418 AI Expert jobs in Chennai

Amazon is looking for an AI Content Expert II to help with annotations, content generation, and data analysis. As part of the Data Team, you will be responsible for delivering high-quality training data to improve and expand AGI's Large Language Models' (LLMs) capabilities.

Note: This is a Fixed Term Contractual Role

Key job responsibilities

As an AI Content Expert, you will be responsible for creating training data that are complex in nature and will require you to make informed and high judgement decisions in each case. You will be working closely with scientists and engineers to review and update guidelines, identify tooling improvement opportunities, and engage in conversations regarding the quality of data.

• Creating and annotating high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content
• Writing grammatically correct texts in different styles with various degrees of creativity, stricly adhering to provided guidelines
• Performing audits and quality checks of tasks completed by other specialists, if required
• Making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks
• Diving deep into issues and implementing solutions independently
• Identifying and reporting tooling bugs and suggesting improvements

A day in the life

We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data.

Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers' lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial.

• Bachelor's degree in a relevant field or equivalent professional experience
• 2+ yrs of experience working with written language data, including experience with annotation, and other forms of data markup.
• Strong research skills to gather relevant information, understand complex topics, and synthesize multiple resources; understanding of basic academic integrity, i.e. plagiarism.
• Excellent attention to details and ability to focus for a long period of time
• Ability to effectively write and evaluate diverse subject matter across various domains*
• Ability to adapt writing style to suit various style guidelines and customers.
• Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy

• Strong proficiency in English. Candidate must demonstrate excellent writing, reading, and comprehension skills (C1 level in the Common European Framework CEFR scale).
• Experience with creating complex data for LLM training and evaluation
• Strong understanding of U.S.-based culture, society, and norms.
• Comfortable with high-school level STEM*
• Familiarity with common markup languages such as HTML, XML, Markdown
• Familiarity with common standard text formats such as JSON, CSV, RTF
• Working knowledge of Python or another scripting language
• Familiarity with regular expressions syntax
• Familiarity with Large Language Models
• Comfort in annotation work that may include sensitive content

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

BASIC QUALIFICATIONS

PREFERRED QUALIFICATIONS

We are seeking an experienced and innovative AI Specialist to join our dynamic team. The ideal candidate will possess deep expertise in artificial intelligence, machine learning, and neural networks, with a proven track record of designing, developing, and deploying AI solutions. The candidate should be adept at analyzing large datasets, developing optimized algorithms, and integrating AI models into production environments.

This role offers the opportunity to contribute to cutting-edge AI applications that solve real-world problems and drive business value

Key Responsibilities:

AI System Design & Development:

Design, develop, and implement AI systems and applications, including machine learning models, neural networks, and natural language processing (NLP) algorithms.

Create and optimize AI algorithms for tasks such as image recognition, speech processing, and predictive analytics.

Data Analysis & Feature Engineering:

Analyze large datasets to identify trends, patterns, and actionable insights.

Perform data preprocessing, data wrangling, and feature engineering to enhance model performance.

Model Training & Optimization:

Train and fine-tune machine learning models using labeled and unlabeled data to improve model accuracy and efficiency.

Continuously monitor and optimize models for better performance.

AI Model Integration:

Deploy machine learning models into production environments, ensuring scalability and reliability.

Integrate AI technologies with existing software and business processes using REST APIs.

Utilize Docker and Kubernetes to containerize and manage AI models.

Research & Innovation:

Stay up to date with the latest advancements in AI and machine learning technologies.

Explore and experiment with new AI applications, tools, and methodologies to enhance system capabilities.

Collaboration & Agile Development:

Work closely with cross-functional teams in an Agile environment to develop AI-driven solutions that meet business requirements.

Communicate findings and results to stakeholders, ensuring AI solutions align with business goals.

Primary Skills and Qualifications:

AI and Machine Learning Expertise:

Strong knowledge of supervised and unsupervised learning techniques, including classification, regression, clustering, and reinforcement learning.

Hands-on experience developing and deploying machine learning models in production environments.

Technical Proficiency:

Programming Languages: Advanced proficiency in Python, with additional experience in R and SQL as a plus.

