Pawan kumar

Angestellt, Senior Machine Learning Engineer, DISH Digital Solutions GmbH
Köln, Deutschland

Fähigkeiten und Kenntnisse

Web-Entwicklung
Jenkins
Object Oriented Programming
Flask (Webframework)
AWS
Sicherheit
Networking
Amazon S3
Firebase
Load
DNS
Programmiersprache
FastAPI
LLMs
MLOps
PYTEST
integrating
predictions
SonarQube
Skalierbarkeit
Werkzeug
Komplettsysteme
Klassifizierung
data generation
integrations
Agent
User-Authentisierung
Linux
Lernen
Datenbank
API
Code
Agile Entwicklung
Infrastruktur
Google Cloud
Software
PyTorch
Cloud Computing
IT-Anwendungen
Kommunikation
Informationstechnologie
Kubernetes
Plattform
Computer
Forschung
Full-Stack-Entwicklung
Qualität
Deep Learning
Windows
Websphere
Forecast
Automatisierung
ETL
Softwareentwicklung
CI/CD
Lieferung
Projekte
Strategie
Data Quality
Weblogic
Künstliche Intelligenz
Informatik
Dask
Dataflow
LLM
low latency
NLTK
Spacy
user satisfaction
experiments
experimentation
stakeholders
Metriken
Maschinelles Lernen
Innovation
Algorithmus
Chatbot
Konferenz
Data Governance
Apache Airflow
Python
Google Cloud Platform
Data Science
Data Engineering
dev ops
big query
Project Management
ETL (Extract, transform, load)
Software Development
Agile Development
Database
Docker
Data Warehouse
Computer Science
Data Analysis
English Language
Git
Natural Language Processing
Keras
NumPy
Data Modelling
TensorFlow
Machine Learning
German
Artificial intelligence
Python pandas
Apache Spark
Management
Big Data
Deep learning
GitLab
ML
Flask (web framework)
Team leadership
Collaboration Management
Führung
Team work
Communication skills
Reliability
SQL
Architecture
Django
Large language models
Generative AI
Software framework

Werdegang

Berufserfahrung von Pawan kumar

  • Bis heute 10 Monate, seit Okt. 2024

    Senior Machine Learning Engineer

    DISH Digital Solutions GmbH

    1. Led 5+ ML projects implementing LLM system for synthetic data generation, OCR, invoice automation; 40% cost reduction. 2. Directed MLOps standardization across 5 units, establishing CI/CD frameworks; 40% faster time-to-market. 3. Orchestrated Terraform cloud automation; 60% faster provisioning, 25% cost reduction. 4. Deployed RAG-powered chatbots with multi-agent architecture; 25% higher user satisfaction. 5. Implemented AI compliance framework; zero bias/non-compliance incidents.

  • 2 Jahre und 8 Monate, März 2022 - Okt. 2024

    Machine Learning Engineer

    DISH Digital Solutions GmbH

    1. Led migration of applications and projects to GCP, optimizing infrastructure and enhancing scalability. 2. Forecasted and reduced compute costs for ML lifecycle. 3. Developed and implemented CI/CD and ML pipelines using MLflow, Kubeflow, and TFX. 4. Ensured scalability, security, and governance of ML infrastructure through maintenance and optimization. 5. Productionalized Generative AI solutions, including RagPowered Engines/Bots and a Prompt Engineering SaaS platform, focusing on AI and data governance.

  • 1 Jahr und 5 Monate, Okt. 2020 - Feb. 2022

    Full Stack Machine Learning Researcher

    Leibniz Universität Hannover

    Designed RL-based scheduling algorithm for Kubernetes clusters under EU-fundedBraine Project, improving resource utilization by 40% and reducing pod scheduling latency by 60% across distributed environments.

  • 3 Jahre und 1 Monat, Sep. 2015 - Sep. 2018

    Software Engineer

    Infosys Limited

    1. Managed installation, configuration, administration, and automation of WebSphere Application Server and Oracle WebLogic Server. 2. Set up security permissions in WebSphere environments to authenticate against LDAP servers and secure consoles using SSL. 3. Troubleshot JEE runtime environment issues by analyzing server logs, diagnosing thread-dumps, and heap-dumps using MAT, IBM heap analyzer, and Oracle Visual JVM.

Sprachen

  • Englisch

    Fließend

  • Deutsch

    Gut

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