1127 Computer Vision Jobs - Page 46

Project Role : Responsible AI Engineer Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Must have skills : Accenture Delivery Architectures (ADA) Summary: As an AI Platform Engineer, you will be responsible for developing applications and systems that utilize AI to improve performance and efficiency. Your typical day will involve working with Accenture Delivery Architectures (ADA) and implementing deep learning, neural networks, chatbots, and natural language processing technologies. Roles & Responsibilities: 1 Lead architecture, design, cross business area projects and development teams for AI applications 2 Identify and explore the framework, NLP tools, VA platform, architecture, or tech stack can be used to create a solution and the connection between the components - Collaborate with cross-functional teams to ensure seamless integration of AI-based applications and systems. - Stay updated with the latest advancements in AI and machine learning technologies, integrating innovative approaches for sustained competitive advantage. Professional & Technical Skills: 1 Knowledge of applications using MEAN stack, Angular JS, Nodejs, Python 2 Understanding of UI technologies like HTML, JavaScript, jQuery 3 Hands on experience on VA tools like Microsoft Bot Framework, Google Dialog flow, RASA, Amazon Lex at least 2 4 Knowledge of: Big Data, LAMP Linux, Apache, MySQL, PHP, DevOps, PaaS a: Custom Frameworks, Spring related technologies, UML, OO Design, Spring Boot, Microservice and JEE Archtiecture b: Cloud AWS,Azure,Google c: Artificial intelligence, Machine Professional Attributes : 1 Be a self starter and a fast learner 2 Possess strong problem solving skills with the ability to methodically analyze and resolve tech challenges 3 Possess strong written, verbal,comm,analyitical,tech,inter personal and presentation skills 4 Excellent exp in interaction and handling of clients Educational Qualification: 15years fulltime of Education - Solid grasp of machine learning algorithms and techniques. - Experience with data visualization tools such as Tableau or Power BI. Additional Information: - The candidate should have a minimum of 3 years of experience in Accenture Delivery Architectures (ADA). - The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful AI-driven solutions.

Management Level Ind & Func AI Decision Science Analyst Location: Bengaluru (Bangalore), Gurugram (Gurgaon), Hyderabad, Chennai. Must-have skills: Programming languages -Python/R, Generative AI, Large Language Models (LLMs), ML libraries such as Scikit-learn, TensorFlow, Torch, Lang Chain, or OpenAI API, RAG Applications. Good to have skills :Big data technologies such as Spark or Hadoop,AI model explainability(XAI),bias detection and AI ethics. Familiarity with Edge AI and deploying models on embedded devices for industrial automation. Experience with Reinforcement Learning (RL) and AI-driven optimization techniques. Job Summary We are looking for a Data Scientist / AI Specialist with 1-3 years of experience to join our team and work on client projects in the Automotive & Industrial sectors. This role will involve leveraging traditional Machine Learning (ML), Generative AI (GenAI), Agentic AI, and Autonomous AI Systems to drive innovation, optimize processes, and enhance decision-making in complex industrial environments. Prior experience in the Auto/Industrial industry is a plus, but we welcome candidates from any domain with a strong analytical mindset and a passion for applying AI to real-world business challenges. Roles & Responsibilities: Develop, deploy and monitor AI/ML models in production environments & enterprise systems, including predictive analytics, anomaly detection, and process optimization for clients. Work with Generative AI models (e.g., GPT, Stable Diffusion, DALLE) for applications such as content generation, automated documentation, code synthesis, and intelligent assistants. Implement Agentic AI systems, including AI-powered automation, self-learning agents, and decision-support systems for industrial applications. Design and build Autonomous AI solutions for tasks like predictive maintenance, supply chain optimization, and robotic process automation (RPA). Work with structured and unstructured data from various sources, including IoT sensors, manufacturing logs, and customer interactions. Optimize and fine-tune LLMs (Large Language Models) for specific business applications, ensuring ethical and explainable AI use. Utilize MOps and AI orchestration tools to streamline model deployment, monitoring, and retraining cycles. Collaborate with cross-functional teams, including engineers, business analysts, and domain experts, to align AI solutions with business objectives. Stay updated with cutting-edge AI research in Generative AI, Autonomous AI, and Multi-Agent Systems. Professional & Technical Skills: 1-3 years of experience in Data Science, Machine Learning, or AI-related roles. Proficiency in Python (preferred) or R, and experience with ML libraries such as Scikit-learn, TensorFlow, Torch, Lang Chain, or OpenAI API. Strong understanding of Generative AI, Large Language Models (LLMs), and their practical applications. Hands-on experience in fine-tuning and deploying foundation models (e.g., OpenAI, Llama, Claude, Gemini, etc.). Experience with Vector Databases (e.g., FAISS, Chroma, Weaviate, Pinecone) for retrieval-augmented generation (RAG) applications. Knowledge of Autonomous AI Agents (e.g., AutoGPT, BabyAGI) and multi-agent orchestration frameworks. Experience working with SQL and NoSQL databases. Familiarity with cloud platforms (AWS, Azure, or GCP) for AI/ML model deployment. Strong problem-solving and analytical thinking abilities. Ability to communicate complex AI concepts to technical and non-technical stakeholders. Bonus:Experience in Automotive, Industrial, or Manufacturing AI applications (e.g., predictive maintenance, quality inspection, digital twins). Additional Information: Bachelor/Master's degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines with an excellent academic record /MBA from top-tier universities. Excellent Communication and Interpersonal Skills. About Our Company | Accenture Qualification Experience: Minimum 1-3 years of relevant Data Science, Machine Learning or AI-related roles., Exposure to Industrial & Automotive Firms or Professional Services. Educational Qualification: Bachelor/Master’s degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines with an excellent academic record or MBA from top-tier universities.