Ts 2 years experience data scientist Jobs – 132 Open Jobs Today

AI Infrastructure Architect
Accenture —Hyderabad, Telangana
- Full-time
- Computer Science
- DevOps
- Java
8d
AI Engineering Lead
Turing —Hyderabad, Telangana
- Azure
- Master's degree
- SQL
- Flexible schedule
ML Engineer(Databricks MLOps)
Anblicks —Hyderabad, Telangana
- Computer science
- Computer Science
- DevOps
Quick apply
Senior AI ML Engineer
Optum —Hyderabad, Telangana
- Full-time
- Doctoral degree
- Computer Science
- Writing skills
- Health insurance
Principal Azure Cloud Platform Engineer - Databricks & CI/CD Pipelines
サイネオス・ヘルス —Madhapur, Hyderabad, Telangana
- Azure
- SQL
- Leadership
Business Intelligence Engineer , Amazon Last Mile
ADCI - Karnataka —Hyderabad, Telangana
- Full-time
- Oracle
- Java
- Master's degree
Gen AI Architect
PepsiCo —Hyderabad, Telangana
- Remote
- Azure
- Computer Science
- Master's degree
LabVIEW Quality Engineer
Skyroot Aerospace —Hyderabad, Telangana
- Full-time
- Engineering
- C++
- Bachelor's degree
UX Quantitative Researcher, Google Ads
Google —Hyderabad, Telangana
- Full-time
- Doctoral degree
- Research
- Java
14h
Senior Manager, Machine Learning Engineering (Data & Audience Platform), Hyderabad
Warner Bros. Discovery —Hyderabad, Telangana
- Computer Science
- Master's degree
- SQL
Large Language Model Architect
Accenture —Hyderabad, Telangana
- Full-time
- Computer science
- Doctoral degree
- Computer Science
8d
Sr. Delivery Consultant-AI/ML, ProServe
AWS ProServe IN - Karnataka —Hyderabad, Telangana
- Full-time
- Computer Science
- SQL
- AWS
Senior Expert (Rapid Prototyping)
Novartis —Hyderabad, Telangana
- Full-time
- Research
- Machine learning
- APIs
Senior Software Engineer I - Full Stack/ Backend - AI Interfaces
Seismic —Hyderabad, Telangana
- Full-time
- Azure
- Computer Science
- Master's degree
Deputy Director - AI Solution and Platforms
PepsiCo —Hyderabad, Telangana
- Remote
- Azure
- Computer Science
- Salesforce
Senior Cloud AI Engineer - Ai Platform
Teradata —Hyderabad, Telangana
- Full-time
- Azure
- Computer Science
- DevOps
4d

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AI Infrastructure Architect

Accenture -
Hyderabad, Telangana

Apply Now

Job details

Full-time
8 days ago

Qualifications

BCS
CI/CD
Computer Science
Kubernetes
Full-stack development
Software deployment
Enterprise Software
DevOps
AWS Certification
Git
Java
Bash (Unix shell)
AWS
C++
Docker
C
Bachelor's degree
Machine learning
Terraform
Continuous integration
Computer Engineering
Scripting
Scalability
S3
AI
Communication skills
Python
PowerShell
AWS Certified DevOps Engineer – Professional
AWS Certified Developer – Associate
AWS Certified Solutions Architect – Professional
Identity & access management
Information Technology

Full job description

Project Role : AI Infrastructure Architect
Project Role Description : Architect and build custom Artificial Intelligence (AI) infrastructure/hardware solutions. Optimize AI infrastructure/hardware performance, power consumption, cost and scalability of computational stack. Advise on AI infrastructure technology and vendor evaluation, selection and full stack integration.
Must have skills : Machine Learning Operations
Good to have skills : Amazon Web Services (AWS)
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education

Role Summary / Description

AI Powered Tech Talent

As a hands-on Engineer in AI Infrastructure Architecture, you will design, build, automate, monitor and optimize AI/ML infrastructure on AWS for reliable, scalable and cost-effective model development and production workloads. you will work on moderately complex infrastructure components under guidance from senior architects and engineers, contributing to GPU/accelerated compute environments, model deployment pipelines, observability, security and operational reliability for AI-driven business solutions.

