11 Gpt4 Jobs

As an Applied AI Engineer at DevRev, your role is crucial in ensuring that customers derive optimal value from the DevRev platform. You will collaborate closely with the pre- and post-sales Customer Experience team to develop solutions over the core platform through applications written in TypeScript, JavaScript, Python, and more. Your creativity and expertise will be instrumental in shaping how AI, analytics, and workflows are integrated into customers" processes. Your primary objectives in this role will involve designing, developing, and implementing integrations, automations, and customizations to seamlessly integrate DevRev with customers" tech stack and workflows, thereby ensuring successful customer engagements. You will leverage AI in innovative ways to address customer challenges, including the application of Generative AI techniques such as prompt engineering for large language models (LLMs) to enhance the AI agent experience. Additionally, you will focus on fine-tuning semantic search engines for improved search accuracy, conducting data analysis, writing SQL queries, and creating dashboards to drive decision-making based on insights. Communication plays a key role in your responsibilities, as you will proactively engage with all key stakeholders, including Customers, Engineering, Product, Customer Success & Support, Revenue, Marketing, etc., to maintain constant feedback loops. Your ability to learn new tools and guide customers through critical workflows, such as integrating with code repositories, will be essential in delivering exceptional customer experiences. The ideal candidate for this role should possess a degree in software engineering or equivalent professional experience, with hands-on coding skills in TypeScript/JavaScript, Python, APIs, Webhooks, and SQL. Familiarity with Generative AI technologies like GPT-4, prompt engineering, and fine-tuning, as well as knowledge of vector databases and data embeddings, will be advantageous. Strong written and verbal communication skills in English, a result-oriented work style, a continuous learning mindset, and a passion for challenging work that demands high energy and performance are qualities that will contribute to your success in this role. At DevRev, our culture is founded on the principles of being hungry, humble, honest, and acting with heart. Our vision is centered on supporting the development of the world's most customer-centric companies, while our mission revolves around leveraging design, data engineering, and machine intelligence to empower engineers to better serve their customers. Join us at DevRev and be part of a team that is dedicated to driving innovation and helping companies thrive in the dynamic landscape of AI-driven SaaS.,

As an AI Systems Architect / LLM-Native Generalist at SBEK (Sab-Ek), a jewelry brand rooted in service, myth, and light, you will play a crucial role in shaping the integration of storytelling, AI systems, product design, and social impact. Your primary responsibility will be to design, test, and implement advanced AI tools and infrastructure that will enhance our brand and operational efficiency. Your expertise in working with various no-code and low-code platforms, modern LLM tools, and the evolving AI agent ecosystem will be essential for this role. You should possess a proactive approach to experimentation, quick learning abilities, and a track record of reliable execution. Key Responsibilities: - Design and manage internal AI workflows using platforms such as Supabase, Lovable, Cursor, N8n, and Airtable - Evaluate and utilize tools like Lang Chain, GPT-4, Claude, Mistral, Flowise, Vercel AI SDK, and other RAG frameworks - Collaborate with the founder to create prototypes using a combination of no-code solutions, automation, and API logic - Stay updated on the latest LLM tools, open-source projects, and AI-enabled platforms - Develop simple documentation and system maps to ensure team alignment Required Skills & Experience: - Proficiency in various AI-native tools such as Lovable, Cursor, N8n, Supabase, Zapier, Vercel, Firebase, Flowise, Make, and Lang Chain - Understanding of backend logic, user roles, API integrations, and real-time data processing - Ability to implement secure authentication systems and subscription workflows independently - Strong problem-solving capabilities, creativity, and a knack for turning abstract ideas into functional solutions - Familiarity with prompt engineering, vector databases, and the basics of model selection - Willingness to iterate, experiment, and deliver solutions efficiently Bonus Qualifications: - Experience in developing custom GPT models or personal AI assistants - Demonstrated ability to integrate multiple tools or models in innovative ways - Interest in leveraging AI for social good initiatives - Track record of deploying successful applications or automations - Excellent communication skills and the ability to articulate complex concepts clearly This role is ideal for individuals who already possess a deep understanding of AI concepts and technologies and are eager to further explore the field. Please note that we are seeking candidates who are already proficient in AI tools and platforms, as we are not offering training from scratch. If you are actively engaged in exploring AI tools, utilizing platforms like Lovable and Cursor, and envisioning their potential applications in products and businesses, we encourage you to apply for this exciting opportunity at SBEK.,

