204 Ffmpeg Jobs - Page 3

Lead Assistant Manager EXL/LAM/1465683 Digital SolutionsNoida Posted On 29 Aug 2025 End Date 13 Oct 2025 Required Experience 2 - 5 Years Basic Section Number Of Positions 1 Band B2 Band Name Lead Assistant Manager Cost Code D014959 Campus/Non Campus NON CAMPUS Employment Type Permanent Requisition Type New Max CTC 1000000.0000 - 2500000.0000 Complexity Level Not Applicable Work Type Hybrid – Working Partly From Home And Partly From Office Organisational Group EXL Digital Sub Group Digital Solutions Organization Digital Solutions LOB CX(CONNECx) SBU Exelia.AI Country India City Noida Center Noida - Centre 59 Skills Skill PYTHON PROGRAMMING NATURAL LANGUAGE PROCESSING - NLP GCP Minimum Qualification BTECH Certification No data available Job Description Senior ASR/TTS Specialist - AI Agent Integration Expert Company: EXL Service Type: Full-time Experience: 3+ years Position Summary We seek an exceptional Senior ASR/TTS Specialist to lead speech AI initiatives and integrate advanced speech technologies with AI agent frameworks. This role focuses on fine-tuning ASR/TTS models, implementing MLOps best practices, and building production-ready speech AI systems powering next-generation conversational AI agents. Key Responsibilities Speech AI Model Development & Integration Model Fine-tuning : Customize state-of-the-art ASR/TTS models for domain-specific applications with <300ms latency Speech-to-Speech Systems : Build end-to-end S2S pipelines using Amazon Nova Sonic v1.0, Azure OpenAI Realtime (GPT-4o), and Gemini 2.5 Flash Native Audio Multi-modal Integration : Develop speech models integrating with vision and text modalities in AI agents Agent Framework Integration : Implement speech capabilities with LangChain/LangGraph, CrewAI, AutoGen, LlamaIndex, and OpenAI Assistants API MLOps & Production Engineering Model Lifecycle : Implement comprehensive MLOps pipelines using MLflow, Weights & Biases, and automated CI/CD Multi-cloud Deployment : Deploy speech models across AWS Bedrock, Google Cloud AI, and Azure Cognitive Services Real-time Processing : Build WebSocket-based streaming audio systems handling 1000+ concurrent connections Production Monitoring : Implement WER tracking, latency monitoring, and multi-provider failover mechanisms Research & Development Cutting-edge Research : Stay current with latest speech AI breakthroughs and implement novel architectures Performance Optimization : Optimize models for real-time inference using TensorRT, ONNX, and edge deployment Data Pipeline Engineering : Build scalable audio ingestion, preprocessing, and augmentation systems Required Qualifications Core Technical Skills (Must-Have) Speech AI Models (3+ years experience): - ASR Systems : Amazon Nova Sonic v1.0, Google Speech-to-Text, Azure Speech Services, Whisper, Wav2Vec2, Riva - TTS Systems : Google TTS, Azure Cognitive Services TTS, ElevenLabs (REST/WebSocket), Tortoise, VITS, FastSpeech2 - Speech-to-Speech : Direct S2S without intermediate text, multimodal audio processing - Cloud Services : AWS Bedrock Runtime, Google Cloud AI (Gemini API), Azure OpenAI Services Programming & Frameworks: - Languages : Expert Python, proficient C++/Rust for optimization - ML Frameworks : Advanced PyTorch, TensorFlow 2.x, JAX/Flax - Audio Processing : librosa, torchaudio, soundfile, WebRTC, µ-law/PCM conversion - Agent Frameworks : Hands-on experience with 3+ of: LangChain, CrewAI, AutoGen, LlamaIndex, OpenAI Assistants MLOps & Infrastructure (Essential) MLOps Tools (2+ years): - Experiment Management : MLflow, Weights & Biases - Model Serving : TorchServe, TensorFlow Serving, NVIDIA Triton - Workflow Orchestration : Apache Airflow, Kubeflow, Prefect - Containerization : Docker, Kubernetes for speech model deployment Cloud & Production: - Multi-cloud Experience : AWS (Bedrock, Nova Sonic), Google Cloud (Gemini, Speech APIs), Azure (OpenAI Services) - Real-time Systems : Sub-300ms latency, WebSocket architecture, telecom integration (Genesys AudioConnector) - Monitoring : Audio quality metrics, model drift detection, production reliability (99.9% uptime) Preferred Qualifications Advanced Specializations Multi-lingual Processing : Cross-lingual transfer learning, zero-shot adaptation Domain Expertise : Healthcare, legal, technical domain speech AI Edge AI : TensorRT, Core ML, ONNX optimization for mobile/edge deployment Research Background : Publications in ICASSP, INTERSPEECH, ICML, NeurIPS Leadership & Education Team Leadership : Experience leading speech AI teams and technical initiatives Education : MS/PhD in Computer Science, Electrical Engineering, or related field Open Source : Contributions to speech AI libraries and frameworks Technical Environment Production Technology Stack Core Technologies: - Languages : Python, C++, Rust, TypeScript - Frameworks : PyTorch, TensorFlow, JAX, LangChain, CrewAI, AutoGen - Cloud Services : AWS Bedrock, Google Cloud AI, Azure OpenAI Services - Audio Tools : librosa, torchaudio, WebRTC, FFmpeg - MLOps : MLflow, Kubeflow, Docker, Kubernetes, NVIDIA Triton - Databases : Vector DBs (Pinecone, Weaviate), PostgreSQL, Redis Production Models: - Amazon Nova Sonic v1.0 (Speech-to-Speech streaming) - Gemini 2.5 Flash Native Audio Dialog (Multimodal processing) - Azure OpenAI GPT-4o (Realtime voice conversations) - ElevenLabs (Voice cloning and synthesis) Infrastructure GPU Clusters : NVIDIA A100/H100 for model training Edge Deployment : NVIDIA Jetson, ARM-based targets Real-time Requirements : <300ms latency, 1000+ concurrent streams Enterprise Integration : Genesys AudioConnector, SIP protocol, telephony systems Key Projects & Success Metrics Primary Focus Areas Next-gen S2S Systems : Amazon Nova Sonic, Azure OpenAI Realtime, Gemini Native Audio Multi-cloud Integration : Unified APIs across AWS, Google Cloud, Azure Conversational AI Agents : Low-latency speech-enabled customer service bots Telecom Integration : Enterprise telephony and AudioConnector systems Domain-specific Models : Medical, legal, technical vocabulary fine-tuning Success Metrics Performance : <5% WER for domain-specific tasks Latency : <300ms end-to-end processing Reliability : 99.9% uptime for production services Scale : 1000+ concurrent speech streams Workflow Workflow Type Digital Solution Center

