Job Type: Full-timeLocation: On-site We are looking for a skilled Python Backend Engineer to join our growing team at Immerso AI. You will work closely with our AI/ML team to build scalable backend systems that power intelligent media tools. Your work will directly support AI-driven applications like face swapping, image generation, and content analytics. ResponsiblitesDevelop and maintain APIs using FastAPIDesign and manage relational data in PostgreSQLCollaborate with AI/ML teams to serve and integrate modelsHandle image metadata, storage references, and retrieval pipelinesEnsure backend services are scalable, secure, and production-readyContribute to Docker-based deployment setups Required SkillsProficiency in Python 3.x and FastAPIExperience with PostgreSQL (schemas, queries, indexing)Familiarity with Docker and REST API principlesStrong collaboration skills, especially with AI/ML teamsGood understanding of backend architecture and performance optimization Additional QualificationsExperience with ORM tools (SQLAlchemy or SQLModel)Basic understanding of AI/ML model deploymentFamiliarity with cloud services (AWS, GCP, or similar)

About the Role We are looking for a skilled and creative Flutter Developer to join our engineering team. You will be responsible for building cross-platform mobile applications with high performance, rich animations, and seamless integration with AI-driven APIs. This role offers the opportunity to shape visually compelling user experiences that reach a global audience. Key Responsiblites:Develop and maintain high-quality Flutter applications for both iOS and AndroidIntegrate with FastAPI backend and GPT-powered APIsTranslate UI/UX designs into responsive, elegant mobile interfacesCollaborate with designers, backend engineers, and AI/ML teamsEnsure optimal performance, usability, and animation smoothnessImplement state management using Provider, Riverpod, or similar tools Required Experience:Strong experience with Flutter & DartProficient in building and consuming REST APIsSolid grasp of state management conceptsAbility to implement custom animations and UI componentsUnderstanding of mobile performance optimization and responsive design Additional Qualifications:Experience with Firebase services (Auth, Analytics, etc.)Familiarity with AI-integrated apps or GPT APIsKnowledge of deploying apps to App Store and Google PlayExposure to tools like Lottie, Rive, or Flutter Animate

DevOps EngineerJob Type: Full-timeLocation: On-site About the Role: We’re looking for a skilled DevOps Engineer to design, implement, and manage robust CI/CD pipelines, cloud infrastructure, and containerized deployments. You’ll collaborate across teams to ensure performance, reliability, and seamless deployment of AI-driven products. Key Responsibilities:Build and maintain CI/CD pipelines using Jenkins, GitLab CI, or GitHub ActionsManage containerized applications with Docker and KubernetesDeploy, monitor, and optimize cloud infrastructure on AWS, GCP, or AzureAutomate infrastructure using Terraform, AnsibleMonitor server performance with Prometheus, Grafana, and ensure uptimeAdminister Nginx/Apache and maintain secure server environments Requirements:1–3 years of DevOps engineering experienceStrong foundation in CI/CD, containerization, and cloud platformsProficient in Linux/Windows server managementHands-on with Git, GitHub, GitLab, or Bitbucket for version controlBachelor's degree in CS/IT or equivalent practical experience

Job Description: We are seeking a skilled and experienced Frontend Developer with over 2 years of experience in building modern web applications using React. The ideal candidate should have a strong understanding of UI/UX principles, responsive design, and frontend performance optimization. Proficiency in both Bootstrap and Tailwind CSS is required to deliver visually appealing and mobile-responsive applications. Responsibilities: Develop, test, and maintain responsive user interfaces using React. Implement reusable components and ensure cross-browser compatibility. Integrate frontend applications with RESTful APIs. Apply styling using Bootstrap and Tailwind CSS, maintaining consistency and responsiveness across devices. Collaborate with backend developers, designers, and stakeholders to enhance user experience. Requirements: B.E, B.Tech in Computer Science or a related field. 2+ years of professional experience in frontend development. Strong knowledge of React and modern JavaScript (ES6+). Proficiency in CSS frameworks: Bootstrap and Tailwind CSS . Experience with responsive and mobile-first design. Strong expertise in developing and integrating RESTful APIs for seamless data communication between systems. Excellent attention to detail and problem-solving skills. Show more Show less

