11,896 AI Powered Applications jobs in India

Join Proximity Works, one of the world’s most ambitious AI technology companies, shaping the future of Sports, Media, and Entertainment. Since 2019, Proximity Works has created and scaled AI-driven products used by 697 million daily users, generating $73.5 billion in enterprise value for our partners. Headquartered in San Francisco with offices in Los Angeles, Dubai, Mumbai, and Bangalore, we help global brands discover high-impact AI use cases, build transformative tech stacks, and scale to hundreds of millions of users.

If you’re excited about building high-performance backend systems at the frontier of AI, this role will give you the opportunity to make global impact.

Role Summary

We are seeking a Backend Engineer to design, build, and scale resilient microservices and APIs that power next-generation AI products. You will partner closely with ML engineers and data scientists to productionize LLMs, RAG pipelines, and multimodal models, ensuring inference is fast, cost-efficient, and production-grade. This is a hands-on role for someone passionate about distributed systems, performance optimization, and bringing cutting-edge AI to millions of users.

• Design and build scalable microservices that power Proximity’s AI-driven search and discovery stack.
• Develop backend services and APIs to support LLM-powered applications.
  Collaborate with ML engineers and data scientists to integrate RAG pipelines, multimodal models, and inference workloads into production.
• Optimize inference pipelines for latency, throughput, and cost efficiency (e.g., batching, caching, token budgeting).
• Own end-to-end delivery of complex backend projects, from design to deployment and monitoring.
• Write high-quality, maintainable code with rigorous testing and fault-tolerant practices.
• Drive operational excellence through performance tuning, incident response, and root cause analysis.
• Work cross-functionally with Product Managers, Data Scientists, and global engineering teams to translate business needs into scalable technical solutions.
  
  

• Robust, resilient backend systems powering AI-driven applications for Proximity’s global partners.
• Consistent reduction in inference latency and infrastructure costs.
• High availability and fault tolerance across production services.
• Rapid, collaborative feature delivery with product and ML teams.
• Clear documentation and monitoring practices that ensure operational smoothness.
  

Requirements

• Bachelor’s or Master’s degree in Computer Science or a related field.
• 4–6 years of backend development experience, ideally with exposure to AI or large-scale data systems.
• Proficiency in Java, Golang, or Python with strong coding and system design fundamentals.
• Experience designing and scaling distributed systems at production scale.
• Exposure to LLM inference setups (e.g., vLLM, Hugging Face Inference, Triton).
• Strong debugging, profiling, and performance tuning skills for latency-sensitive applications.
• Knowledge of storage systems, query optimization, and caching strategies.
• Hands-on experience with AWS (preferred), Kafka, and CI/CD pipelines.
• Ability to work autonomously and deliver in fast-paced environments.
• Passion for mentoring engineers and leading by example.
• Curiosity about ad-tech and search systems, and how to optimize them for user and business outcomes.

Builder’s mindset · High ownership · Analytical clarity · Collaborative spirit · Global mindset · Growth orientation

Benefits

• Work directly on frontier AI problems with some of the world’s largest sports, media, and entertainment brands.
• Be part of a global-first, high-performance engineering culture.
• Competitive compensation aligned with global markets, with remote-first flexibility.
• Annual global off-sites with Proxonauts from San Francisco, Dubai, India, and beyond.
• High autonomy, direct accountability, and the opportunity to ship AI systems at scale.

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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Position :
AI/ML Engineer.

Location :
Bangalore.

Industry :
IT Software.

Experience Required :
3-5 Years.

WFO 5 Days

• The focus is on advanced machine learning, with significant depth in deep learning, large language models, and recommender systems.
• Youll be involved in validation, defect management, and the overall software development life cycle.
• The role requires extensive hands-on experience with Ubuntu/Yocto Linux, as well as popular open-source ML frameworks like PyTorch, TensorFlow, and ONNX Runtime.
• Exposure to profiling ML workloads, end-to-end AI/ML compute stack validation (including HIP, CUDA, OpenCL, OpenVINO, ONNX Runtime, TensorFlow/PyTorch integration), and end-to-end AI pipeline assessment from model conversion to inference and kernel execution.
• Proficiency in Python programming, strong problem-solving skills, and a mindset open to innovative approaches are vital.
• Youll work using global production software quality assurance methodologies, taking strong ownership of deliverables, and collaborating with teams globally.

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Company Description
MarsDevs is a remote-first, offshore digital product development company based in India.

We specialize in building MVPs, Mobile and Web Applications, SaaS Products, and vertical solutions for SMBs.

With a Track Record Of Delivering Over 60 Solutions In 10 Countries And 12 Different Industry Verticals, We Focus On Quality Code, Speed, And Lasting Technical

• Build and scale Retrieval-Augmented Generation (RAG) systems.
• Fine-tune LLMs for specific use cases and improve performance.
• Develop multi-agent systems using LangChain/LangGraph or other equivalent tools.
• Work with vector databases and scale them using metadata strategies.
• Optimize and deploy transformer-based models.
• Handle large datasets and design efficient data pipelines.
• Address LLM limitations with prompt engineering and fallback logic.
• Collaborate with product, data, and engineering teams to ship AI solutions.
• Stay updated on new tools, research, and apply best-fit :
• Should have 4+ years of experience.
• Experience building large-scale RAG systems.
• Hands-on with LLM fine-tuning and transformers.
• Strong with vector DBs (Pinecone, FAISS, etc.) and metadata filtering.
• Proven experience with multi-agent AI systems.
• Solid Python skills, good grasp of ML fundamentals.
• Experience with LangChain, LangGraph.
• Comfortable deploying on AWS/GCP/Azure.
• Knows LLM limitations and practical workarounds.
• NLP and conversational AI :
• Knowledge of MLOps, model deployment workflows.
• Familiarity with Spark, Ray, or other distributed systems.

)

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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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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