Important Note: Read till the end and send application on our Whatsapp no. to be considered. ---- Get ready to be a part of fast-growing team making next generation marketing platform to make it really simple to launch marketing campaigns with AI Agents. We have been recognized among the Tech50 companies of 2021 by Yourstory and got Startup Maharathi award at Startup Mahakumbh 2025. Tired of being a small cog in a big machine? At Intellemo, you won't just be writing codeyou'll be a core member of our engineering team, building the brain behind our AI marketing agents that are changing the game for thousands of businesses. We are a funded, profitable, fast-growing startup on a mission to make sophisticated marketing and sales automation accessible to everyone. The Opportunity This isn't just another backend role. As our core backend hire, you will have unparalleled ownership, a direct impact on our product's success, and the opportunity to work directly alongside the CEO/CTO to shape our entire technical foundation. You will be instrumental in solving our biggest bottleneck and paving the way for us to scale 10x. If you thrive on challenges and want your work to matter, this is the role for you. Key Responsibilities: Develop and maintain our backend services , including building and consuming RESTful APIs and working with our GraphQL API gateway. Integrate with external platforms such as Google Ads, Meta Ads, Linkedin Ads, Pinterest, etc. to automate campaign management and reporting. Connect with AI/ML APIs and contribute to the development of our agentic AI capabilities. Orchestrate agentic behavior using internal Agentic framework to create intelligent, automated marketing workflows. Build and optimize our creative rendering engine for generating images and videos using libraries like wand, ImageMagick, and FFmpeg. Develop web scraping and data extraction capabilities for website/landing page analysis using tools like BeautifulSoup. Contribute to our microservices-oriented architecture , ensuring our services are scalable, maintainable, and resilient. Collaborate with frontend developers to ensure seamless integration of our backend services with the user interface. Write clean, efficient, and well-documented code , and participate in code reviews to maintain our high standards of quality. Required Skills and Qualifications: 1-2 years of professional experience as a Python Backend Engineer with Gen AI focus. Strong proficiency in Python FastAPI. Demonstrable experience with building and integrating with third-party APIs, particularly for marketing related platforms like Google Ads and Meta Ads. A solid understanding of AI/ML concepts and experience working with AI/ML APIs. Familiarity with Langchain, MCP or similar frameworks for building applications with large language models (LLMs). Experience with image or video processing libraries such as CV2, ImageMagick, or FFmpeg. Proficiency with web scraping libraries like BeautifulSoup. A good understanding of microservices architecture and its principles. Familiarity with GraphQL and experience working with API gateways. Solid knowledge of relational and NoSQL databases (e.g., PostgreSQL, MongoDB). A Bachelor's degree in Computer Science is a must. What We Offer Direct Mentorship: You will be mentored directly by the CEO/CTO, offering a unique learning opportunity you won't find anywhere else. Unmatched Impact & Ownership: See the code you write immediately affect our clients and our company's bottom line. No bureaucracy, just pure building. A Problem-Solver's Paradise: We offer a constant stream of complex and fascinating challenges at the intersection of AI, marketing, and creative automation. Rapid Growth Trajectory: As a critical early hire, you'll be on the fast track for technical leadership as the company scales. Competitive Salary: A salary in the range of 7-10 LPA + option of ESOPs post probation. Location: This is a full-time, in-office position at our Gurgaon, Haryana office. We don't have Work from home role or remote work to iterate and build faster. We believe in the power of in-person collaboration and are excited to build a strong, cohesive team. How to Apply To apply, click on https://wa.me/917574863996?text=Hi+team,+saw+this+on+Naukri.+I+want+to+work+with+Intellemo or send Whatsapp to + 917574863996 Shortlisted candidates will be contacted to schedule the next steps in the interview process.

Job Title: Video Processing App Developer Intern (React Native / Node.js) Company: Challenz Location: Remote (Preference for New Zealand or Australia-based candidates) Internship Duration: 3 Months (Unpaid) Compensation: Top-performing interns may be offered a paid position after the internship Start Date: Immediate About the Role: We’re seeking enthusiastic and skilled Video Processing App Developer Interns to help us build powerful, creative video experiences for the Challenz app. You’ll be working on features that enable users to capture, edit, and share TikTok-style challenge videos with filters, effects, and real-time rendering—all while ensuring seamless playback and optimized storage. Responsibilities: Develop and enhance video capture, editing, and uploading workflows Implement real-time filters, transitions, and effects for video challenges Optimize video playback, compression, and storage integration with Supabase Collaborate with product and backend teams to support a high-performance media pipeline Required Skills: Experience with React Native / Expo Basic backend development skills in Node.js / Express.js Proficiency with video tools/libraries: FFmpeg, AVFoundation, OpenGL, or Metal Understanding of video encoding, GPU rendering, and compression techniques Nice to Have: Experience building TikTok-style short video apps or challenge features Familiarity with AR filters, video stickers, or audio syncing Understanding of RESTful APIs and Supabase and Cloudflare R2 integration How to Apply: Apply via LinkedIn or contact us directly at +64 2102244076.

Job Title: Sr. DevOps engineer Experience: 6+ years Location: Remote Job Type: Full-Time ABOUT THE ROLE — Senior DevOps & SRE Engineer Join a small, cross-functional squad and take charge of our cloud platform - automated CI/CD, observability, infrastructure-as-code, security hardening, and cost-efficient scaling for microservices, AI workloads, and mobile APIs. Day-to-day: partner with Product, Backend, Mobile, QA, and Security to design, build, test, and ship resilient infrastructure; run incident reviews; and drive reliability KPIs. Workflow: Slack for comms, Kanban boards, two-week sprints; AWS codebuild/codepipeline + Terraform for CICD; Docker on ECS/Fargate. Reporting line: you work directly with the ROLE_OWNER and interface with the CTO & CEO as needed. Location: worldwide - overlap at least 4 hours with North-American Eastern Time. SKILLS & EXPERIENCE Must-Have: Deep expertise with AWS (ECS/Fargate, IAM, VPC, CloudWatch) and solid understanding of container orchestration (Docker, EKS/Kubernetes). Proven IaC discipline with Terraform and AWS-based CI/CD (AWS, or GitHub Actions). Prometheus/OpenTelemetry, log pipelines (FluentBit/ELK) and alerting tools such as Datadog; able to define SLOs and automate incident response. Strong scripting in Python or Bash, plus comfort with SQL for troubleshooting. Clear, concise English communication and a bias toward proactive ownership. Nice-to-Have: Knowledge of GPU & AI/ML workloads (e.g., SageMaker, Triton) and media pipelines (FFmpeg, video codecs). Exposure to serverless / event-driven design (Lambda, SNS/SQS), cost-optimization. Experience hardening systems for SOC 2 / PCI or similar compliance; familiarity with DevSecOps scanning and secrets management. Familiarity with React/Next.js, Python ecosystems and mobile CI/CD. Prior work on high-scale, real-time products (WebSocket gateways, streaming).

