8,275 AI Powered Robots jobs in India

Key Responsibilities

• Design, develop, and deploy scalable machine learning models for classification, regression, NLP, and generative AI tasks.
• Build and optimize data transformation workflows using Python, Pandas, and related libraries.
• Lead AI/ML pipelines from data ingestion to model deployment, monitoring, and retraining.
• Implement model observability and monitoring for drift detection and continuous evaluation.
• Develop and deploy REST APIs to integrate ML models with production systems using frameworks like FastAPI.
• Ensure high code quality through unit/integration testing and code reviews.
• Collaborate with cross-functional teams including Data Engineers, DevOps, and Product Managers.
• Stay updated with the latest advancements in AI, ML, and GenAI frameworks and tools.
• Apply DevOps/MLOps practices to automate and manage the full ML lifecycle.

Required Skills
Programming & Python Ecosystem :

• Advanced proficiency in Python with expertise in Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
• Strong understanding of asynchronous programming, concurrency, and FastAPI (Starlette).
• In-depth knowledge of multithreading, multiprocessing, and Python GIL.
• Ability to write clean, efficient, and testable code.

Machine Learning & Deep Learning

• Strong grasp of traditional ML concepts : classification, regression, regularization (L1/L2), overfitting/underfitting, multicollinearity.
• Experience with deep learning architectures : RNNs, attention mechanisms, dropout, early stopping, GANs, diffusion models.
• Knowledge of transfer learning and pre-trained model fine-tuning.

MLOps

• Hands-on experience in ML pipeline design including training, deployment, and monitoring.
• Proficiency in data drift and concept drift detection and mitigation.
• Familiarity with model observability tools, unstructured data drift monitoring, and automated drift alerts.

Software Engineering & DevOps

• Strong expertise in REST API development, CI/CD pipelines, and integration testing.
• Experience with Docker and containerized deployments.
• Familiarity with cloud-based ML deployment (AWS, Azure) and logging/monitoring frameworks.

Data Engineering & Problem Solving

• Strong experience with data wrangling, transformation, joins, ranking, filtering, and preprocessing using Python/Pandas.
• Ability to handle large datasets and build efficient preprocessing workflows.

Nice-to-Have

• Experience in Generative AI and working with LLMs.
• Exposure to MLOps tools like MLflow, Kubeflow, or Airflow.
• Knowledge of transformer-based models, embeddings, and NLP pipelines.
• Prior contributions to open-source ML frameworks or GitHub repositories.

Core Skills & Proficiency

• Python
• NumPy
• PyTorch
• Machine Learning
• Deep Learning
• REST API Development
• Agile Software Development
• API Development
• Generative AI
• Artificial Intelligence

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Develop machine learning models and algorithms using Python and relevant libraries (e.g., Tensor Flow, PyTorch, sci-kit-learn).

• Experience in Gen AI and Proficiency in could technologies such as AWS, GCP or azure.
• Collaborate with data engineers to design and implement data pipelines for efficient data processing, analysis, and model training.
• Apply machine learning techniques to solve complex business problems and optimize existing processes.
• Evaluate and benchmark different machine learning models to determine optimal solutions.
• Work closely with product managers and stakeholders to understand business requirements and translate them into technical solutions.
• Implement scalable and reliable machine learning infrastructure and productionize models.
• Stay updated with the latest developments in AI/ML research and apply them to improve our systems continuously.
• Participate in code reviews, knowledge sharing, and contribute to the overall growth of the AI/ML team

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Job Description : AI Engineer
Overview
We are looking for a highly skilled and experienced AI/ML to join our dynamic team. The ideal candidate will have a robust background in developing web applications using Django and Flask, with expertise in deploying and managing applications on AWS. Proficiency in Django Rest Framework (DRF), a solid understanding of machine learning concepts, and hands-on experience with tools like PyTorch, TensorFlow, and transformer architectures are essential.

