11+ BERT Jobs in Chennai | BERT Job openings in Chennai

• A Natural Language Processing (NLP) expert with strong computer science fundamentals and experience in working with deep learning frameworks. You will be working at the cutting edge of NLP and Machine Learning.

Roles and Responsibilities

• Work as part of a distributed team to research, build and deploy Machine Learning models for NLP.
• Mentor and coach other team members
• Evaluate the performance of NLP models and ideate on how they can be improved
• Support internal and external NLP-facing APIs
• Keep up to date on current research around NLP, Machine Learning and Deep Learning

Mandatory Requirements

• Any graduation with at least 2 years of demonstrated experience as a Data Scientist.

Behavioral Skills

Strong analytical and problem-solving capabilities.

• Proven ability to multi-task and deliver results within tight time frames
• Must have strong verbal and written communication skills
• Strong listening skills and eagerness to learn
• Strong attention to detail and the ability to work efficiently in a team as well as individually

Technical Skills

Hands-on experience with

• NLP
• Deep Learning
• Machine Learning
• Python
• Bert

Preferred Requirements

• Experience in Computer Vision is preferred

Job Description:

We are seeking a Cloud & AI Platform Engineer to design and operate AI-native infrastructure that supports large-scale machine learning, generative AI, and agentic AI systems. 

This role will focus on building secure, scalable, and automated multi-cloud platforms across AWS, Azure, GCP, and hybrid on-prem environments, enabling teams to deploy LLMs, AI agents, and data-driven applications reliably in production. 

You will work at the intersection of cloud engineering, MLOps, LLMOps, DevOps, and data infrastructure, helping build platforms that support RAG pipelines, vector search, AI model lifecycle management, and AI observability. 

Key Responsibilities

AI & Agentic Infrastructure 

• Design infrastructure to support agentic AI systems, autonomous agents, and multi-agent workflows. 
• Build scalable runtime environments for LLM orchestration frameworks. 
• Enable deployment of AI copilots, assistants, and autonomous decision systems. 

Common frameworks may include: 

• LangChain 
• LlamaIndex 
• AutoGPT 

LLMOps & AI Model Lifecycle 

Design and manage LLMOps pipelines for the full lifecycle of large language models: 

• Model deployment 
• Prompt management 
• Versioning 
• Evaluation and testing 
• Model monitoring 

Integrate with AI platforms such as: 

• Azure Machine Learning 
• Amazon SageMaker 
• Vertex AI 

Retrieval-Augmented Generation (RAG) Infrastructure 

Design and optimize RAG pipelines that integrate enterprise knowledge with LLMs. 

Responsibilities include: 

• Document ingestion pipelines 
• Embedding generation workflows 
• Knowledge indexing 
• Query orchestration 
• Retrieval optimization 
• Support scalable semantic search architectures. 

Vector Database & Knowledge Infrastructure 

Deploy and manage vector databases used for AI applications and semantic retrieval. 

Common technologies include: 

• Pinecone 
• Weaviate 
• Milvus 
• FAISS 

Responsibilities include: 

• Index optimization 
• Query latency tuning 
• Scalable embedding storage 
• Hybrid search architecture 

Multi-Cloud AI Infrastructure 

Design and maintain AI-ready infrastructure across: 

• Amazon Web Services 
• Microsoft Azure 
• Google Cloud Platform 

Key responsibilities include: 

• GPU infrastructure management 
• Distributed training environments 
• Hybrid cloud integrations with on-prem data centers 
• Infrastructure scaling for AI workloads 

Data Platforms & Integration 

• Support deployment and optimization of data lakes, data warehouses, and streaming platforms. 
• Work with data engineering teams to ensure secure and scalable data infrastructure. 

Cloud Architecture & Infrastructure 

• Design and implement scalable multi-cloud infrastructure across Azure, AWS, and Google Cloud. 
• Build hybrid cloud architectures integrating on-premise environments with cloud platforms. 
• Implement high availability, disaster recovery, and auto-scaling architectures for AI workloads. 