Job Description: We are looking for a skilled Computer Vision Engineer with over 2 years of hands-on experience in developing deep learning models, with practical knowledge in designing, training, and deploying end-to-end computer vision solutions for real-world applications. As a key member of our AI team, you will be responsible for building and optimizing image and video analysis systems, while collaborating with cross-functional teams to integrate models into production-ready environments and contribute to the development of scalable, AI-driven applications. Roles & Responsibilities: Design and develop computer vision models for image and video analysis tasks. Proficiency in Python and libraries such as OpenCV, NumPy, and scikit-learn. Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras. Practical knowledge of open-source models (e.g., Hugging Face Transformers), with experience in model training, testing, and fine-tuning for deployment. Exposure to Generative AI models such as GANs, VAEs, or diffusion models. Collaborate with the team to integrate and deploy models into production-ready applications. Requirements:  Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 2 years of hands-on experience in computer vision and deep learning. Strong understanding of ML/DL concepts and experience implementing real-world CV models. Familiarity with Hugging Face Transformers and open-source model fine-tuning workflows. Show more Show less

Job Description: We are looking for a passionate and talented Machine Learning Engineer with expertise in Speech Processing to join our team. This role offers the opportunity to work on cutting-edge technologies, develop state-of-the-art solutions, and make a real impact in the field of audio and speech applications. Educational Qualifications: Master’s or PhD in Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related field with a specialization in Speech Processing. Key Responsibilities: Design and develop advanced machine learning algorithms and pipelines for audio and speech generative models, aiming to achieve state-of-the-art (SOTA) performance. Work hands-on with frameworks for Speaker Diarization , Source Separation , Noise Cancellation , Speaker Recognition , and Automatic Speech Recognition (ASR) . Should be able to build text-to-speech (TTS) synthesizers along with integrated features like voice cloning Emotion Control, Accent Flexibility, Pitch variation, and Expressivity. Research and implement speech-to-speech translation (S2ST) systems with a focus on improving accuracy and efficiency. Conduct experiments on large-scale datasets and address challenges related to domain-shifted conditions. Collaborate with cross-functional teams to integrate speech models into real-world applications. Stay up-to-date with the latest advancements in speech processing and explore ways to apply them effectively. Requirements: Proven experience in implementing and optimizing SOTA frameworks for Speaker Diarization , Source Separation , Noise Cancellation , Speaker Recognition , and ASR . Must have experience working with SOTA TTS frameworks or models, along with a solid understanding of integrating advanced features such as Voice Cloning (including zero-shot, cross-lingual, and code-switched speech generation), Emotion Control, Accent Flexibility, Pitch Variation, and Expressivity. Practical knowledge of handling large-scale datasets and managing experiments under domain shifted conditions. Expertise in S2ST systems and their end-to-end development. Strong programming skills in Python and experience with frameworks such as TensorFlow or PyTorch.

Job Type: Full-time Location: On-site About The Role We’re looking for a skilled DevOps Engineer to design, implement, and manage robust CI/CD pipelines, cloud infrastructure, and containerized deployments. You’ll collaborate across teams to ensure performance, reliability, and seamless deployment of AI-driven products. Key Responsibilities Build and maintain CI/CD pipelines using Jenkins, GitLab CI, or GitHub Actions Manage containerized applications with Docker and Kubernetes Deploy, monitor, and optimize cloud infrastructure on AWS, GCP, or Azure Automate infrastructure using Terraform, Ansible Monitor server performance with Prometheus, Grafana, and ensure uptime Administer Nginx/Apache and maintain secure server environments Requirements 1–3 years of DevOps engineering experience Strong foundation in CI/CD, containerization, and cloud platforms Proficient in Linux/Windows server management Hands-on with Git, GitHub, GitLab, or Bitbucket for version control Bachelor's degree in CS/IT or equivalent practical experience

Job Description: We are hiring a Backend Developer with more than 2 years of experience to build scalable, high-performance backend systems. The ideal candidate should be proficient in Django (mandatory) and FastAPI, experienced in both PostgreSQL and MongoDB, and familiar with using Redis for caching and performance optimization. Knowledge of cloud platforms is a plus. Responsibilities: Design, develop, and maintain robust backend applications using Django and FastAPI . Build and integrate RESTful APIs to support frontend applications and third-party integrations. Design and manage database schemas in PostgreSQL and MongoDB . Implement Redis for caching, session storage, and performance enhancements. Develop secure authentication, authorization, and business logic layers. Monitor application performance and troubleshoot production issues. Requirements: B.E, B.Tech in Computer Science or a related field. 2+ years of professional backend development experience. Strong experience with Django (mandatory) and FastAPI . Solid understanding of PostgreSQL and MongoDB databases. Experience with Redis for caching and performance optimization. Proficiency in building and consuming RESTful APIs . Knowledge of cloud platforms (AWS, GCP, Azure) is a plus.