We are seeking a talented and enthusiastic AI Engineer to be a part of our team. As an AI Engineer, you will be responsible for the design, development, and deployment of AI models and algorithms to address intricate challenges and drive business value. The ideal candidate will possess a solid foundation in machine learning, deep learning, and data science, coupled with exceptional programming abilities. Your main responsibilities will include designing, developing, and implementing AI models and algorithms to solve real-world issues. You will collaborate with diverse teams to comprehend business requirements and transform them into technical solutions. Data analysis and preprocessing will be crucial to ensure high-quality input for AI models. Furthermore, you will be involved in training, testing, and validating AI models to guarantee accuracy and performance, along with deploying these models into production environments and monitoring their performance. Continuous enhancement of AI models by integrating new data and feedback will also be part of your role. It is essential to stay updated with the latest advancements in AI and machine learning technologies. Documenting AI models, processes, and outcomes for knowledge sharing and future reference will be necessary. Additionally, participation in code reviews and providing constructive feedback to peers will be expected. The ideal candidate should have prior experience as an AI Engineer, Machine Learning Engineer, or a similar role. Proficiency in machine learning algorithms, deep learning frameworks, statistical methods, and programming languages like Python, R, or Java is required. Familiarity with LLMs such as GPT-4, Llama-2, NLP, RAG, data preprocessing, feature engineering, and data visualization techniques is essential. Experience with machine learning libraries and frameworks like TensorFlow, Keras, PyTorch, Scikit-learn, vector databases such as Pinecone and ChromaDB, cloud platforms like AWS, Google Cloud, Azure, and version control systems like Git is preferred. Strong problem-solving skills, attention to detail, excellent communication, and collaboration skills are also vital. The ideal candidate should have 2-6 years of experience and a Bachelor's or Master's degree in computer science, artificial intelligence, machine learning, or a related field.,

As an AI Automation Specialist, you will play a crucial role in enhancing efficiency, personalization, and scalability in eCommerce store operations and marketing by implementing AI-driven automation solutions. You will be responsible for designing, implementing, and optimizing automated workflows across various platforms such as Shopify, Klaviyo, Zapier, ManyChat, Make.com, and integrating AI tools like ChatGPT, Midjourney, and custom bots to streamline tasks, improve conversion rates, and elevate client performance. Your responsibilities will include setting up AI-based customer support and chatbots utilizing platforms such as ManyChat, Tidio, and Intercom integrated with GPT technology. You will automate processes like abandoned cart flows, welcome series, and post-purchase email journeys using Klaviyo or Omnisend. Additionally, you will leverage tools like Zapier, Make.com, or custom APIs to establish seamless connections between platforms such as Shopify, CRM systems, and advertising networks. Furthermore, you will be tasked with developing AI tools for generating product recommendations, reviews, and auto content creation. Your role will also involve implementing predictive analytics, AI-generated ad creatives, and copy to enhance marketing strategies. Integration of GPT or Claude-powered backend assistants for client stores will be part of your responsibilities. To excel in this role, you are required to possess a strong understanding of automation tools such as Zapier, Make, Pabbly, and Activepieces. Experience with eCommerce tools including Shopify, Klaviyo, Gorgias, and ManyChat is essential. Familiarity with GPT-4, Claude, DALLE, or Midjourney integrations is preferred. Knowledge of APIs, specifically REST and Webhooks, would be advantageous. Your creative problem-solving skills and ability to implement fast, scalable automation solutions will be key to success in this position.,

Prompt Engineer We are looking for a Prompt Engineer to join our delivery team and take ownership of prompt design, optimization, and context structuring in out Agentic AI Projects. You will work closely with data engineers, frontend/backend developers, and domain SMEs to ensure the AI produces accurate, relevant, and useful outputs in response to financial queries. Key Responsibilities: Design, develop, and iteratively improve prompts for financial query handling, chart generation, and narrative explanation. Structure context for LLM calls using metadata, schema details, cube hierarchies, and user query history. Optimize prompt formats for different use cases: summaries, comparative analysis, simulations, and forecast scenarios. Collaborate with SMEs to translate business questions into structured prompt frameworks and test sets. Build and test prompt pipelines using RAG techniques with financial datasets and document sources. Monitor LLM outputs for accuracy, completeness, and business alignment; propose corrections and enhancements. Work with the development team to integrate prompt logic into API endpoints and UI workflows.. Requirements: 2+ years of experience in prompt engineering, NLP, or working with LLMs (e.g., GPT-4, Azure OpenAI). Strong understanding of prompt composition strategies (system prompts, few-shot, chain-of-thought, etc.). Experience working with financial or business data (KPIs, variance reports, financial statements, etc.). Familiarity with tools like LangChain, Azure AI Foundry, or custom RAG implementations. Comfortable reading data schemas (Power BI datasets, OLAP cubes) and using them to craft contextual prompts. Basic knowledge of Python, JSON, and APIs. Excellent communication skills and attention to detail. Ability to collaborate cross-functionally with engineers and finance SMEs. Excellent communication skills Good to have: Experience with Azure cloud services Experience with Azure Foundry & Prompt flow Location: Bangalore