DevOps, Platform Engineering & Automation 

Build automated cloud infrastructure using modern DevOps practices. 

Tools may include: 

• Terraform 
• Docker 
• Kubernetes 
• GitHub Actions 

Responsibilities include: 

• Infrastructure as Code (IaC) 
• Automated deployments 
• CI/CD pipelines for AI models and services 
• Platform reliability and scalability 

AI Observability & Monitoring 

Implement observability frameworks to monitor AI systems in production. 

This includes: 

• Model performance monitoring 
• Prompt evaluation 
• Hallucination detection 
• Latency and throughput analysis 
• Cost monitoring for LLM usage 

Tools may include: 

• Arize AI 
• WhyLabs 
• Weights & Biases 

Security, Governance & Responsible AI 

Ensure AI systems follow strong governance and security practices. 

Responsibilities include: 

• Data privacy and compliance 
• Model governance frameworks 
• Secure model deployment 
• Monitoring model bias and drift 
• AI risk management 

Support enterprise frameworks for Responsible AI and AI compliance. 

Data & Security 

• Experience with data lake architectures, distributed storage, and ETL pipelines 
• Knowledge of data security, encryption, IAM, and compliance frameworks 
• Familiarity with AI governance and responsible AI practices 

Required Skills 

Cloud & Infrastructure 

• Strong experience in Azure (must have), AWS or GCP 
• Hybrid and multi-cloud architecture 
• GPU infrastructure management 

DevOps & Automation 

• Kubernetes 
• Docker 
• Terraform 
• CI/CD pipelines 

AI / ML Platforms 

• MLOps pipelines 
• Model deployment 
• Model monitoring 

AI Application Infrastructure 

• Vector databases 
• RAG pipelines 
• LLM orchestration frameworks 

Programming 

Experience in one or more languages: 

• Python 
• Go 
• Java 
• TypeScript 

Preferred Qualifications 

• Experience building AI copilots or autonomous agents 
• Knowledge of distributed model training - Knowledge of GPU infrastructure and distributed training 
• Familiarity with AI evaluation frameworks - Familiarity with model monitoring, drift detection, and AI observability 
• Experience building enterprise AI platforms 

Education & Experience 

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 
• 4–8+ years experience in cloud infrastructure, DevOps, or platform engineering 
• Experience working in data-driven or AI-focused environments 

What Success Looks Like 

• Reliable ML model deployment pipelines - Reliable infrastructure for LLMs and AI agents, Scalable RAG knowledge platforms 
• Efficient multi-cloud infrastructure management - Fast deployment cycles for AI products 
• Secure and scalable AI-ready cloud platforms 
• Strong automation and governance across cloud and AI systems 

1. 1. Experience with React JS, React Native, JavaScript including DOM Manipulation and the JavaScript object model.
   2. Thorough understanding of React Native and its core Principles.
   3. Hands on experience on React Native Framework at least 1 year.
   4. Understanding of native build tools like Xcode, Gradle etc.
   5. Capability to write Well-documented code with Javascript that is easily readable.
   6. Good Knowledge of HTML5, CSS.
   7. Familiarity with code versioning tools (Such as Git or SVN)
   8. Knowledge about Offline Storage, REST APIs, and document request model
   9. Familiarity with modern front-end build pipelines and tools.
   10. Experience with common front-end development tools such as Babel, Web pack, NPM and YARN etc.
   11. Experience with Native Mobile app deployment on App store and google play store.

JD For PL/SQL

·      Minimum 4+ years of experience in PL/SQL

·      Exposure to create and maintain large database with complex requirement

·      Deep understanding on procedures, functions and collections

·      Hands on experience in analytical and aggregate functions

·      Ability to create and manage triggers

·      Experience in database transaction management

·      Provide support to java developers on need.