NLP Engineer Job Description: The NLP Engineer will develop natural language processing systems for extracting insights from video metadata, comments, and auto-generating video descriptions, tags, and summaries that enhance video discoverability and engagement. Roles: · Build and optimize NLP models for summarization, sentiment analysis, and keyword extraction. · Design and deploy systems for automated description generation based on video content. · Collaborate with AI Integration Engineers for seamless deployment into production environments. · Implement text classification and auto-tagging features to improve video metadata. Responsibilities: · Train and fine-tune NLP models such as BERT, GPT, or other transformer models to generate SEO-friendly video descriptions. · Build pipelines for automatic tag generation based on video metadata and comment analysis. · Perform sentiment analysis and keyword extraction from video transcripts to enhance video discoverability. · Maintain and update NLP models, ensuring their scalability and integration into backend services.

API Engineer Job Description: The API Engineer will design, develop, and maintain scalable RESTful APIs that connect the frontend, backend, and AI services. They will ensure seamless communication and integration with AI models and video data processing systems. Roles: · Design and implement robust and secure RESTful APIs. · Collaborate with frontend and AI teams to integrate video data and AI services. · Manage versioning and documentation for API services. · Implement API performance optimizations, ensuring low latency. Responsibilities: · Develop and maintain API endpoints for video uploads, processing, and AI analysis. · Ensure secure and efficient API architectures, handling authentication, rate limiting, and security protocols. · Collaborate with the front end and database teams to define API contracts and implement required functionality. · Troubleshoot and resolve issues related to API performance, security, and scalability.

Job Description: We are looking for a skilled Computer Vision Engineer with over 2 years of hands-on experience in developing deep learning models, with practical knowledge in designing, training, and deploying end-to-end computer vision solutions for real-world applications. As a key member of our AI team, you will be responsible for building and optimizing image and video analysis systems, while collaborating with cross-functional teams to integrate models into production-ready environments and contribute to the development of scalable, AI-driven applications. Roles & Responsibilities: Design and develop computer vision models for image and video analysis tasks. Proficiency in Python and libraries such as OpenCV, NumPy, and scikit-learn. Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras. Practical knowledge of open-source models (e.g., Hugging Face Transformers), with experience in model training, testing, and fine-tuning for deployment. Exposure to Generative AI models such as GANs, VAEs, or diffusion models. Collaborate with the team to integrate and deploy models into production-ready applications. Requirements: Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 2 years of hands-on experience in computer vision and deep learning. Strong understanding of ML/DL concepts and experience implementing real-world CV models. Familiarity with Hugging Face Transformers and open-source model fine-tuning workflows.

The API Engineer will design, develop, and maintain scalable RESTful APIs that connect the frontend, backend, and AI services. They will ensure seamless communication and integration with AI models and video data processing systems. Design and implement robust and secure RESTful APIs. Collaborate with frontend and AI teams to integrate video data and AI services. Manage versioning and documentation for API services. Implement API performance optimizations, ensuring low latency. Responsibilities: Develop and maintain API endpoints for video uploads, processing, and AI analysis. Ensure secure and efficient API architectures, handling authentication, rate limiting, and security protocols. Collaborate with the front end and database teams to define API contracts and implement required functionality. Troubleshoot and resolve issues related to API performance, security, and scalability.,