Key Responsibilities

• Develop and maintain web applications using Django and Flask frameworks.
• Design and implement RESTful APIs using Django Rest Framework (DRF).
• Deploy, manage, and optimize applications on AWS services, including EC2, S3, RDS, Lambda, and CloudFormation.
• Build and integrate APIs for AI/ML models into existing systems.
• Create scalable machine learning models using frameworks like PyTorch, TensorFlow, and scikit-learn.
• Implement transformer architectures (e.g., BERT, GPT) for NLP and other advanced AI use cases.
• Optimize machine learning models through advanced techniques such as hyperparameter tuning, pruning, and quantization.
• Deploy and manage machine learning models in production environments using tools like TensorFlow Serving, TorchServe, and AWS SageMaker.
• Ensure the scalability, performance, and reliability of applications and deployed models.
• Collaborate with cross-functional teams to analyze requirements and deliver effective technical solutions.
• Write clean, maintainable, and efficient code following best practices.
• Conduct code reviews and provide constructive feedback to peers.
• Stay up-to-date with the latest industry trends and technologies, particularly in AI/ML.

Required Skills And Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proficient in Python with a strong understanding of its ecosystem.
• Extensive experience with Django and Flask frameworks.
• Hands-on experience with AWS services for application deployment and management.
• Strong knowledge of Django Rest Framework (DRF) for building APIs.
• Expertise in machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Experience with transformer architectures for NLP and advanced AI solutions.
• Solid understanding of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB).
• Familiarity with MLOps practices for managing the machine learning lifecycle.
• Basic knowledge of front-end technologies (e.g., JavaScript, HTML, CSS) is a plus.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.

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Job Title :
AI/ML Engineer

Experience :
35 Years

Location :
Remote / Hybrid (Flexible)

Employment Type :
the Role :

We are looking for a highly skilled AI/ML Engineer to join our team and work on building intelligent, data-driven applications. The ideal candidate will have solid experience in developing, deploying, and optimizing machine learning models, along with a strong foundation in Python programming, data preprocessing, and model evaluation.

Responsibilities
You will work closely with data scientists, backend engineers, and product managers to design scalable machine learning pipelines, integrate AI models into production systems, and leverage modern AI frameworks and cloud platforms. This role requires a mix of research capability, engineering skills, and problem-solving ability to turn complex data into actionable insights and Responsibilities :

• Design, develop, and deploy machine learning and deep learning models for various use cases.
• Build and maintain data pipelines for data ingestion, cleaning, transformation, and feature engineering.
• Collaborate with data scientists to transition models from research to production.
• Implement model training, validation, and hyperparameter tuning workflows.
• Integrate AI models into backend systems and APIs.
• Monitor, maintain, and improve model performance in production.
• Work with large datasets using tools such as Pandas, NumPy, and Spark.
• Apply MLOps best practices, including model versioning, automated deployment, and monitoring.
• Stay updated with advancements in AI/ML research, frameworks, and cloud AI Skills & Experience :
• 35 years of experience in AI/ML engineering or applied machine learning.
• Strong programming skills in Python (experience with NumPy, Pandas, Scikit-learn).
• Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Experience with data preprocessing and feature engineering for structured and unstructured data.
• Proficiency in developing, training, and deploying ML models in production environments.
• Knowledge of machine learning algorithms, model evaluation metrics, and optimization techniques.
• Familiarity with MLOps tools and practices (MLflow, Kubeflow, or similar).
• Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services.
• Strong problem-solving skills and the ability to work in a collaborative, agile to Have :
• Experience with natural language processing (NLP) using Hugging Face Transformers, SpaCy, or NLTK.
• Exposure to computer vision frameworks like OpenCV or Detectron2.
• Familiarity with big data tools (Apache Spark, Hadoop).
• Knowledge of containerization (Docker, Kubernetes).
• Understanding of data versioning (DVC) and experiment Join Us ?
• Flexible Remote / Hybrid work arrangement.
• Competitive salary and performance-based incentives.
• Opportunity to work on cutting-edge AI/ML projects.
• Access to continuous learning resources and training programs.
• Collaborative and innovation-driven work culture.

