Top Artificial Intelligence Jobs in Chennai

Join a Lithuanian-language AI contributor network for flexible remote projects involving text, image, and audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment.

Join Welo Data’s Danish AI contributor network for potential remote projects involving data annotation, content evaluation, search and chatbot quality assessment, prompt creation, and cultural or linguistic accuracy. Projects vary in length and scope, with compensation and details provided before each assignment. Candidates must have native or near-native Danish fluency, English proficiency, digital tool comfort, and strong attention to detail.

Join Welo Data’s Bengali contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertisement, and chatbot evaluation; prompt creation and testing; and cultural or linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each project.

Join Welo Data’s global contributor network for flexible, remote AI projects involving text, image, and audio annotation; search, advertisement, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. Native or near-native Hebrew, English proficiency, digital tool comfort, and strong attention to detail are required.

Join Welo Data’s Cantonese AI Trainers Network to support AI data annotation, evaluation, and prompt creation. Work remotely with flexible hours while contributing language and cultural expertise to improve AI systems. Applicants should be native or near-native Cantonese speakers living in Hong Kong, Macau, mainland China, or Malaysia, with strong English skills, digital tool proficiency, attention to detail, and curiosity.

Join Welo Data’s Nepali contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create prompts for large language models; and review cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s contributor network for flexible, remote AI projects involving text, image, or audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic accuracy review. Candidates need native or near-native Kannada fluency, English proficiency, digital tool comfort, and strong attention to detail. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s Vietnamese AI contributor network for potential remote projects involving text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Projects vary in duration and compensation, with details provided before participation.

Join a remote global contributor network supporting AI data projects. Depending on project needs, you may annotate content, evaluate search results or chatbot responses, create prompts, and verify cultural and linguistic accuracy. Projects range from a few days to several weeks, with scope, timelines, and compensation provided before participation.

Architect and improve autonomous AI optimization algorithms for a marketing platform. Analyze A/B tests, integrate AI models, develop multi-touch attribution, expand advertising-channel capabilities, reduce inference costs and latency, incorporate customer feedback, and maintain reliable, continuously improving optimization loops.

The Senior Engineer will develop and expand the AI Studio Platform, design innovative prototypes, collaborate on cloud-native solutions, and research emerging technologies in AI and automation to enhance business outcomes for Presidio's clients.

Leads the architecture, development, deployment, and operation of scalable AI infrastructure, distributed systems, real-time data platforms, microservices, and agentic AI solutions. Defines technical vision, builds resilient and observable production services, processes high-volume network data, mentors engineers, and drives engineering excellence across intelligent networking and automation platforms.

Design, develop, deploy, and scale enterprise AI and machine learning solutions, including predictive models, recommendation engines, automation, and model-serving APIs. Build data pipelines and MLOps workflows, monitor model performance and drift, troubleshoot production systems, and implement responsible AI practices. Collaborate with technical and business stakeholders, contribute to architecture and code reviews, and mentor junior engineers while applying cloud-native technologies.

Develop, deploy, and scale end-to-end analytical solutions for the Vapor Phase Drying process. Build ML models and data pipelines, work with dashboards and model monitoring, use Python and ML libraries, leverage Azure data and ML services, apply time-series forecasting, collaborate cross-functionally, and ensure regulatory and internal compliance.

Lead the development of AI-powered customer support solutions, guiding a team to build scalable, reliable, and secure systems using LLMs and third-party integrations.

Own the architecture and delivery of production-grade generative and agentic AI systems, including LLM agents, RAG pipelines, multi-agent workflows, APIs, and cloud-native services. Establish AI engineering, evaluation, observability, guardrail, and LLMOps practices while mentoring AI/ML and backend engineers. Collaborate with Product, Data, Platform, Security, and Compliance teams to deliver scalable, secure, and business-ready solutions, and provide technical direction on GenAI strategy and architecture.

Leads the identification, development, testing, and scaling of AI and automation solutions across internal delivery processes and future customer-facing use cases. Builds automated test suites, scripts repetitive workflows, pilots generative AI and agentic tools, creates reusable automation assets, tracks measurable value, and enables teams through training and knowledge sharing. Collaborates with project managers, product owners, process owners, testing communities, and delivery teams to ensure maintainable, responsible, and broadly adopted solutions.

Leads customer-facing design and implementation of cloud, platform, infrastructure, data, and AI solutions. Responsibilities include cloud migration and modernization, Infrastructure as Code, CI/CD, Kubernetes, automation, GitOps, platform security, observability, and AI-assisted development. The consultant conducts workshops, creates reusable platform capabilities, enables responsible AI adoption, mentors engineers, supports proposals and pre-sales, and ensures secure, reliable, governed, and cost-effective production solutions.

Design, develop, train, deploy, and maintain production-grade AI/ML solutions. Build predictive, classification, recommendation, and automation systems; prepare and feature-engineer data; create scalable model-serving APIs; deploy with containers and CI/CD; monitor model performance and drift; apply Responsible AI principles; collaborate with product, engineering, and stakeholders in Agile delivery.

Lead design, development, and deployment of production-grade LLM and RAG-based AI solutions. Improve retrieval performance, build automated evaluation and validation frameworks, instrument pgvector retrieval KPIs, integrate metrics into CI/CD, and mentor mid-level engineers while driving technical reviews and best practices.

Lead and align Engineering, ML, and Analytics to deliver scalable, reliable production AI and data systems. Own technical direction, architecture, MLOps, and platform reliability while partnering with Product, Sales, and Customers to ensure engineering work maps to measurable business outcomes.

Hands-on pre-sales technical lead who designs AI/data solution architectures, builds POCs and reusable assets, authors RFP responses, and transitions solutions to delivery across cloud data platforms, ETL/ELT, and applied ML to drive client outcomes.

Build and deploy production-grade generative AI applications: design multi-agent systems and LangGraph workflows, implement advanced RAG with vector DBs, fine-tune and host LLMs, develop scalable FastAPI backends, optimize latency/cost, and containerize services for production.

Design, develop, and deploy machine learning and deep learning models; build end-to-end ML pipelines including preprocessing, training, evaluation, and deployment; perform feature engineering on large datasets; deploy and monitor models on cloud platforms; collaborate with cross-functional teams to integrate AI solutions and retrain models as needed.

Design, build, and scale production Generative AI systems: multi-agent workflows, advanced RAG pipelines, model fine-tuning and quantization, LLM integration and swapping, high-performance FastAPI backends, vector search and retrieval, containerized deployment, and monitoring for latency, cost, and reliability.