Job Description: We are hiring a Generative AI Engineer to join our team working on AI applications involving Large Language Models (LLMs) , Vision-Language Models (VLMs) , and Computer Vision (CV) . Roles and Responsibilities: Fine-tune and optimize LLMs for tasks such as summarization, classification, Q&A, and creative generation. Work with Vision-Language Models (e.g., BLIP, MiniGPT, Kosmos) for tasks like image captioning, visual question answering, and retrieval. Contribute to training and evaluating Computer Vision models for tasks like image generation, detection, or editing. Implement and test various prompt engineering and LoRA-based fine-tuning approaches for different tasks. Preprocess and manage multi-modal datasets (images + text), and create training/evaluation pipelines. Write clean, modular, and well-documented code for training, inference, and deployment. Collaborate with backend, product, and design teams to integrate models into real-world applications. Stay updated with the latest papers and open-source projects in the Generative AI space. Requirements: Bachelor's degree in Computer Science, Artificial Intelligence, or related field. 2–3 years of experience in machine learning or deep learning, preferably in NLP or computer vision domains. Proficiency in Python , PyTorch , and libraries such as Transformers (Hugging Face) , OpenCV , or TorchVision . Hands-on experience with LLMs (e.g., GPT, BERT, LLaMA) or CV models (e.g., CLIP, Stable Diffusion). Familiarity with transformers , attention mechanisms , tokenization , and embedding techniques . Comfortable working with datasets , training loops , and evaluation metrics .

Job Description: We are looking for a Lead Generative AI Engineer with 3–5 years of experience to spearhead development of cutting-edge AI systems involving Large Language Models (LLMs) , Vision-Language Models (VLMs) , and Computer Vision (CV) . You will lead model development, fine-tuning, and optimization for text, image, and multi-modal use cases. This is a hands-on leadership role that requires a deep understanding of transformer architectures, generative model fine-tuning, prompt engineering, and deployment in production environments. Roles and Responsibilities: Lead the design, development, and fine-tuning of LLMs for tasks such as text generation, summarization, classification, Q&A, and dialogue systems. Develop and apply Vision-Language Models (VLMs) for tasks like image captioning, VQA, multi-modal retrieval, and grounding. Work on Computer Vision tasks including image generation, detection, segmentation, and manipulation using SOTA deep learning techniques. Leverage frameworks like Transformers, Diffusion Models, and CLIP to build and fine-tune multi-modal models. Fine-tune open-source LLMs and VLMs (e.g., LLaMA, Mistral, Gemma, Qwen, MiniGPT, Kosmos, etc.) using task-specific or domain-specific datasets. Design data pipelines , model training loops, and evaluation metrics for generative and multi-modal AI tasks. Optimize model performance for inference using techniques like quantization, LoRA, and efficient transformer variants. Collaborate cross-functionally with product, backend, and ML ops teams to ship models into production. Stay current with the latest research and incorporate emerging techniques into product pipelines. Requirements: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 3–5 years of hands-on experience in building, training, and deploying deep learning models, especially in LLM, VLM , and/or CV domains. Strong proficiency with Python , PyTorch (or TensorFlow), and libraries like Hugging Face Transformers, OpenCV, Datasets, LangChain, etc. Deep understanding of transformer architecture , self-attention mechanisms , tokenization , embedding , and diffusion models . Experience with LoRA , PEFT , RLHF , prompt tuning , and transfer learning techniques. Experience with multi-modal datasets and fine-tuning vision-language models (e.g., BLIP, Flamingo, MiniGPT, Kosmos, etc.). Familiarity with MLOps tools , containerization (Docker), and model deployment workflows (e.g., Triton Inference Server, TorchServe). Strong problem-solving, architectural thinking, and team mentorship skills.