This role is for one of the Weekday's clients Salary range: Rs 1500000 - Rs 2000000 (ie INR 15-20 LPA) Min Experience: 3 years Location: Remote (India) JobType: full-time We are expanding rapidly and seeking sharp, self-driven engineers to help shape our next-generation platform. If you enjoy working in fast-paced environments and love solving complex SaaS scaling challenges, this role is for you. Requirements Qualifications & Responsibilities Strong proficiency in troubleshooting and infrastructure management Solid background in software development and programming Hands-on experience with databases Excellent analytical and problem-solving skills Ability to work independently and remotely Bachelor's degree in Computer Science, Information Technology, or related field (preferred) Exposure to ML model training and deployments (a plus) Essential Skills Advanced Python programming skills Strong experience with SQL Proficiency in at least one web framework: Tornado, Flask, FastAPI Experience with video encoding (ffmpeg) and image processing (GraphicsMagick, PIL) Familiarity with Git, CI/CD, and DevOps tools Frontend experience with React, TypeScript, HTML5, CSS3 Nice-to-Have Skills Additional expertise in video encoding and image processing Knowledge of machine learning and related tools Experience with web/proxy servers (nginx, Apache, Traefik) Understanding of SaaS stacks such as task queues, search engines, cache servers Prior exposure to startup or early-stage environments What We're Not Looking For Candidates without prior experience building or contributing to cloud-based SaaS applications Candidates uncomfortable working independently and remotely What You'll Gain High autonomy with a low-meeting culture — we trust you to deliver your best work Direct collaboration with founders and senior engineers — no unnecessary layers A continuous learning budget for courses, books, and events A fast-paced, creative environment where your contributions have a direct impact Core Skills: Python | API Development | Web Development | FastAPI | MySQL | Docker Swarm | Celery | AWS | React Native | TypeScript | HTML5/CSS3 | CI/CD | Machine Learning

Python Backend Engineer – Video Processing & Edge Deployment Role Overview You will develop high-performance video processing pipelines optimized for both cloud and edge environments, leveraging GPUs for acceleration and advanced compression for efficiency. Key Responsibilities 1. Build backend systems for video ingestion, processing, and distribution. 2. Implement FFmpeg pipelines for transcoding, compression, and FPS adjustments. 3. Optimize video workflows for H.265 and AV1 codecs. 4. Deploy and manage workloads on Nvidia A16 GPUs and Nvidia Jetson edge devices. 5. Integrate video analytics into backend APIs. 6. Tune video processing performance for edge and low-bandwidth environments. 7. Maintain and troubleshoot Linux-based video processing deployments. Required Skills 1. Strong command of Python and Django. 2. In-depth expertise in FFmpeg for complex video workflows. 3. Experience with GPU-based development (Nvidia A16, Nvidia Jetson). 4. Knowledge of H.265 and AV1 compression algorithms. 5. Understanding of FPS optimization in streaming/video pipelines. 6. Proficiency with Linux systems and backend deployment practices. Location - IIT Delhi Job Types: Full-time, Permanent Pay: ₹50,000.00 - ₹60,000.00 per month Application Question(s): Do you have experience in Video Processing & Edge Deployment? Can you submit relieving letter on the 1st day of joining? Work Location: In person Speak with the employer +91 8638994017

Job Title: Sr. DevOps engineer Experience: 6+ years Location: Remote Job Type: Full-Time ABOUT THE ROLE — Senior DevOps & SRE Engineer Join a small, cross-functional squad and take charge of our cloud platform - automated CI/CD, observability, infrastructure-as-code, security hardening, and cost-efficient scaling for microservices, AI workloads, and mobile APIs. Day-to-day: partner with Product, Backend, Mobile, QA, and Security to design, build, test, and ship resilient infrastructure; run incident reviews; and drive reliability KPIs. Workflow: Slack for comms, Kanban boards, two-week sprints; AWS codebuild/codepipeline + Terraform for CICD; Docker on ECS/Fargate. Reporting line: you work directly with the ROLE_OWNER and interface with the CTO & CEO as needed. Location: worldwide - overlap at least 4 hours with North-American Eastern Time. SKILLS & EXPERIENCE Must-Have: Deep expertise with AWS (ECS/Fargate, IAM, VPC, CloudWatch) and solid understanding of container orchestration (Docker, EKS/Kubernetes). Proven IaC discipline with Terraform and AWS-based CI/CD (AWS, or GitHub Actions). Prometheus/OpenTelemetry, log pipelines (FluentBit/ELK) and alerting tools such as Datadog; able to define SLOs and automate incident response. Strong scripting in Python or Bash, plus comfort with SQL for troubleshooting. Clear, concise English communication and a bias toward proactive ownership. Nice-to-Have: Knowledge of GPU & AI/ML workloads (e.g., SageMaker, Triton) and media pipelines (FFmpeg, video codecs). Exposure to serverless / event-driven design (Lambda, SNS/SQS), cost-optimization. Experience hardening systems for SOC 2 / PCI or similar compliance; familiarity with DevSecOps scanning and secrets management. Familiarity with React/Next.js, Python ecosystems and mobile CI/CD. Prior work on high-scale, real-time products (WebSocket gateways, streaming).

Location: Remote (India) Schedule: Required daily working window: 10:00 AM – 1:00 PM Pacific Time (PST/PDT) , regardless of location (including India). For reference only: this window corresponds to ~ 11:30 PM – 2:30 AM IST during PST and 10:30 PM – 1:30 AM IST during PDT. Engagement: Open to contract or full‑time (discussed during process) About the Role We’re looking for a video graphics animator who specializes in AI‑generated video —especially node‑based pipelines in ComfyUI —to produce polished short‑form content and AI influencer videos. You’ll build repeatable workflows, ship eye‑catching visuals, and keep us on the cutting edge of generative video. What You’ll Do Design, build, and iterate end‑to‑end AI video pipelines (storyboard → generation → post) using ComfyUI and complementary tools. Create AI influencer content : persona development, look consistency, lip‑sync, expression control, and voice‑to‑video alignment; deliver platform‑ready cuts (TikTok, Reels, YT Shorts). Own motion design & finishing : typography, transitions, overlays, color, sound design, and final QC (deflicker, stabilization, upscaling). Standardize workflows : version‑lock nodes/models, maintain presets, and document best practices for reproducibility. Experiment fast with new models, motion modules, and control methods; present comparisons and recommendations. Collaborate in real time during the required 10 AM–1 PM Pacific window with creative, growth, and product stakeholders. Manage media ops : assets, rights/attribution, prompt libraries, seeds, and shot catalogs. What Success Looks Like (60–90 Days) A reusable ComfyUI pipeline (JSON) for AI influencer shorts with lip‑sync and motion control, producing consistent character identity. A library of style presets (look, typography, music beds) and a prompt pack for at least 3 content series. A cadence of 3–5 publish‑ready clips/week meeting platform specs and brand guidelines. Clear documentation on workflow, model choices, and performance trade‑offs. Required Skills & Experience Portfolio of AI video work (must include AI avatar/influencer or comparable character‑consistent content). Expert with ComfyUI (custom nodes, graph optimization, batching, tiled diffusion, IP‑Adapter/Control workflows, model management). Strong grasp of diffusion/video fundamentals : prompting, seeds, CFG/schedulers, ref image conditioning, AnimateDiff / motion modules, control nets, frame interpolation, face restoration, upscaling, and deflicker. Lip‑sync / audio‑driven animation experience (e.g., Wav2Lip/SadTalker‑style pipelines or similar) and voice‑to‑video timing . Pro‑level finishing in one or more: After Effects , Premiere Pro , DaVinci Resolve/Fusion , or Nuke . Solid motion design: type, layout, timing, easing, transitions , and sound design basics. System & ops savvy : GPU workflow know‑how, VRAM budgeting, render queues, file/version hygiene, and documentation. Excellent communication; comfortable collaborating live in the 10 AM–1 PM Pacific window. Nice‑to‑Have Experience with commercial AI video tools (e.g., Runway, Pika, Luma, etc.) and 3D integration ( Blender/Unreal ) for camera or environment work. Python familiarity for custom ComfyUI nodes or lightweight automation. Brand/social chops: hook writing, pacing for retention, and UGC‑native aesthetics. Understanding of synthetic‑media ethics , rights, and platform disclosure policies. Tools You May Use Here Generation/Orchestration: ComfyUI (core), Stable Diffusion‑based models, motion/control modules. Post & Finishing: After Effects, Premiere Pro, Resolve/Fusion, Topaz/FFmpeg utilities. Audio/Lip‑Sync: your preferred stack for TTS, alignment, and cleanup. Collaboration: Slack/Meet/Notion; Git or Drive‑based versioning for graphs/assets. Portfolio Requirements (must include links) Please include 3–6 pieces that demonstrate: AI influencer or avatar pieces with consistent identity across shots. Before/after or node graph screenshots showing your pipeline thinking. Any style‑matched or brand‑guided work (explain constraints and results). A brief note on models, nodes, and parameter choices used. How We’ll Evaluate Visual quality, consistency, and storytelling. Technical rigor and reproducibility of your pipeline. Speed from brief to publish‑ready output. Collaboration and feedback responsiveness during the Pacific hours. Compensation & Benefits Competitive pay commensurate with experience and engagement type. Fully remote; modern tool stack; fast feedback loops. Opportunity to shape our AI content strategy and build foundational workflows.