ML Libraries/Frameworks: Expertise in TensorFlow, PyTorch, and scikit-learn.

Cloud Platforms: Hands-on experience with AWS, Azure, or Google Cloud for model deployment and management.

Model Deployment & Integration: Familiarity with REST APIs, Docker, and Kubernetes for seamless model integration.

Secondary Skills and Preferred Qualifications:

Natural Language Processing (NLP):

Experience with NLP frameworks such as NLTK, spaCy, Hugging Face, and BERT.

Agile Methodologies:

Knowledge of Agile practices, with experience using tools like JIRA for project management.

Mathematics and Statistics:

Strong foundation in probability, statistics, and linear algebra to support model development and evaluation.

Data Handling & Preprocessing:

Proficiency in data cleaning, transformation, and feature engineering to prepare data for modeling.

Role & responsibilities

Impact Based Forecasting

• Collaborate with other members of the IT team, meteorologists, hydrologists, GIS specialists, and disaster risk management experts within RIMES to ensure the development of IBF DSS.
• Develop AI models (e.g., NLP, computer vision, reinforcement learning)
• Integrate models into applications and dashboards.
• Ensure model explainability and ethical compliance.
• Assist the RIMES Team in applying AI/ML models to forecast hazards and project likely impacts based on exposure and vulnerability indices.
• Work with forecasters and domain experts to automate the generation of impact-based products.
• Ensure data security, backup, and compliance with data governance and interoperability standards.
• Train national counterparts on the use and management of the AL, including analytics dashboards.
• Collaborate with GIS experts, hydromet agencies, and emergency response teams for integrated service delivery.
• Technical documentation on data architecture, models, and systems.

Capacity Building and Stakeholder Engagement

• Facilitate training programs for team members and stakeholders, focusing on RIMES policies, regulations, and the use of forecasting tools.
• Develop and implement a self-training plan to enhance personal expertise, obtaining a trainer certificate as required.
• Prepare and implement training programs to enhance team capacity and submit training outcome reports.

Reporting

• Prepare technical reports, progress updates, and outreach materials for stakeholders.
• Maintain comprehensive project documentation, including strategies, milestones, and outcomes.
• Capacity-building workshop materials and training reports.

Other Responsibilities

• Utilize AI skills to assist in system implementation plans and decision support system (DSS) development.
• Utilize skills to assist in system implementation plans and decision support system (DSS) development.
• Assist in 24/7 operational readiness for client early warning systems such as SOCs, with backup support from RIMES Headquarters.
• Undertake additional tasks as assigned by the immediate supervisor or HR manager based on recommendations from RIMES technical team members and organizational needs.
• The above responsibilities are illustrative and not exhaustive. Undertake any other relevant tasks that could be needed from time to time.

Preferred candidate profile

• Minimum of 3 years of experience in data engineering, analytics, or IT systems for disaster management, meteorology, or climate services.
• Experience in multi-stakeholder projects and facilitating capacity-building programs.
• Machine Learning Fundamentals: Deep understanding of various ML algorithms, including supervised, unsupervised, and reinforcement learning. This includes regression, classification, clustering, time series analysis, anomaly detection, etc.
• Deep Learning: Proficiency with deep learning architectures (e.g., CNNs, RNNs, LSTMs, Transformers) and frameworks (TensorFlow, PyTorch, Keras). Ability to design, train, and optimize complex neural networks.
• Strong programming skills in Python, with extensive libraries (NumPy, Pandas, SciPy, Scikit-learn, Matplotlib, Seaborn, GeoPandas).
• Familiarity with AI tools: such as PyTorch, TensorFlow, Keras, MLflow, etc.
• Data Visualization: Ability to create clear, compelling visualizations to communicate complex data and model outputs.
• Familiarity with early warning systems, disaster risk frameworks, and sector-specific IBF requirements is a strong plus.
• Proficiency in technical documentation and user training.

Contract Duration

The contract will initially be for one year and may be extended based on the satisfactory completion of a 180-day probationary period and subsequent annual performance reviews.

How to Apply:

Interested candidates should send your application letter, resume, salary expectation and 2 references to rimeshra- by midnight of 1 October 2025, Bangkok time.

