2 Vipergpt Jobs

About The Role Were building an agentic AI platform that turns one line of text and a video feed into end-to-end, real-time computer-vision solutionsthink semantic video search, object / action recognition, and task-oriented visual agents deployable with a single click As a Gen AI ML Engineer, youll architect the core vision & multimodal-reasoning stack and pave the road from prototype to production. Roles And Responsibilities Semantic video search Ship a pipeline that allows users to type show every forklift near aisle 5 in the last 30 minutes and get keyed-off clips in Wire embeddings to a hybrid FAISS/HNSW index; surface results through a simple REST & React playground. Create agentic pipelines Chain vision language models and zero/few-shot vision models with LLM planners (Gemini, GPT-4o, AutoGen, etc.) so a single prompt becomes a multi-step perception workflow. Profile and accelerate inference (TensorRT, ONNX, quantization, batching) to meet latency / throughput targets on GPU and CPU fleets. Rapid prototyping loops Run weekly paper-to-prototype spikes: reproduce a fresh arXiv idea, benchmark, and decide go/no-go in Hand successful python scripts & checkpoints to MLOps for productionizationno plumbing marathons. Data & Evaluation Spin up scalable pipelines for video ingestion, labeling (active learning, weak supervision), experiment tracking, and continuous evaluation. Collaborate & Lead Partner with product and ML Ops engineers; set research direction, mentor future hires, and establish best practices. Must-have Skill Set 13 years deep-learning research experience (internships & grad work count). Fluency in Python + PyTorch; comfortable hacking large vision/LLM repos. Proof you ship ideasfirst-author paper, OSS repo, Kaggle medal, or faithful reproduction of a cutting-edge model. Hands-on with LLM prompting/fine-tuning and at least one agent framework. Able to turn fuzzy product asks into measurable experiments and explain results clearly. Bonus Cred Large-scale video retrieval or temporal grounding experience. Prior work building agentic-AI pipelines that combine perception models with LLM reasoning. Open-source contributions to GenAI/vision libs (OpenCLIP, Vid2Seq, ViperGPT, etc.). What can you expect? Ability to shape the future of manufacturing by leveraging best-in-class AI and software; we are a unique organization with niche skill set that you would also develop while working with us World class work culture, coaching and development Mentoring from highly experienced leadership from world class companies (refer to Ripik.AI website for details) International exposure Work Location NOIDA (Work from Office)

About the role: Were building an agentic AI platform that turns one line of text and a video feed into end-to-end, real-time computer-vision solutionsthink semantic video search, object / action recognition, and task-oriented visual agents deployable with a single click. As a Gen AI ML Engineer, youll architect the core vision & multimodal-reasoning stack and pave the road from prototype to production. Roles and Responsibilities: Semantic video search Ship a pipeline that allows users to type show every forklift near aisle 5 in the last 30 minutes and get keyed-off clips in 1 s. Wire embeddings to a hybrid FAISS/HNSW index; surface results through a simple REST & React playground. Create agentic pipelines Chain vision language models and zero/few-shot vision models with LLM planners (Gemini, GPT-4o, AutoGen, etc.) so a single prompt becomes a multi-step perception workflow. Profile and accelerate inference (TensorRT, ONNX, quantization, batching) to meet latency / throughput targets on GPU and CPU fleets. Rapid prototyping loops Run weekly paper-to-prototype spikes: reproduce a fresh arXiv idea, benchmark, and decide go/no-go in 5 days. Hand successful python scripts & checkpoints to MLOps for productionizationno plumbing marathons. Data & Evaluation Spin up scalable pipelines for video ingestion, labeling (active learning, weak supervision), experiment tracking, and continuous evaluation. Collaborate & Lead Partner with product and ML Ops engineers; set research direction, mentor future hires, and establish best practices. Must-have skill set: 13 years deep-learning research experience (internships & grad work count). Fluency in Python + PyTorch; comfortable hacking large vision/LLM repos. Proof you ship ideasfirst-author paper, OSS repo, Kaggle medal, or faithful reproduction of a cutting-edge model. Hands-on with LLM prompting/fine-tuning and at least one agent framework. Able to turn fuzzy product asks into measurable experiments and explain results clearly. Bonus cred: Large-scale video retrieval or temporal grounding experience. Prior work building agentic-AI pipelines that combine perception models with LLM reasoning. Open-source contributions to GenAI/vision libs (OpenCLIP, Vid2Seq, ViperGPT, etc.). What can you expect? Ability to shape the future of manufacturing by leveraging best-in-class AI and software; we are a unique organization with niche skill set that you would also develop while working with us World class work culture, coaching and development Mentoring from highly experienced leadership from world class companies (refer to Ripik.AI website for details) International exposure