Top Artificial Intelligence Jobs in Chennai

Build and refine AI-powered prototypes for supply chain and manufacturing operations. Engage with factory and warehouse teams, translate operational needs into software requirements, develop Python-based RAG and agentic systems, integrate APIs and data sources, and iterate prototypes based on frontline feedback. The role involves SQL and document data preparation, agile collaboration, occasional manufacturing-site travel, and progressive adoption of enterprise AI frameworks and production engineering practices.

Design, build, and scale production AI agents across EveryWatch. Own the agent roadmap, architecture, shared tools, memory, state, observability, evaluation, and cost controls. Harden WatchChat, develop RAG and tool-calling systems, establish measurable quality standards, and ship solutions directly in Python. Collaborate with sales, product, data, and engineering teams to identify high-impact use cases and take agent concepts from discovery through production.

Join Welo Data’s Canadian French contributor network for potential remote AI projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and details provided before each assignment.

Join Welo Data’s French AI Trainers Network as a flexible contributor supporting annotation, evaluation, and prompt creation projects. Contributors may label text, images, or audio; assess search results, advertisements, and chatbot responses; create prompts for large language models; and ensure cultural and linguistic accuracy. This is a talent community rather than an active opening, with project details and compensation provided when assignments become available.

Designs and operationalizes enterprise analytics, KPI frameworks, data validation pipelines, machine learning solutions, and governed GenAI capabilities. Builds advanced SQL and Python data transformations, RAG and agentic AI workflows, evaluation frameworks, and production-ready deliverables. Applies anomaly detection, forecasting, and other advanced analytics techniques while implementing testing, logging, guardrails, deployment packaging, documentation, and security controls.

Build scalable Java full-stack applications, including Spring Boot microservices, REST APIs, event-driven integrations, and responsive React interfaces. Develop secure, tested, high-performance software while collaborating in Agile teams, participating in code reviews, and working with Product Owners and QA. Integrate AI/ML services and features into applications to support automation and decision-making. Preferred experience includes cloud deployment, CI/CD, Docker, Kubernetes, and modern AI platforms or LLM integrations.

Lead the end-to-end product experience across acquisition, onboarding, avatar selection, chat, media generation, and retention. Drive conversion, retention, and LTV through hypotheses, prioritization, A/B testing, and data-informed design. Establish the product’s design direction and design system, lead a multidisciplinary design team, and partner with product, analytics, marketing, engineering, research, and support.

Build and operate the infrastructure, frameworks, SDKs, runtime systems, and tooling for an AI agent platform supporting ERP product teams. Develop frontend and backend systems, APIs, microservices, distributed services, cloud infrastructure, and production LLM integrations. Translate product requirements into technical solutions, ensure reliability and developer experience, contribute to architecture decisions, and mentor engineers.

The role involves providing legal guidance on global privacy and AI issues, collaborating with teams to ensure compliance, and developing scalable processes.

Build and own production-grade AI systems, including backend services, scalable APIs, LLM integrations, RAG pipelines, and agentic workflows. Responsibilities include testing, documentation, model deployment, performance optimization, collaboration, and continuous learning, with increasing ownership and complexity based on experience.

Architect scalable, low-latency AI/ML systems and real-time inference pipelines for voice, vision, and NLP applications. Lead model productionization, infrastructure and framework selection, architecture reviews, optimization, observability, and MLOps best practices. Collaborate with product, data science, and engineering teams while mentoring engineers. The role requires expertise in distributed systems, LLM inference optimization, vector databases, RAG, containerization, cloud platforms, CI/CD, edge deployment, and software architecture.

Owns technical direction for enterprise agentic AI solutions across application, cloud, data, and AI layers. Leads architecture decisions, deployment standards, security reviews, reusable infrastructure, CI/CD practices, and production monitoring. Mentors Forward Deployed Engineers toward independent delivery, guides design and code reviews, prototypes high-risk components, and resolves critical blockers. The role emphasizes technical leadership, scalable deployment capability, cloud cost discipline, agent evaluation, guardrails, and operational reliability rather than sustained feature development.