Please state AI SpecialistImpact-Based Forecasting: Your Name the Subject line of the email. Only short-listed applicants will be contacted.

Ms. Dusadee Padungkul

Head-Department of Operational Support

Regional Integrated Multi-Hazard Early Warning System

AIT Campus, 58 Moo 9 Paholyothin Rd., Klong 1,

Klong Luang, Pathumthani 12120 Thailand.

RIMES promotes diversity and inclusion in the workplace. Well-qualified applicants particularly women are encouraged to apply.

Roles and Responsibilities

Design, test, and refine prompts to optimize LLM performance across diverse tasks and domains.

Build and maintain a library of prompt templates and reusable components.

Collaborate with engineers, analysts, and business teams to embed prompt engineering into broader AI workflows.

Analyse model outputs and user feedback to iteratively improve prompt accuracy, consistency, and relevance.

Monitor developments in the fields of prompt engineering, generative AI, and LLM capabilities to inform internal practices.

Contribute to documentation, internal guidelines, and knowledge-sharing initiatives related to prompt engineering.

Required Background

Demonstrable experience with prompt writing and LLM fine-tuning.

Skilled in writing effective test cases for validation and performance checks.

Basic data analysis capabilities, with proficiency in tools such as SQL and Excel.

Strong problem-solving skills with a keen eye for detail.

Excellent communication and collaboration skills, with the ability to work across cross-functional teams.

Quick learner with a proactive mindset and an interest in emerging AI technologies.

Ideal Background

Design and deliver LLM-powered features with robust LLMOps. Choose models (OpenAI, Google, Anthropic, open-source), build RAG pipelines with vector stores, implement evaluation harnesses, guardrails, and safety checks. Optimise prompts, latency, cost, and quality; deploy services (vLLM/Ray Serve) and track telemetry.

prompt design, and practical GenAI applications. You'll play a key role in optimizing how large language models (LLMs) are used across various workflows, helping drive innovation and performance through effective prompt engineering.

Generative AI: advanced expertise working with: LLMs/transformer models, AWS Bedrock, SageMaker, LangChain

LLM Ops: putting models into production in the AWS ecosystem

Experience productionizing ML/Gen AI services and working with complex datasets.

Srong understanding of software development, algorithms, optimization, and scaling.

Excellent communication and business analysis skills.

Cloud engineering experience (AWS cloud services)

Snowflake

Software development experience to consolidating all information from thousands of tables. We want to explore using GNAI (Generative Natural Language AI) to accelerate this process, as the current manual approach is very laborious. The desired outcome is to have a senior -level resource who can deliver a proof of concept within 8-10 weeks in parttime as well.

Prompt engineering & prompt templates

RAG architecture (chunking, retrieval, ranking)

Evaluation (groundedness, factuality) & guardrails

Serving & scaling (vLLM/Ray), latency/cost tuning

Data governance, privacy, and security

Education-Bachelors/Masters in CS/AI/Statistics or equivalent.

Role

• The Generative AI specialist should be building GenAI LLM model driven solution using State of the Art Models like ( OpenAI, Gemini, Claude) , Opensource Models ( llama, Mistral).
• Should have expertise in fine tuning and training models .
• Should have implemented projects with expertise on Agents, Tools and RAG solutions.
• Hands on expertise in integrating LLMs with VectorDB like chromadb, faiss, pinecone is required.
• Expertise in PEFT, Quantization of models is required.
• Experience in Tensorflow, Pytorch, Python, Hugging Face, Transformers is must.
• Expert in data preparation, analysis and hands one expertise in Deep Learning model development is preferred.
• Additional expertise in deploying models in AWS is desired but optional.

Skills - OpenAI, Gemini, LangChain, Transformers, Hugging Face, Python, Pytorch, Tensorflow, Vectordb( chromadb, faiss, pinecone)

• Project experience - Atleast 1-2 live implementation of Generative AI driven solution implementation.
• Extensive experience in implementing chatbots, knowledge search and in NLP .
• Good expertise in implementing Machine learning and deep learning solutions for atleast 2 years.

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BASIC QUALIFICATIONS

PREFERRED QUALIFICATIONS