing RAID levels (RAID 0, RAID 1, and RAID 5)

Education

MBA - Business Decision, ERP & Marketing

Sree Nidhi Institue Of Science And Technology
Hyderabad, India
08.2007 - 11.2009

Skills

Cloud Platform: IAAS, PAAS, SAAS, DAAS, Private Cloud

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Technicaltalksworkshops

  • Provided multiple training and workshops to the current team and organization on AI/ML models
  • Provided Internal Demonstration on Technical tools like Ansible & Terraform to the Team.
  • Conducted technical talks to various Engineering Institutions for Final year BE Students

Areas Of Interest

  • OpenAI, LLM, Generated AI
  • Data Science
  • NLP and Image Processing

Personal Information

  • Date of Birth: 12/10/1985
  • Nationality: Indian

Projects

Metrics Analytics & Auto Detection Recovery Framework (Real-time and Historical trends) For On-Premises & ORAN Deployment Infrastructure. (One cell5G ORAN-Open Radia Access Network), System Architect, Dev & Integration & Deployment, Grafana, Prometheus, Thanos, MINIO, Python, AWS (EC2, EKS, S3, Lambda, VPC), Edge-computing, Custom-Library, Helm Chart HTML5, DevOps, Container Networking, Kubernetes Engine, fluentd, fluent-bit, Microservice, AI/ML, Kibana, Elastic Search, Centralized monitoring solution for multi-cluster environments with long-term storage capabilities. Supports all types of system metrics (multi-cluster, cluster, node, Pod, container, Application, etc.). Provide single pane of glass observability to assess the overall health of deployments & Live status. Interactive dashboards, easily spot anomalies & trends. Raise email alerts in real-time proactively or upon encountering any fault. Ingest all alerts into Elasticsearch for simplified searching, filtering & aggregation. Auto Detection and Recovery Framework. Automated root-cause analysis using ML Techniques. Separate Historical and Realtime Dashboard for Cluster, Node, Pod, and Container overview. Automated Troubleshooting and Log Analytics Framework. (4G,5G Platform & gNB Applications), System Architect, Dev & Integration & Deployment, Grafana, Elastic Search, Logstash, Kibana, S3, Python, AWS (EC2,EKS,S3,VPC), Container Networking, DevOps, K8S Engine, Elastic Cloud, Fluent bit, AI/ML, NLP, LLM, Centralized logging solution for text-based logs generated by all One Cell products. Available as a managed service on the public cloud and on-prem as a Pipeline solution for 4G, and 5G. Dashboards, real-time queries, and aggregations. Create dashboards to automate repeated analysis saving countless hours of effort. Computation and Analysis of Logs that have interesting keywords like Fail, Terminate, Disconnect, and Error. Automated Log Analysis during Ingestion (Perforce logs, Debug Logs, Failure Logs, Alarms, RP Logs). Framework supports many options to cover typical log analysis cases otherwise performed manually by users. A flexible YAML-based framework to define rules for performing complex log analysis. Industrial IIOT platform with Mind sphere & Edge Platform for On-premises Data Processing (Edge Apps and Mind Apps, Edge Computing, cloud), Backend Developer (Services & Cloud) and integration, Siemens Edge Box (Hardware), Mind sphere, IIOT, Node.js Restful Service, Angular 9, Containers, K8's, HTML5, MQTT, IOWA Service, DevOps, Rancher Orchestration Engine, Postgres, Azure, Data Pipeline, Mind Apps and Edge Apps for KPI, Notification, data time series, and diagnostic data analysis. These Apps will perform various calculations based on different formulas and perform alarm management, notifications. Processing real-time telemetered data pumping from OPCUA. Filtering real-time data from field devices via Scada server. Siemens Edge Computing for in-house or on-premises data computing and distribution with north-bound cloud connectivity. TIA Cloud Service with Elasticity & Distribution Web Version (Highly Scalable Objects), Backend Developer (Services and Cloud), AWS (IaaS, PaaS), K8s, Containers, C#, DevOps, WCF, Restful Service, Angular 5, Microservices, SOA, The commission engineer and plant manager can use it during production, browser availability & modularizable. It helps to configure a distributed plant & an infinite number of plant objects and elastic plant hierarchy can be distributed to multiple runtimes. It provides infinite scalable objects, Scalability, and elasticity on a common plant model. Pay as per usage"model, replacing the single license model. Trust and Trace with Blockchain and AI/ML (Mango Juice procession plant), AI/ML, AWS, Containers, Blockchain, DevOps, NodeJS, Restful Service, Angular 8, python, K8's, Human to Human, Machine to Human, machine to machine, Use IOT to push findings to blockchain. Traceable history of multiple stakeholder data and give insights. OCR scanner, Classification/forecast, Anomaly detector, Mind-sphere, and cloud integration. Edge integration of multiple algorithms and apps. Use of AI over blockchain for trust calculation. Use IOT to push findings to the blockchain. Customer experience can be one of the reasons for validating AI models to know if they can be trusted. Industrial- ID Fan Condition Monitoring App (Edge Apps - Edge Computing, Cloud Computing), Siemens Edge Box, AI/ML, OPCUA, PLC, Node.js Sockets, Restful Service, Angular 8, Containers, HTML5, MQTT, DevOps, Rancher, Kubernetes Orchestration Engine, Postgres, docker, python, Analytics @ Edge: Bringing intelligence at the machine edge, and Edge-computing based solution. Disparate & Multivariate approach: Analysis of Electrical parameters, Critical Processes, and Health Parameters, Actionable Insights, configurable Recommendation Engine. Anomaly Prognosis: Anomaly detection using Statistical methods and machine learning algorithms. Trend Analysis: Real time data monitoring and Real time vs Predicted data analysis

Interests

AI & Computer Vision Technology

Timeline

Technical Lead

EFI
08.2023 - 04.2024

Senior SoftwareEngineer

CommScope Networks (R&D-Telecommunication-5G Onecell)
12.2021 - 07.2023

Software Engineer

HSBC Electronic Data Processing
01.2019 - 12.2021

Devops Engineer

Virtusa
01.2016 - 01.2019

AWS Cloud Engineer

NTT Data
06.2013 - 01.2016

Linux Administrator

CtrlS Datacenters
01.2011 - 05.2013

MBA - Business Decision, ERP & Marketing

Sree Nidhi Institue Of Science And Technology
08.2007 - 11.2009

Work Availability

monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Accomplishments

  • Supervised team of 5 staff members.
  • Achieved expected result by introducing nlp techniques for data pre-processing tasks.

Work Preference

Work Type

Full TimeContract Work

Work Location

On-SiteRemoteHybrid

Important To Me

Work-life balancePaid sick leaveHealthcare benefitsWork from home optionFlexible work hoursPersonal development programsCompany Culture
Andalam SeshuPhaniAI/ML Engineer