Do you want to be part of a team building high-tech robots that help the environment EarthSense is a startup on the forefront of robotics, autonomy, and agricultural technology. We're developing the next generation of artificial intelligence robots and rapidly expanding what's possible with smart and conscientious farming. We are seeking a Cloud Data and Web Software Engineer (Full Stack developer) with a strong background in data engineering, developing and deploying cloud systems, developing front end solutions, and other miscellaneous software tasks. The successful candidate will work on designing, implementing, and testing software for managing storage and transfer of data from our robots, visualizing and processing our data, and deploying large-scale data processing solutions on the cloud. Responsibilities include developing and maintaining software APIs for uploading and downloading data through our cloud services, data format conversion, data cleansing software, front end solutions for data interaction, deploying solutions on the cloud with tools like Kubernetes, and collaborating with the team on data visualization and processing tools. Qualifications: - Education: Bachelors degree in computer science - Experience: Minimum of 4 years in cloud and data engineering, particularly relating to image, video, and/or LiDAR data Technical Skills required: - Programming Languages: Proficiency in Python and web programming languages - Cloud providers: Experience with AWS required, Experience with GCP / Azure preferred - Development Tools: Docker, Git, Linux, Kubernetes - Data management tools: Experience with OpenCV, FFMPEG, ROS1/ROS2 data reading preferred Soft Skills needed: - Strong analytical and problem-solving skills - Ability to work independently and collaboratively within a team - Detail-oriented, with a commitment to software quality and testing - Positive attitude, willingness to learn, and perform in challenging environments What We Offer: - A dynamic work environment with opportunities to innovate and make a real impact in robotics - Access to the latest technology and resources to advance your skills To apply, please submit your resume, portfolio (if applicable), and a brief cover letter highlighting your experience and passion for robotics and software development to indiajobs@earthsense.co,

We are seeking a 'Computer Vision Engineer' to develop AI-driven video analytics solutions for extracting in-depth cricket data from match footage, live broadcasts, and player tracking systems. This role involves leveraging deep learning, pose estimation, and image processing to analyze player movements, shot selection, bowling mechanics, and match dynamics. Key Responsibilities. Video-Based Cricket Analytics. Develop computer vision models for player tracking, ball trajectory prediction, and shot classification. Extract real-time insights from video streams, including player positions, footwork analysis, and batting/bowling techniques. Implement pose estimation (OpenPose, MediaPipe, DeepLabCut) to analyze player body movements. Use action recognition models to classify batting strokes, bowling variations, and fielding plays. Deep Learning & Image Processing. Apply CNNs, Transformers, YOLO, Mask R-CNN, and Optical Flow for cricket action recognition. Develop segmentation models to differentiate players, umpires, and key match elements (ball, stumps, pitch zones). Use GANs and super-resolution techniques to enhance low-quality video footage. Build OCR (Optical Character Recognition) systems to extract scoreboards and match statistics from live broadcasts. Real-Time Video Processing & Streaming. Implement real-time video processing pipelines using OpenCV, FFmpeg, and GStreamer. Work with multi-angle TV footage and drone feeds to enhance match analysis. Develop low-latency algorithms for real-time ball speed, swing, and spin detection. Data Collection, Annotation & Model Training. Build automated annotation tools for labeling cricket match videos. Train supervised and unsupervised learning models using cricket datasets. Collaborate with sports analysts to validate and refine model predictions. Model Deployment & Performance Optimization. Deploy computer vision models on edge devices, cloud platforms, and real-time streaming systems. Optimize models for low latency and high accuracy in live cricket broadcasts. Implement A/B testing and continuous monitoring to improve model performance. Camera Calibration & Video Trigonometry. Perform camera calibration for distortion correction and real-world coordinate mapping. Use homography transformation and perspective correction for multi-angle alignment. Apply video trigonometry to calculate player distances, ball speed, angles, and movement trajectories. Work with multi-camera synchronization and stereo vision for depth estimation in cricket analytics. About CompanyAt Lifease Solutions LLP, we believe that design and technology are the perfect blend to solve any problem and bring any idea to life. Lifease Solutions is a leading provider of software solutions and services that help businesses succeed. Based in Noida, India, we are committed to delivering high-quality, innovative solutions that drive value and growth for our customers. Our expertise in the finance, sports, and capital market domains has made us a trusted partner for companies around the globe. We take pride in our ability to turn small projects into big successes, and we are always looking for ways to help our clients maximize their IT investments