Job Description: We are looking for a Lead Generative AI Engineer with 35 years of experience to spearhead development of cutting-edge AI systems involving Large Language Models (LLMs) , Vision-Language Models (VLMs) , and Computer Vision (CV) . You will lead model development, fine-tuning, and optimization for text, image, and multi-modal use cases. This is a hands-on leadership role that requires a deep understanding of transformer architectures, generative model fine-tuning, prompt engineering, and deployment in production environments. Roles and Responsibilities: Lead the design, development, and fine-tuning of LLMs for tasks such as text generation, summarization, classification, Q&A, and dialogue systems. Develop and apply Vision-Language Models (VLMs) for tasks like image captioning, VQA, multi-modal retrieval, and grounding. Work on Computer Vision tasks including image generation, detection, segmentation, and manipulation using SOTA deep learning techniques. Leverage frameworks like Transformers, Diffusion Models, and CLIP to build and fine-tune multi-modal models. Fine-tune open-source LLMs and VLMs (e.g., LLaMA, Mistral, Gemma, Qwen, MiniGPT, Kosmos, etc.) using task-specific or domain-specific datasets. Design data pipelines , model training loops, and evaluation metrics for generative and multi-modal AI tasks. Optimize model performance for inference using techniques like quantization, LoRA, and efficient transformer variants. Collaborate cross-functionally with product, backend, and ML ops teams to ship models into production. Stay current with the latest research and incorporate emerging techniques into product pipelines. Requirements: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 35 years of hands-on experience in building, training, and deploying deep learning models, especially in LLM, VLM , and/or CV domains. Strong proficiency with Python , PyTorch (or TensorFlow), and libraries like Hugging Face Transformers, OpenCV, Datasets, LangChain, etc. Deep understanding of transformer architecture , self-attention mechanisms , tokenization , embedding , and diffusion models . Experience with LoRA , PEFT , RLHF , prompt tuning , and transfer learning techniques. Experience with multi-modal datasets and fine-tuning vision-language models (e.g., BLIP, Flamingo, MiniGPT, Kosmos, etc.). Familiarity with MLOps tools , containerization (Docker), and model deployment workflows (e.g., Triton Inference Server, TorchServe). Strong problem-solving, architectural thinking, and team mentorship skills. Show more Show less

Job Description: We are looking for a Lead Generative AI Engineer with 35 years of experience to spearhead development of cutting-edge AI systems involving Large Language Models (LLMs) , Vision-Language Models (VLMs) , and Computer Vision (CV) . You will lead model development, fine-tuning, and optimization for text, image, and multi-modal use cases. This is a hands-on leadership role that requires a deep understanding of transformer architectures, generative model fine-tuning, prompt engineering, and deployment in production environments. Roles and Responsibilities: Lead the design, development, and fine-tuning of LLMs for tasks such as text generation, summarization, classification, Q&A, and dialogue systems. Develop and apply Vision-Language Models (VLMs) for tasks like image captioning, VQA, multi-modal retrieval, and grounding. Work on Computer Vision tasks including image generation, detection, segmentation, and manipulation using SOTA deep learning techniques. Leverage frameworks like Transformers, Diffusion Models, and CLIP to build and fine-tune multi-modal models. Fine-tune open-source LLMs and VLMs (e.g., LLaMA, Mistral, Gemma, Qwen, MiniGPT, Kosmos, etc.) using task-specific or domain-specific datasets. Design data pipelines , model training loops, and evaluation metrics for generative and multi-modal AI tasks. Optimize model performance for inference using techniques like quantization, LoRA, and efficient transformer variants. Collaborate cross-functionally with product, backend, and ML ops teams to ship models into production. Stay current with the latest research and incorporate emerging techniques into product pipelines. Requirements: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 35 years of hands-on experience in building, training, and deploying deep learning models, especially in LLM, VLM , and/or CV domains. Strong proficiency with Python , PyTorch (or TensorFlow), and libraries like Hugging Face Transformers, OpenCV, Datasets, LangChain, etc. Deep understanding of transformer architecture , self-attention mechanisms , tokenization , embedding , and diffusion models . Experience with LoRA , PEFT , RLHF , prompt tuning , and transfer learning techniques. Experience with multi-modal datasets and fine-tuning vision-language models (e.g., BLIP, Flamingo, MiniGPT, Kosmos, etc.). Familiarity with MLOps tools , containerization (Docker), and model deployment workflows (e.g., Triton Inference Server, TorchServe). Strong problem-solving, architectural thinking, and team mentorship skills. Show more Show less

As an iOS Developer, you will be responsible for building iOS apps using Swift and Xcode while following modern design patterns such as MVC/MVVM. You will need to integrate backend services through Microservices APIs to enable scalable and modular features. Collaboration with design, product, and backend teams will be essential for feature development and enhancements. Ensuring high code quality through unit testing, performance tuning, and crash analytics will also be a key part of your role. Additionally, you will handle end-to-end App Store deployment, updates, and versioning. The ideal candidate should be proficient in Swift, with experience using UIKit and/or SwiftUI. Knowledge of working with Microservices and securely handling REST API integration is required. Familiarity with Xcode, version control (Git), and debugging tools is essential. A solid understanding of the iOS app lifecycle, architecture, and Apple Human Interface Guidelines is expected. Experience with testing frameworks and API testing tools like Postman or Charles Proxy would be advantageous.,