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develop and manage applications involved with Search Systems. Maintain and upgrade search indices for large document repositories, as well as optimizing indexing/queries and supporting analytics

Analyze website metrics and customer behaviour data

AI/ML Lead Lending Automation & GenAI Orchestration

Role Type : Full-time | Hands-On AI/ML Leadership

Work Location : Hyderabad

Role Overview :

We are seeking a hands-on AI/ML Lead who will design, develop, and deploy AI-driven lending automation solutions with a focus on NLP workflows, GenAI orchestration, and valuation process automation. This is a 50% coding and delivery role, 50% architecture and leadership role. You will work directly with our Engineering Lead, Data Engineering Team, Product Managers, and UK-based stakeholders to define, architect, and integrate AI capabilities seamlessly into our + React enterprise platform.

Key Responsibilities :

AI Solution Architecture & Development :

• Architect and implement end-to-end AI/ML features aligned with lending workflows :

• NLP Document Parsing OCR, entity extraction, semantic search, summarization, classification.

• Valuation Automation Predictive modeling for asset and loan valuations.

• GenAI Orchestration Multi-step, multi-service automation workflows.

• Develop production-grade AI services in Python, integrating with REST/GraphQL APIs, microservices, and event-driven architectures.

• Integrate GenAI APIs (OpenAI GPT, Anthropic Claude, AWS Comprehend, Google Vertex AI, etc.) into existing systems.

Model Lifecycle Management :

• Select, train, fine-tune, and deploy models (LLMs, transformer-based models, classical ML).

• Implement model monitoring pipelines for accuracy, drift detection, bias evaluation, and retraining triggers.

• Optimize inference latency, throughput, and scalability for production workloads.

Data Readiness & Governance :

• Collaborate with Data Engineering to ensure AI-ready data pipelines (schema design, storage format, vectorization strategies).

• Establish data labeling, augmentation, and versioning processes for supervised and semi-supervised learning.

• Ensure compliance with data privacy regulations (GDPR, RBI guidelines) and ethical AI principles.

AI Workflow Orchestration :

• Design and implement multi-step AI orchestration layers combining LLM prompts, RAG (Retrieval-Augmented Generation), and business rules.

• Build custom prompt chains and tools to handle complex workflows like Credit Committee Pack creation and communication parsing.

Stakeholder Collaboration & Leadership :

• Translate complex AI concepts into clear business benefits for non-technical stakeholders.

• Mentor and guide developers on AI integration best practices.

• Track AI feature KPIs and demonstrate measurable business impact.

Required Skills & Experience :

• Total Experience : years in software engineering, with 3+ years hands-on AI/ML solution delivery.

• Proven record of deploying AI/NLP features in production environments.

• Proficiency in Python (FastAPI, Flask, LangChain, Hugging Face Transformers, PyTorch/TensorFlow).

• Strong experience with NLP pipelines tokenization, embeddings, semantic search, summarization, classification, sentiment analysis.

• Expertise in AI orchestration frameworks (LangChain, Haystack, LlamaIndex) and workflow automation.

• Proficient in REST API design, microservices, and integrating AI with JavaScript/TypeScript-based backends.

• Deep understanding of data structures, feature engineering, and vector databases (Pinecone, Weaviate, FAISS).

• Solid grasp of MLOps tools (MLflow, Kubeflow, AWS SageMaker, Azure ML).

• Familiarity with cloud-native AI deployments (AWS, Azure, GCP).

• Strong communication skills for technical-to-business translation.

Bonus Skills :

• Fintech or lending automation platform experience.

• Familiarity with financial document workflows (KYC, underwriting, valuation reports).

• Hands-on experience with RAG pipelines, prompt engineering, and custom LLM training.