We are seeking a 'Computer Vision Engineer' to develop AI-driven video analytics solutions for extracting in-depth cricket data from match footage, live broadcasts, and player tracking systems. This role involves leveraging deep learning, pose estimation, and image processing to analyze player movements, shot selection, bowling mechanics, and match dynamics. Key Responsibilities. Video-Based Cricket Analytics. Develop computer vision models for player tracking, ball trajectory prediction, and shot classification. Extract real-time insights from video streams, including player positions, footwork analysis, and batting/bowling techniques. Implement pose estimation (OpenPose, MediaPipe, DeepLabCut) to analyze player body movements. Use action recognition models to classify batting strokes, bowling variations, and fielding plays. Deep Learning & Image Processing. Apply CNNs, Transformers, YOLO, Mask R-CNN, and Optical Flow for cricket action recognition. Develop segmentation models to differentiate players, umpires, and key match elements (ball, stumps, pitch zones). Use GANs and super-resolution techniques to enhance low-quality video footage. Build OCR (Optical Character Recognition) systems to extract scoreboards and match statistics from live broadcasts. Real-Time Video Processing & Streaming. Implement real-time video processing pipelines using OpenCV, FFmpeg, and GStreamer. Work with multi-angle TV footage and drone feeds to enhance match analysis. Develop low-latency algorithms for real-time ball speed, swing, and spin detection. Data Collection, Annotation & Model Training. Build automated annotation tools for labeling cricket match videos. Train supervised and unsupervised learning models using cricket datasets. Collaborate with sports analysts to validate and refine model predictions. Model Deployment & Performance Optimization. Deploy computer vision models on edge devices, cloud platforms, and real-time streaming systems. Optimize models for low latency and high accuracy in live cricket broadcasts. Implement A/B testing and continuous monitoring to improve model performance. Camera Calibration & Video Trigonometry. Perform camera calibration for distortion correction and real-world coordinate mapping. Use homography transformation and perspective correction for multi-angle alignment. Apply video trigonometry to calculate player distances, ball speed, angles, and movement trajectories. Work with multi-camera synchronization and stereo vision for depth estimation in cricket analytics. About CompanyAt Lifease Solutions LLP, we believe that design and technology are the perfect blend to solve any problem and bring any idea to life. Lifease Solutions is a leading provider of software solutions and services that help businesses succeed. Based in Noida, India, we are committed to delivering high-quality, innovative solutions that drive value and growth for our customers. Our expertise in the finance, sports, and capital market domains has made us a trusted partner for companies around the globe. We take pride in our ability to turn small projects into big successes, and we are always looking for ways to help our clients maximize their IT investments

We are seeking a 'Computer Vision Engineer' to develop AI-driven video analytics solutions for extracting in-depth cricket data from match footage, live broadcasts, and player tracking systems. This role involves leveraging deep learning, pose estimation, and image processing to analyze player movements, shot selection, bowling mechanics, and match dynamics. Key Responsibilities. Video-Based Cricket Analytics. Develop computer vision models for player tracking, ball trajectory prediction, and shot classification. Extract real-time insights from video streams, including player positions, footwork analysis, and batting/bowling techniques. Implement pose estimation (OpenPose, MediaPipe, DeepLabCut) to analyze player body movements. Use action recognition models to classify batting strokes, bowling variations, and fielding plays. Deep Learning & Image Processing. Apply CNNs, Transformers, YOLO, Mask R-CNN, and Optical Flow for cricket action recognition. Develop segmentation models to differentiate players, umpires, and key match elements (ball, stumps, pitch zones). Use GANs and super-resolution techniques to enhance low-quality video footage. Build OCR (Optical Character Recognition) systems to extract scoreboards and match statistics from live broadcasts. Real-Time Video Processing & Streaming. Implement real-time video processing pipelines using OpenCV, FFmpeg, and GStreamer. Work with multi-angle TV footage and drone feeds to enhance match analysis. Develop low-latency algorithms for real-time ball speed, swing, and spin detection. Data Collection, Annotation & Model Training. Build automated annotation tools for labeling cricket match videos. Train supervised and unsupervised learning models using cricket datasets. Collaborate with sports analysts to validate and refine model predictions. Model Deployment & Performance Optimization. Deploy computer vision models on edge devices, cloud platforms, and real-time streaming systems. Optimize models for low latency and high accuracy in live cricket broadcasts. Implement A/B testing and continuous monitoring to improve model performance. Camera Calibration & Video Trigonometry. Perform camera calibration for distortion correction and real-world coordinate mapping. Use homography transformation and perspective correction for multi-angle alignment. Apply video trigonometry to calculate player distances, ball speed, angles, and movement trajectories. Work with multi-camera synchronization and stereo vision for depth estimation in cricket analytics. About CompanyAt Lifease Solutions LLP, we believe that design and technology are the perfect blend to solve any problem and bring any idea to life. Lifease Solutions is a leading provider of software solutions and services that help businesses succeed. Based in Noida, India, we are committed to delivering high-quality, innovative solutions that drive value and growth for our customers. Our expertise in the finance, sports, and capital market domains has made us a trusted partner for companies around the globe. We take pride in our ability to turn small projects into big successes, and we are always looking for ways to help our clients maximize their IT investments

We are seeking a 'Computer Vision Engineer' to develop AI-driven video analytics solutions for extracting in-depth cricket data from match footage, live broadcasts, and player tracking systems. This role involves leveraging deep learning, pose estimation, and image processing to analyze player movements, shot selection, bowling mechanics, and match dynamics. Key Responsibilities. Video-Based Cricket Analytics. Develop computer vision models for player tracking, ball trajectory prediction, and shot classification. Extract real-time insights from video streams, including player positions, footwork analysis, and batting/bowling techniques. Implement pose estimation (OpenPose, MediaPipe, DeepLabCut) to analyze player body movements. Use action recognition models to classify batting strokes, bowling variations, and fielding plays. Deep Learning & Image Processing. Apply CNNs, Transformers, YOLO, Mask R-CNN, and Optical Flow for cricket action recognition. Develop segmentation models to differentiate players, umpires, and key match elements (ball, stumps, pitch zones). Use GANs and super-resolution techniques to enhance low-quality video footage. Build OCR (Optical Character Recognition) systems to extract scoreboards and match statistics from live broadcasts. Real-Time Video Processing & Streaming. Implement real-time video processing pipelines using OpenCV, FFmpeg, and GStreamer. Work with multi-angle TV footage and drone feeds to enhance match analysis. Develop low-latency algorithms for real-time ball speed, swing, and spin detection. Data Collection, Annotation & Model Training. Build automated annotation tools for labeling cricket match videos. Train supervised and unsupervised learning models using cricket datasets. Collaborate with sports analysts to validate and refine model predictions. Model Deployment & Performance Optimization. Deploy computer vision models on edge devices, cloud platforms, and real-time streaming systems. Optimize models for low latency and high accuracy in live cricket broadcasts. Implement A/B testing and continuous monitoring to improve model performance. Camera Calibration & Video Trigonometry. Perform camera calibration for distortion correction and real-world coordinate mapping. Use homography transformation and perspective correction for multi-angle alignment. Apply video trigonometry to calculate player distances, ball speed, angles, and movement trajectories. Work with multi-camera synchronization and stereo vision for depth estimation in cricket analytics. About CompanyAt Lifease Solutions LLP, we believe that design and technology are the perfect blend to solve any problem and bring any idea to life. Lifease Solutions is a leading provider of software solutions and services that help businesses succeed. Based in Noida, India, we are committed to delivering high-quality, innovative solutions that drive value and growth for our customers. Our expertise in the finance, sports, and capital market domains has made us a trusted partner for companies around the globe. We take pride in our ability to turn small projects into big successes, and we are always looking for ways to help our clients maximize their IT investments

