5 Vlm Jobs

As an AI Software Engineer 1 , you will be a key contributor to the design, development, and deployment of AI-driven solutions across both Computer Vision and Large Language Model (LLM) domains. You will be responsible for building deep learning models, writing scalable and maintainable code, and integrating these models into production-grade systems. The role demands a strong foundation in AI/ML theory, proficiency in practical deep learning, and a hands-on approach to software development. You will work closely with cross-functional teams to translate business requirements into working AI solutionsranging from real-time vision systems to NLP pipelines and user-facing interfaces that interact with AI services. We are looking for candidates who can thrive in a technically diverse environment and are enthusiastic about pushing the boundaries of applied AI. Responsibilities: Software Engineering & System Integration Write clean, modular, production-ready code for inference pipelines and AI systems. Develop and maintain interfaces and user-facing components for AI tools and services. Collaborate with backend and platform teams to integrate models into scalable systems. Contribute to CI/CD pipelines, code reviews, testing strategies, and performance monitoring. Deep Learning & AI Model Development: Design, train, and evaluate deep learning models for CV and NLP use cases. Develop end-to-end solutions for: Computer Vision tasks (object detection, segmentation, OCR, activity recognition). Language-related tasks (document parsing, question answering, summarization, RAG pipelines, Building LLM Agents to solve tasks). Optimize model performance using benchmarking and validation against real-world datasets. Data Management & Curation Plan, collect, and preprocess data across modalities (images, video, text). Coordinate with internal teams and vendors for annotation and validation tasks. Define data versioning, quality control, and reproducibility standards. Research & Innovation: Keep up with the latest in deep learning, computer vision, and LLM advancements. Prototype and evaluate new architectures (e.g., ViTs, SAM, LVMs, LLMs like LLaMA, GPT, Mistral). Publish internal documentation and contribute to tech blogs or open-source codebases where appropriate. Requirements: Strong programming skills in Python with hands-on experience using deep learning frameworks (PyTorch/TensorFlow), LLMs frameworks (Autogen/SmolAgents/Langchain) & VLMs 1+ years of experience building AI models in at least one domain (CV or NLP). Proficiency in model lifecycle: training, validation, deployment, and monitoring. Experience working with Git, Docker, and Linux-based environments. Good understanding of ML fundamentals: CNNs, Transformers, LLMs, optimization techniques. Ability to build simple UI components that interface with backend AI services.

As a Senior Data Scientist specializing in Large Language Models (LLMs), Vision Language Models (VLMs), Prompt Engineering, and AI Agents, you will be instrumental in the development of a Proof of Concept (POC) project aimed at automating and enhancing test case creation for user stories. Leveraging cutting-edge AI techniques, such as extracting information from images and documents, automated test case generation, and code analysis for testability, you will play a vital role in advancing this innovative project. Your key responsibilities will include developing and deploying advanced AI/ML solutions utilizing LLMs, VLMs, and prompt engineering to automate the creation and refinement of test cases for user stories. You will also be tasked with extracting and interpreting content from various sources, including images and documents, through the use of Vision Language Models and other relevant tools. Additionally, your role will involve analyzing existing codebases to enhance testability using AI-driven approaches, researching and implementing AI Agent frameworks to optimize testing workflows, and continuously evaluating and improving models and prompts for accuracy, efficiency, and business alignment. To qualify for this position, you should have at least 5 years of experience as a Data Scientist or in a related AI/ML role, with proven expertise in LLMs such as OpenAI and Claude. Hands-on experience with VLMs and prompt engineering, as well as a demonstrated track record of developing and applying AI Agents to automate real-world processes, are essential requirements. You should possess a strong background in automating testing processes using AI/ML techniques, proficiency in Python and common ML frameworks, and experience in extracting structured data from unstructured content like text, images, and documents. Familiarity with code analysis, test case design, and the software development lifecycle, along with excellent problem-solving, communication, and collaboration skills, will be beneficial for excelling in this role.,

Design AI models using LLMs/VLMs to automate test case creation, extract data from text/images, analyze code for testability, optimize prompts, implement AI agents, and enhance testing workflows with accurate, scalable automation. Required Candidate profile Seeking Data Scientist with 5+ yrs in AI/ML, hands-on with LLMs, VLMs, prompt engineering & AI agents. Skilled in Python, automation, data extraction, code analysis & problem-solving.

LLMs, VLMs, Prompt Engineering & AI Agents POC Project,

Key Responsibilities: Collaborate closely with Machine Learning and Engineering teams on advanced data extraction technologies (e.g., no-OCR, VLM-based extraction) Translate business needs into epics and user stories for development teams Align product goals with company strategy in coordination with Product Management Maintain a well-prioritized product backlog based on business value Work with stakeholders and data analysts to ensure data-driven product decisions Track product progress, performance, and deliverables across sprints Communicate effectively with globally distributed teams and stakeholders Stay updated with agile practices, ML/AI trends, and industry standards Required Experience & Qualifications: 3+ years as a Product Owner in an agile environment Familiarity with AI/ML patterns (e.g., VLM, LLMs) and experience working with ML-driven teams Technical aptitude with a fast-learning mindset Strong data orientation and analytical thinking Agile and/or SAFe framework knowledge Excellent attention to detail and communication skills Comfortable working in international, cross-functional environments Proficient in spoken and written English Nice to Have: Exposure to Regulatory Compliance Product Marketing experience Strong cross-cultural communication Advanced data analysis capabilities Knowledge of Biometric Security Standards