Key Responsibilities

• Design, develop, and deploy AI/ML models for real-world applications.
• Implement Generative AI solutions using platforms like OpenAI, Anthropic Claude, and HuggingFace Transformers.
• Work on LLM fine-tuning using PEFT, LoRA, QLoRA, and similar parameter-efficient methods.
• Develop intelligent agents using LangChain and LangGraph frameworks.
• Build and optimize RAG pipelines integrated with vector databases like Pinecone, Weaviate, etc.
• Apply prompt engineering techniques to improve model performance and outputs.
• Collaborate cross-functionally with product, data, and engineering teams to deliver scalable AI systems.
• Work with cloud infrastructure, especially AWS, for model training, deployment, and orchestration.
• Stay up to date with the latest research and trends in AI, LLMs, and agent-based systems.
• Implement and maintain MCP Protocols and agentic workflows for advanced decision-making Skills & Experience :
• 46 years of strong experience in Machine Learning, Deep Learning or Generative AI and Agentic AI.
• Hands-on experience with Generative AI, LLM architectures, and open-source models like Mistral, Meta LLaMA, etc.
• Proficiency in LangChain, LangGraph, and prompt engineering.
• Familiarity with Vector Databases such as Pinecone, Weaviate, FAISS, etc.
• Experience with OpenAI, HuggingFace, Anthropic Claude, and model APIs.
• In-depth understanding of LLM fine-tuning techniques (LoRA, QLoRA, PEFT).
• Strong Python programming skills and experience with ML frameworks (PyTorch, TensorFlow).
• Good understanding of AWS services for model training, hosting, and storage.
• Solid understanding of RAG pipelines, agentic AI frameworks, and MCP Protocols.
• Experience working in a fast-paced, research-driven environment.

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Job Description : AI/ML Specialist
We are looking for a highly skilled and experienced AI/ML Specialist to join our dynamic team.

The ideal candidate will have a robust background in developing web applications using Django and Flask, with expertise in deploying and managing applications on AWS.

Proficiency in Django Rest Framework (DRF), a solid understanding of machine learning concepts, and hands-on experience with tools like PyTorch, TensorFlow, and transformer architectures are essential.

Key Responsibilities

• Develop and maintain web applications using Django and Flask frameworks.
• Design and implement RESTful APIs using Django Rest Framework (DRF).
• Deploy, manage, and optimize applications on AWS services, including EC2, S3, RDS, Lambda, and CloudFormation.
• Build and integrate APIs for AI/ML models into existing systems.
• Create scalable machine learning models using frameworks like PyTorch, TensorFlow, and scikit-learn.
• Implement transformer architectures (e.g., BERT, GPT) for NLP and other advanced AI use cases.
• Optimize machine learning models through advanced techniques such as hyperparameter tuning, pruning, and quantization.
• Deploy and manage machine learning models in production environments using tools like TensorFlow Serving, TorchServe, and AWS SageMaker.
• Ensure the scalability, performance, and reliability of applications and deployed models.
• Collaborate with cross-functional teams to analyze requirements and deliver effective technical solutions.
• Write clean, maintainable, and efficient code following best practices.
• Conduct code reviews and provide constructive feedback to peers.
• Stay up-to-date with the latest industry trends and technologies, particularly in AI/ML.

Required Skills And Qualifications

• Bachelors degree in Computer Science, Engineering, or a related field.
• 3+ years of professional experience as a AI/ML Specialist.
• Proficient in Python with a strong understanding of its ecosystem.
• Extensive experience with Django and Flask frameworks.
• Hands-on experience with AWS services for application deployment and management.
• Strong knowledge of Django Rest Framework (DRF) for building APIs.
• Expertise in machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Experience with transformer architectures for NLP and advanced AI solutions.
• Solid understanding of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB).
• Familiarity with MLOps practices for managing the machine learning lifecycle.
• Basic knowledge of front-end technologies (e.g., JavaScript, HTML, CSS) is a plus.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.

Skills

• Artificial Intelligence (AI), pandas, Natural Language Processing (NLP), NumPy, Machine Learning (ML), TensorFlow, PyTorch and Python.

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