Python Backend Engineer – Video Processing & Edge Deployment Role Overview You will develop high-performance video processing pipelines optimized for both cloud and edge environments, leveraging GPUs for acceleration and advanced compression for efficiency. Key Responsibilities 1. Build backend systems for video ingestion, processing, and distribution. 2. Implement FFmpeg pipelines for transcoding, compression, and FPS adjustments. 3. Optimize video workflows for H.265 and AV1 codecs. 4. Deploy and manage workloads on Nvidia A16 GPUs and Nvidia Jetson edge devices. 5. Integrate video analytics into backend APIs. 6. Tune video processing performance for edge and low-bandwidth environments. 7. Maintain and troubleshoot Linux-based video processing deployments. Required Skills 1. Strong command of Python and Django. 2. In-depth expertise in FFmpeg for complex video workflows. 3. Experience with GPU-based development (Nvidia A16, Nvidia Jetson). 4. Knowledge of H.265 and AV1 compression algorithms. 5. Understanding of FPS optimization in streaming/video pipelines. 6. Proficiency with Linux systems and backend deployment practices. Location - IIT Delhi Job Types: Full-time, Permanent Pay: ₹50,000.00 - ₹60,000.00 per month Application Question(s): Do you have experience in Video Processing & Edge Deployment? Can you submit relieving letter on the 1st day of joining? Work Location: In person Speak with the employer +91 8638994017

Job Title: Senior Software Engineer I/II- Video Streaming Engineer Department: Technology Reports to: Software Engineering Manager Experience: 3+ years Location: Ahmedabad, India (Remote option Available) Company Introduction Genea was built on a foundation of listening to and serving our commercial real estate customer’s needs starting with our flagship Overtime HVAC product. Over the years, we’ve earned the trust and loyalty of 21 of the top 25 largest commercial real estate companies in the US and continue to prove our value to them every day. Our clients depend on us to develop value-added technology solutions to solve other pain points in their operations. We have grown our product portfolio to serve the complex and expanding needs of property teams. Genea is a family of solutions are designed to improve commercial real estate operations through cutting-edge technology. Revolutionize access control, streamline overtime HVAC, and economize submeter billing. Our host of cloud-based, automated solutions are built to cut costs, reduce admin times, and maximize the tenant experience. Experiencing enormous growth with aggressive expansion plans, Genea is expanding a Software Development and Operations center in India and is looking for dynamic engineering leaders, who can become part of this already successful growth story, and partner in creating a world class team and products. Overview Senior Software Engineer I/II focus on applying the principles of engineering to software development. The role includes analyzing and modifying existing software as well as creating new software and designing, constructing and testing end-user applications that meet user needs — all through software programming languages. Genea is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some technology’s greatest challenges and make an impact on Genea’s end users. A software engineer's approach should be customer-centric and result-driven. Software engineer needs to combine computer science principles with innovative thinking to solve daily software development tasks. Transparency and teamwork and dedication are essential qualities of a software engineer. What You'll Do Write and test product or system development code. Design and implement video streaming and video processing services necessary to support new and existing features. Design metrics that capture the streaming experience and system performance. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Maintain a pulse on emerging technologies and discover hidden opportunities in our environment. Ensure redundancy and resilience of Genea production infrastructure. What We Look For A scrappy, entrepreneurial attitude that gets high-quality projects done quickly. Expert in at least one general-purpose programming language. Node.JS, Python, Rust, or C/C++. REST API development hands on experience. Knowledge of multiple streaming protocols (RTMP, RTSP, RTP, HLS, WebRTC, DASH, etc.) and codecs (AAC, Opus, H264, H265, VP8, VP9, AV1, etc.). Highly proficient in database design, with both relational and NoSQL databases. Comfortable working with AWS, Linux, Docker, continuous deployment workflow, multiple programming languages tech stack. Strong written and verbal communication skills. Self-directed, analytical, and work well in a team environment. Passionate about the Genea product. Experience with multiple multimedia libraries and frameworks: FFmpeg, GStreamer, libvpx, x264, x265, etc. is a plus. Experience on building video pipeline with AI inference for computer vision is a plus. Competencies Diversity - Shows respect and sensitivity for cultural differences; Educates others on the value of diversity; Promotes a harassment-free environment; Builds a diverse workforce. Ethics - Treats people with respect; Keeps commitments; Inspires the trust of others; Works with integrity and ethically; Upholds organizational values. Adaptability - Adapts to changes in the work environment; Manages competing demands; Changes approach or method to best fit the situation; Able to deal with frequent change, delays, or unexpected events. Attendance/Punctuality - Is consistently at work and on time; Ensures work responsibilities are covered when absent; Arrives at meetings and appointments on time. Design - Generates creative solutions; Translates concepts and information into images; Uses feedback to modify designs; Applies design principles; Demonstrates attention to detail. Oral Communication - Speaks clearly and persuasively in positive or negative situations; Listens and gets clarification; Responds well to questions; Demonstrates group presentation skills; Participates in meetings. Problem Solving - Identifies and resolves problems in a timely manner; Gathers and analyzes information skillfully; Develops alternative solutions; Works well in group problem solving situations; Uses reason even when dealing with emotional topics. Professionalism - Approaches others in a tactful manner; Reacts well under pressure; Treats others with respect and consideration regardless of their status or position; Accepts responsibility for own actions; Follows through on commitments. Quality - Demonstrates accuracy and thoroughness; Looks for ways to improve and promote quality; Applies feedback to improve performance; Monitors own work to ensure quality. Quantity - Meets productivity standards; Completes work in timely manner; Strives to increase productivity; Works quickly. Safety and Security - Observes safety and security procedures; Determines appropriate action beyond guidelines; Reports potentially unsafe conditions; Uses equipment and materials properly. Teamwork - Balances team and individual responsibilities; Exhibits objectivity and openness to others' views; Gives and welcomes feedback; Contributes to building a positive team spirit; Puts success of team above own interests; Able to build morale and group commitments to goals and objectives; Supports everyone's efforts to succeed. Technical Skills - Assesses own strengths and weaknesses; Pursues training and development opportunities; Strives to continuously build knowledge and skills; Shares expertise with others. Written Communication - Writes clearly and informatively; Edits work for spelling and grammar; Varies writing style to meet needs; Presents numerical data effectively; Able to read and interpret written information. Perks And Benefits We Offer ✨Work Your Way: Enjoy a flexible working environment that suits your lifestyle. ✨Time Off: 24 days of PTO and 10 holidays to unwind and pursue your passions. ✨Comprehensive Leave Options: Including maternity, paternity, adoption, wedding, and bereavement leaves to support you during important life events. ✨ Health & Safety First: Benefit from family health insurance and personal accident coverage beyond your CTC. ✨Top Workplace Honors: Celebrated as a Top Workplace from 2021 to 2024. ✨Balanced Workweek: Embrace a balanced life with our 5-day work schedule