·      Understanding on Agile methodologies

·      Good written and oral communication skills

Interview: Direct walk-in Interview only

Location: Chennai & Madurai

Work mode: Hybrid

Location: Siruseri

Job Description

• Act as a technical expert for CRM projects.
• Be responsible for working on D365 CRM development, support, and integration projects.
• Lead or participate in design and architecture sessions with key business users, gathering and documenting business processes and requirements for the system.
• Architect the CRM system, related customizations, and reports to model the business and organizational process.
• Advise business users on best practices for CRM, development, or integration processes.
• Writing technical specifications for planned work.
• Build and configure CRM forms, views, dashboards, and workflows.
• Develop SSRS reports using Microsoft SQL and FetchXML. Maintain code repository, VSTS backlog, and source control.
• Effectively utilize SDK and 3rd party tools such as XRM Toolbox for administration of CRM system. Support of the application including fixing application issues.

Eligibility Criteria:

• 5+ years’ experience with different versions of Microsoft CRM including D365 CRM.
• Experience in migrations, customizations, JavaScript, C#, .NET, HTML, SQL Server, and SSRS including plugins, scripting, and form creation.
• Experience in workflow development including complex ones.
• Experience with CRM API, REST/ODATA, and SOAP endpoints.
• Experience in integrating D365 CRM with other applications is preferred.

Job Sector: IT , Software

Job Type: Permanent

Location: Chennai

Experience: 8 -10 Years

Salary: 12 – 14 LPA

Education: Any Graduate with relevant experience

Notice Period: Immediate or max 30days NP

Key Skills: Business Analysis, Requirement gathering

CV submission closing date: 15/07/2021

Contact at triple eight two zero nine four two double seven

Required Skills:

1. Strong BA with presentation skills
2. US Customer Engagement experience
3. Self-driven – should be able to independently work towards business objective
4. Should have past experience of program management
5. Strong communication skills
6. Must be flexible to work in overlapping times with US PST timezone

• Starting and stopping SAP instance.
• User administration – setup and maintenance.
• Authorization / Role / Profiles – setup and maintenance.
• Setup SAP security.
• Maintenance of system's health.
• Monitor system performance and logs.
• Spool and print administration.
• Maintain system landscape.

WHAT WE'RE LOOKING FOR

•  Bachelors or master’s in software engineering, Computer Science or other relevant disciplines
•  5+ years experience as a Back-End or Full Stack Developer with hands-on experience working with Python with  3+ years Preferably with AWS Services knowledge (Lambda, API Gateway, CloudWatch, Queues, Topics, etc)
•  Strong Knowledge in Python v3.x Language
•  Experience in REST APIs with JSON
•  Error handling and Logging 
•  Any DB knowledge 
•  Knowledge in Node.js is an added advantage
•  Knowledge in implementing Terraform is a plus
•  Knowledge on Sumo Logic log aggregation is a plus
• Must know how to produce high quality, “Clean” code that is performant, maintainable and secure

Requirements : 

a) CSS / Bootstrap : Flex Layout/ability to demonstrate the cascading nature of CSS clearly with example/Positioning.

b) Pure JavaScript: Prototype chain and inner workings of inheritance in JS. Understood DOM, Events, Event Bubbling, and Capturing/ ability to demonstrate it with example/ Promises and their use cases.

c) TypeScript: Basic understanding of using TS. Union Types, Index Signatures,

d) REST: Backend experience. REST principles, URL structures for APIs. integration using native JS (fetch and Promises) and in Angular. use cases of getting vs POST vs PUT vs PATCH.

e) Angular :  Abstractions of Angular Component, Service, Pipe, Directive, Module, Lifecycles. Knew advanced patterns as well Dynamic Components, Content Projection, Reactive Forms, ViewChild, ContentChild. Understood Observables and various operators demonstration of Design Skills ability to create the component and module hierarchy for a moderately complex application, along with their interactions