Key Responsibilities
Write, review and debug code, scripts and infrastructure-as-code for AWS AI infrastructure, automation, monitoring and deployment tooling.
Configure and provision AWS compute resources for AI/ML workloads, including GPU-enabled instances, Amazon EC2, Amazon EKS, Amazon SageMaker and supporting storage/networking services.
Support deployment automation and CI/CD pipelines for AI systems, models and applications using tools such as Git, Terraform/CloudFormation, Docker, Kubernetes and workflow orchestration tooling.
Deploy and operate AI services, model-serving components and data pipelines while applying reliability, security, cost-efficiency and scalability practices.
Monitor infrastructure and model-serving health using AWS CloudWatch and related observability tools troubleshoot issues across compute, storage, networking, containers and application layers.
Collaborate with data scientists, ML engineers, platform engineers and architects to integrate AI models into enterprise systems while meeting compliance and operational requirements.
Document reusable patterns, configuration standards and runbooks for AWS-based AI infrastructure.

Required Qualifications
Bachelor's degree in Computer Science, Computer Engineering, Information Technology or a related engineering field.
Minimum 2 years of experience coding, building, monitoring or troubleshooting AI/ML infrastructure, data platforms, model deployment pipelines or cloud/platform engineering solutions.
Strong understanding of AI/ML concepts and the compute, storage, networking, security and deployment foundations required to run AI workloads.
Minimum 2 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash or PowerShell.
Experience with CI/CD, infrastructure-as-code, containers, Kubernetes, workflow orchestration and operational monitoring tools.
Strong problem-solving ability, communication skills and collaboration mindset in a fast-paced engineering environment.

Required Skills/ Experience
Hands-on experience with AWS services relevant to AI infrastructure such as EC2, EKS, SageMaker, S3, IAM, VPC, CloudWatch and related DevOps services.
Experience designing or operating GPU/accelerated compute, distributed training setups, containerized deployments and model-serving workloads.
Working knowledge of Terraform or CloudFormation, Docker, Kubernetes, CI/CD pipelines and observability practices.
Ability to optimize infrastructure for performance, reliability, scalability, cost and security.
Understanding of MLOps patterns including experiment tracking, model registry, model deployment, monitoring and rollback approaches.

Good to Have Skills
AWS certification such as AWS Certified Solutions Architect, Developer, DevOps Engineer or Machine Learning specialty/associate level.
Exposure to industry use cases in BFSI, healthcare, retail/e-commerce, telecom, manufacturing or public sector where AI infrastructure must meet compliance, reliability and data-governance expectations.
Familiarity with large language model infrastructure, vector databases, retrieval pipelines, GPU scheduling or model optimization techniques.
Knowledge of security controls, FinOps practices, incident management and production support processes for enterprise AI platforms.

15 years full time education

Apply Now

Refine Your Search

2 years experience data scientist jobs in ts

AI Infrastructure Architect

AI Engineering Lead

ML Engineer(Databricks MLOps)

Senior AI ML Engineer

Principal Azure Cloud Platform Engineer - Databricks & CI/CD Pipelines

Business Intelligence Engineer , Amazon Last Mile

Gen AI Architect

LabVIEW Quality Engineer

UX Quantitative Researcher, Google Ads

Senior Manager, Machine Learning Engineering (Data & Audience Platform), Hyderabad

Large Language Model Architect

Sr. Delivery Consultant-AI/ML, ProServe

Senior Expert (Rapid Prototyping)

Senior Software Engineer I - Full Stack/ Backend - AI Interfaces

Deputy Director - AI Solution and Platforms

Senior Cloud AI Engineer - Ai Platform

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