You will be responsible for AI-assisted development and maintenance of applications utilizing Generative AI and Large Language Models for speech recognition, language translation, and text-to-speech. Additionally, you will evaluate and facilitate the adoption of AI tools for dialogue dubbing, audio description, closed captioning, and subtitling. Collaboration with software engineers, technical, and creative teams will be a key aspect of this role. Ideal candidates should have experience in Python coding, with a preference for knowledge of both local and cloud-based Large Language Model usage. Familiarity with audio and video file formats, as well as tools like FFmpeg, GraphicsMagick, and Gstreamer, can be advantageous. An understanding of API and SDK integrations is also required. The ability to work independently, drive innovation, and a good grasp of movies and their production workflows will be highly beneficial. Previous experience in dialog dubbing, subtitling, closed-captions, and audio descriptions will be considered an added advantage.,

We are building a next-generation live video streaming platform in a compliance-sensitive niche. The platform has been in development for several years, validated through discussions with well-known players in the space, and is nearly launch-ready. This role offers more than a short-term development contract. For the right candidate, this can grow into a lead technical position with the ability to build and manage your own team. Responsibilities Debug, test, and polish the platform for launch readiness Handle both frontend and backend updates Ensure server, security, and compliance stability (NGINX, SSL, Redis, DB) Manage streaming and media integrations (Ant Media, FFMPEG, WebRTC) Lead ongoing technical maintenance and future scaling efforts Requirements Strong experience with Node.js, React, TypeScript, and MongoDB Familiarity with media streaming technologies (WebRTC, Ant Media, FFMPEG) Proficiency in DevOps (Linux, NGINX, PM2, deployments, SSL) Ability to work in a regulated / age-restricted content industry Willingness and eligibility to pass compliance requirements with payment processors Tech Stack Backend/API: Node.js (NestJS), MongoDB, Redis, PM2 Frontend/Admin: React, TypeScript Streaming/Media: Ant Media Server, FFMPEG, WebRTC, WebSockets Server Ops: NGINX, Linux environment, SSL/HTTPS, deployments

Role Overview We are looking for a Software Engineer – Video Pipelines to join our Video AI Platform team. This role is focused on building robust, high-performance video pipelines for both Video-on-Demand (VoD) and Live streaming systems . You will be hands-on in implementing modules for video decoding, encoding, transcoding, and modification , ensuring that our platform delivers low-latency, high-quality video experiences at scale. As a pipeline-builder, you will work closely with senior engineers and architects to bring designs and AI workflows into production-ready video systems , using frameworks like FFmpeg, GStreamer, and GPU-accelerated SDKs . Key Responsibilities Video Pipeline Engineering Build and maintain video ingestion, decoding, encoding, and transcoding pipelines for VoD and Live systems. Integrate adaptive bitrate streaming (HLS, DASH) into delivery pipelines. Work with FFmpeg, GStreamer, NVIDIA Video Codec SDK, and VAAPI to implement efficient video processing components. Ensure pipeline compatibility with multiple codecs and containers (H.264/H.265, AV1, VP9, MP4, MKV, TS). Video Modification Modules Implement frame-accurate transformations such as redaction (face/voice blurring), reframing, auto-zoom, and overlays. Build timeline-aware components that align scene metadata with video streams for precise modifications. Optimize GPU-accelerated filters for real-time and batch processing . Performance & Scalability Profile and tune pipelines for low-latency live streaming and high-throughput VoD workflows . Contribute to scaling strategies for large video libraries and live event workloads. Optimize for cloud cost efficiency while maintaining reliability. Collaboration & Execution Work with senior engineers to translate designs into production components . Collaborate with AI teams to integrate model outputs into video pipelines (e.g., scene tagging, redaction cues). Participate in code reviews, testing, and deployment automation . Qualifications Must-Have 2–5 years of experience in video pipeline or multimedia systems engineering . Strong coding skills in C++ and/or Python . Hands-on experience with FFmpeg, GStreamer, libx264/x265, NVENC/DEC . Understanding of video codecs and streaming protocols (H.264/H.265, VP9, AV1, HLS, DASH, RTMP). Familiarity with GPU acceleration (CUDA, NVENC/DEC, VAAPI, or equivalent). Nice-to-Have Exposure to cloud-native deployments (AWS/GCP/Azure, Docker, Kubernetes). Experience in real-time video editing or transformation pipelines . Familiarity with timeline-based metadata, content retrieval, or AI-driven video modifications . Knowledge of adaptive streaming and edge delivery optimizations .

Must Have: Experience in GStreamer, Ffmpeg, MediaSDK Experience in Modern C++14/17, OOPs, Design patternsJob Title: C++ Video/Audio Streaming Lead (GStreamer) Job Summary We are seeking a highly experienced and driven C++ Video/Audio Streaming Lead with deep expertise in GStreamer, multimedia pipelines, and real-time streaming protocols. As the technical lead, you will architect, design, and lead the development of low-latency video and audio streaming systems for live broadcasting, video conferencing, or surveillance applications. You will also mentor a team of engineers and collaborate closely with product, QA, and DevOps teams. Key Responsibilities Lead the design and development of media streaming applications using C++ and GStreamer. Architect and optimize media pipelines for real-time, low-latency video/audio transmission. Integrate various audio/video codecs, containers, and transport protocols (RTP, RTSP, RTMP, WebRTC). Drive performance profiling, debugging, and tuning of multimedia applications. Collaborate with cross-functional teams on system integration, UI, and backend coordination. Guide and mentor a team of engineers; conduct code reviews and enforce best practices. Stay updated with the latest developments in multimedia frameworks, codecs, and streaming protocols. Participate in technical planning, estimations, and architecture reviews. Mandatory Key Skills GStreamer,Ffmpeg,MediaSDK,C++14,C++17,Modern C++,Object-Oriented Programming,OOPs,Design Patterns,C++*

About the Role We are looking for a Backend/DevOps Engineer to build and maintain high-performance backend services and deployment pipelines for our AI-driven applications. You will design robust APIs, manage real-time data flows, and ensure reliable system deployment and monitoring. This role involves close collaboration with AI/ML, data, and frontend teams to deliver scalable, secure, and production-ready systems. Key Responsibilities Design and implement backend APIs (FastAPI/Flask/Django) for managing data, user profiles, and real-time events. Develop services to handle real-time data streams and ensure low-latency delivery to frontend applications. Integrate ML inference services with databases and business logic. Deploy and orchestrate system components (streaming services, ML models, databases, frontend) on local or cloud infrastructure. Containerize applications with Docker and manage orchestration (Docker Compose / Kubernetes). Set up CI/CD pipelines for smooth deployments and updates. Monitor system performance, uptime, and resource usage across compute environments. Implement authentication, authorization, and data security best practices. Troubleshoot backend and infrastructure issues to ensure smooth operation. Requirements Technical Skills: Strong experience with backend frameworks: FastAPI, Flask, or Django. Solid understanding of REST APIs / WebSockets / gRPC. Good knowledge of databases: PostgreSQL, MySQL, MongoDB, or Redis. Familiarity with real-time data or media streaming protocols (RTSP, WebRTC, HLS, FFmpeg, GStreamer). Hands-on experience with Docker (mandatory), Kubernetes (preferred). Strong Linux deployment skills. Experience in CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins). Knowledge of security, authentication, and access control mechanisms. Nice to Have: Exposure to AI/ML model serving or edge deployments. Experience with monitoring tools (Prometheus, Grafana). Understanding of performance optimization for real-time systems.