Own the technical delivery of AI solutions from stakeholder engagement and conceptualization through proof of concept, productionization, and maturity. Design multi-agent, generative AI, RAG, and fine-tuned LLM solutions; develop evaluation and AgentOps practices; and apply NLP, computer vision, and predictive models. Support pre-sales, create technical artifacts, guide engineering teams, and deploy scalable solutions using microservices, containers, Kubernetes, AWS, and Azure.

Leads the development and maintenance of scalable test automation frameworks using Playwright and Selenium. Develops Java and Python automation scripts, integrates test suites with Azure DevOps and Jenkins pipelines, and implements AI-assisted capabilities such as script generation, self-healing, intelligent test data, and failure analysis. Mentors automation engineers, conducts code reviews, collaborates in Agile teams, and promotes quality engineering best practices.

Develop and optimize AI and generative AI applications using Python, large language models, machine learning, NLP, TensorFlow, and PyTorch. Build APIs, backend services, semantic search systems, and vector database integrations. Fine-tune models, monitor production performance, and collaborate with data scientists, engineers, and product teams to deliver scalable AI features. Document models and workflows while applying prompt engineering, embeddings, and MLOps practices.

Leads the design, development, deployment, and operation of enterprise-scale AI, machine learning, NLP, GenAI, and agentic AI solutions. Builds scalable Python pipelines on Databricks and Azure, develops distributed ML applications, and implements MLOps, LLMOps, CI/CD, and responsible AI practices. Collaborates with technical and business teams to deliver actionable intelligence, establishes AI strategies and roadmaps, mentors junior engineers, and supports team scaling.

Build and scale production machine learning systems for ecommerce search, retrieval, ranking, recommendations, personalization, and GenAI experiences. Responsibilities include developing ML models, optimizing multi-stage ranking pipelines, running offline and A/B experiments, applying reinforcement learning and bandits, deploying Databricks pipelines through AKS, designing scalable ML infrastructure, and monitoring models using MLOps and LLMOps practices.

Designs, develops, evaluates, and deploys enterprise-scale AI, machine learning, NLP, generative AI, and agentic solutions for e-commerce. Builds scalable Python pipelines on Databricks and Azure, develops distributed streaming ML applications, and drives software delivery through DevOps, MLOps, and LLMOps practices. Collaborates cross-functionally to translate business needs into reliable AI products while implementing responsible AI, explainability, fairness, human validation, compliance, and governance.

Designs and scales AI/ML platforms for pricing, promotion optimization, and demand forecasting across B2C and B2B channels. Develops time-series, causal inference, reinforcement learning, recommendation, and price elasticity models. Builds end-to-end ML pipelines, production API integrations, monitoring, retraining, and drift detection. Collaborates with data engineering, product, marketing analytics, cloud, and business teams to optimize revenue, profitability, promotions, competitive pricing, and customer-segment decisions.

Contribute to AI data projects through language data annotation, evaluation, and instruction creation. Work remotely with flexible hours to help develop more inclusive and capable AI systems. Applicants must be native or near-native Simplified Chinese speakers living in China, Canada, the United States, or Malaysia, with fluent English, comfort using digital tools, strong attention to detail, and curiosity.

Join Welo Data’s remote contributor network for future AI data projects involving text, image, or audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural or linguistic accuracy review. Contributors must have native or near-native Twi 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 a remote Albanian-language AI contributor network supporting flexible annotation, evaluation, and prompt-creation projects. Work may include labeling text, images, or audio; assessing search results, advertisements, and chatbot responses; creating prompts for large language models; and ensuring cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Freelance remote contributors support AI language-data projects through annotation, evaluation, prompt creation, and Korean-to-Chinese machine-transliterated lyric review. Responsibilities include assessing meaning, fluency, naturalness, and accuracy; rating quality against defined criteria; correcting errors; and providing feedback to improve AI systems. Projects are task-based, flexible, and dependent on availability.

Join Welo Data’s global contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and review cultural and linguistic accuracy. Native or near-native Javanese fluency, English proficiency, digital tool familiarity, and attention to detail are required. This is a talent community rather than an active job opening.

Join Welo Data’s Dutch talent network for potential flexible, remote AI-data projects. 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. Native or near-native Dutch, English proficiency, digital-tool comfort, and attention to detail are required.