Must Have: Experience in GStreamer, Ffmpeg, MediaSDK Experience in Modern C++14/17, OOPs, Design patterns Job Overview: We are seeking an experienced C++ Video/Audio Streaming Lead (GStreamer) to join our team and drive the development of cutting-edge video and audio streaming solutions. In this role, you will lead the design, implementation, and optimization of multimedia streaming systems using GStreamer and C++. The ideal candidate will have strong expertise in multimedia technologies, with a focus on real-time media processing, and will be able to guide the team in delivering high-performance, scalable solutions. Key Responsibilities: Leadership & Collaboration: Lead a team of developers to design, implement, and optimize video and audio streaming solutions using C++ and GStreamer. Collaborate with cross-functional teams to ensure the seamless integration of multimedia components. Streaming System Architecture: Architect and design the system for efficient media streaming, addressing performance, scalability, and reliability. Build robust solutions for video/audio encoding, decoding, and streaming. GStreamer Expertise: Leverage GStreamer to build complex pipelines for media processing, handling video and audio synchronization, compression, streaming protocols, and more. Optimization: Analyze performance bottlenecks in streaming systems and work on optimizing latency, throughput, and resource consumption. Improve system efficiency through profiling and tuning. Innovation & Research: Stay up to date with the latest trends in media streaming, codecs, and protocols (e.g., H.264, H.265, WebRTC, RTMP, etc.) and explore new ways to enhance the functionality and performance of our streaming systems. Code Review & Mentorship: Review code written by team members, providing constructive feedback to ensure high code quality and adherence to best practices. Mentor junior developers and help them grow their technical skills. Troubleshooting: Identify, analyze, and resolve technical issues in the streaming pipeline, ensuring seamless user experiences across multiple platforms and devices. Client & Stakeholder Interaction: Work closely with clients or internal stakeholders to understand requirements, deliver high-quality solutions, and maintain clear communication regarding project progress. Keywords GStreamer,Object-Oriented Programming,OOPs,DesignPatterns,Ffmpeg,MediaSDK,Stakeholder Interaction,Client Interaction,Troubleshooting,C++* Mandatory Key Skills GStreamer,Object-Oriented Programming,OOPs,Design Patterns,Ffmpeg,MediaSDK,Stakeholder Interaction,Client Interaction,Troubleshooting,C++*

DESCRIPTION Prime Video is changing the way millions of customers interact with video content. We're looking for a talented Video Codec Engineer to join our team in developing and optimizing video compression technologies for Prime Video's streaming infrastructure. Key job responsibilities As a Codec Engineer at Prime Video, you'll work on encoder/decoder solutions that impact billions of streaming hours annually. You'll collaborate with team members to optimize codec performance and implement effective video delivery solutions across various platforms. A day in the life • Implement and optimize video compression algorithms • Assist in benchmarking codec performance across different platforms • Collaborate with team members on video quality assessment metrics and encoding algorithms • Contribute to the integration of video processing workloads into the streaming infrastructure • Help implement production-ready solutions • Participate in technical design discussions and code reviews • Write clean, maintainable, and efficient code About the Team: Our mission is to build and operate innovative video streaming technology that provides the best customer-centric streaming experience for VOD and Live globally. We implement technologies that deliver flawless streaming experiences using optimal bandwidth. We foster a supportive, diverse, and inclusive work environment. Internal job description Basic qualifications 1+ years of non-internship professional software development experience 1+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience Experience programming with at least one software programming language Solid understanding of video coding standards (H.264, HEVC, AV1) Preferred qualifications 1+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience Bachelor's degree in computer science or equivalent • Experience with video encoding optimization and profiling tools • Knowledge of video quality assessment and metrics • Familiarity with open-source video encoders and FFmpeg • Experience working on video processing systems • Experience with AI-assisted C/C++ code development • Interest in technical innovation and video coding standards Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. BASIC QUALIFICATIONS 1+ years of non-internship professional software development experience Experience programming with at least one software programming language PREFERRED QUALIFICATIONS Bachelor's degree in computer science or equivalent Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Python Backend Engineer – Video Processing & Edge Deployment Role Overview You will develop high-performance video processing pipelines optimized for both cloud and edge environments, leveraging GPUs for acceleration and advanced compression for efficiency. Key Responsibilities 1. Build backend systems for video ingestion, processing, and distribution. 2. Implement FFmpeg pipelines for transcoding, compression, and FPS adjustments. 3. Optimize video workflows for H.265 and AV1 codecs. 4. Deploy and manage workloads on Nvidia A16 GPUs and Nvidia Jetson edge devices. 5. Integrate video analytics into backend APIs. 6. Tune video processing performance for edge and low-bandwidth environments. 7. Maintain and troubleshoot Linux-based video processing deployments. Required Skills 1. Strong command of Python and Django. 2. In-depth expertise in FFmpeg for complex video workflows. 3. Experience with GPU-based development (Nvidia A16, Nvidia Jetson). 4. Knowledge of H.265 and AV1 compression algorithms. 5. Understanding of FPS optimization in streaming/video pipelines. 6. Proficiency with Linux systems and backend deployment practices. Job Types: Full-time, Permanent Pay: ₹40,000.00 - ₹50,000.00 per month Application Question(s): Do you have experience in Video Processing & Edge Deployment? Can you submit relieving letter on the 1st day of joining? Work Location: In person Speak with the employer +91 8638994017

An AI/ML Engineer designs, develops, and deploys machine learning models and AI solutions. They preprocess data, build algorithms, optimize performance, and integrate models into applications to solve real-world problems using AI and automation.

Job Title: Backend & DevOps Engineer Location : Surat (Onsite) Experience : 2+ Years About the Role We’re looking for a Backend & DevOps Engineer to design, build, and scale real-time infrastructure powering global communication. You’ll work on distributed microservices, low-latency APIs, cloud-native systems, and production-grade DevOps pipelines. Responsibilities Build fault-tolerant services (WebRTC SFU, TURN/STUN, analytics pipelines) Develop RESTful & WebSocket APIs with ultra-low latency Manage cloud infrastructure (AWS/GCP, Kubernetes, Docker) Implement CI/CD pipelines, monitoring, logging, and observability Optimize databases (PostgreSQL, MongoDB, Redis) for scale Requirements 2+ years backend development & DevOps experience Strong knowledge of networking (TCP/IP, DNS, HTTP/2, WebRTC) Hands-on with AWS/GCP, Kubernetes, Terraform, Helm Proficiency in Node.js/Golang/Python Experience with observability tools (Prometheus, Grafana, OpenTelemetry) Linux proficiency & Git-based workflows Nice to Have Experience with SIP, RTP/RTCP, GStreamer, FFmpeg Open-source contributions or SRE practices Tech Stack: Node.js, Golang, Python, PostgreSQL, MongoDB, Redis, Kubernetes, Docker, AWS, GCP, Terraform, Helm, Prometheus, Grafana, OpenTelemetry, WebRTC