As an AI Research Scientist, your role will involve developing the overarching technical vision for AI systems that cater to both current and future business needs. You will be responsible for architecting end-to-end AI applications, ensuring seamless integration with legacy systems, enterprise data platforms, and microservices. Collaborating closely with business analysts and domain experts, you will translate business objectives into technical requirements and AI-driven solutions. Working in partnership with product management, you will design agile project roadmaps that align technical strategy with market needs. Additionally, you will coordinate with data engineering teams to guarantee smooth data flows, quality, and governance across various data sources. Your responsibilities will also include leading the design of reference architectures, roadmaps, and best practices for AI applications. You will evaluate emerging technologies and methodologies, recommending innovations that can be integrated into the organizational strategy. Identifying and defining system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems will be crucial aspects of your role. Leveraging containerization (Docker, Kubernetes) and cloud services, you will streamline the deployment and scaling of AI systems. Implementing robust versioning, rollback, and monitoring mechanisms to ensure system stability, reliability, and performance will also be part of your duties. Project management will be a key component of your role, overseeing the planning, execution, and delivery of AI and ML applications within budget and timeline constraints. You will be responsible for the entire lifecycle of AI application development, from conceptualization and design to development, testing, deployment, and post-production optimization. Enforcing security best practices throughout each phase of development, with a focus on data privacy, user security, and risk mitigation, will be essential. Furthermore, providing mentorship to engineering teams and fostering a culture of continuous learning will play a significant role in your responsibilities. In terms of mandatory technical and functional skills, you should possess a strong background in working with or developing agents using langgraph, autogen, and CrewAI. Proficiency in Python, along with robust knowledge of machine learning libraries such as TensorFlow, PyTorch, and Keras, is required. You should also have proven experience with cloud computing platforms (AWS, Azure, Google Cloud Platform) for building and deploying scalable AI solutions. Hands-on skills with containerization (Docker), orchestration frameworks (Kubernetes), and related DevOps tools like Jenkins and GitLab CI/CD are necessary. Experience using Infrastructure as Code (IaC) tools such as Terraform or CloudFormation to automate cloud deployments is essential. Additionally, proficiency in SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) and expertise in designing distributed systems, RESTful APIs, GraphQL integrations, and microservices architecture are vital for this role. Knowledge of event-driven architectures and message brokers (e.g., RabbitMQ, Apache Kafka) is also required to support robust inter-system communications. Preferred technical and functional skills include experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) to ensure system reliability and operational performance. Familiarity with cutting-edge libraries such as Hugging Face Transformers, OpenAI's API integrations, and other domain-specific tools is advantageous. Experience in large-scale deployment of ML projects, along with a good understanding of DevOps/MLOps/LLM Ops and training and fine-tuning of Large Language Models (SLMs) like PALM2, GPT4, LLAMA, etc., is beneficial. Key behavioral attributes for this role include the ability to mentor junior developers, take ownership of project deliverables, contribute to risk mitigation, and understand business objectives and functions to support data needs. If you have a Bachelor's or Master's degree in Computer Science, certifications in cloud technologies (AWS, Azure, GCP), and TOGAF certification (good to have), along with 11 to 14 years of relevant work experience, this role might be the perfect fit for you.,

As a Python Developer within our Information Technology department, your primary responsibility will be to leverage your expertise in Artificial Intelligence (AI), Machine Learning (ML), and Generative AI. We are seeking a candidate who possesses hands-on experience with GPT-4, transformer models, and deep learning frameworks, along with a profound comprehension of model fine-tuning, deployment, and inference. Your key responsibilities will include designing, developing, and maintaining Python applications that are specifically tailored towards AI/ML and generative AI. You will also be involved in building and refining transformer-based models such as GPT, BERT, and T5 for various NLP and generative tasks. Working with extensive datasets for training and evaluation purposes will be a crucial aspect of your role. Moreover, you will be tasked with implementing model inference pipelines and scalable APIs utilizing FastAPI, Flask, or similar technologies. Collaborating closely with data scientists and ML engineers will be essential in creating end-to-end AI solutions. Staying updated with the latest research and advancements in the realms of generative AI and ML is imperative for this position. From a technical standpoint, you should demonstrate a strong proficiency in Python and its relevant libraries like NumPy, Pandas, and Scikit-learn. With at least 7+ years of experience in AI/ML development, hands-on familiarity with transformer-based models, particularly GPT-4, LLMs, or diffusion models, is required. Experience with frameworks like Hugging Face Transformers, OpenAI API, TensorFlow, PyTorch, or JAX is highly desirable. Additionally, expertise in deploying models using Docker, Kubernetes, or cloud platforms like AWS, GCP, or Azure will be advantageous. Having a knack for problem-solving and algorithmic thinking is crucial for this role. Familiarity with prompt engineering, fine-tuning, and reinforcement learning with human feedback (RLHF) would be a valuable asset. Any contributions to open-source AI/ML projects, experience with vector databases, building AI chatbots, copilots, or creative content generators, and knowledge of MLOps and model monitoring will be considered as added advantages. In terms of educational qualifications, a Bachelor's degree in Science (B.Sc), Technology (B.Tech), or Computer Applications (BCA) is required. A Master's degree in Science (M.Sc), Technology (M.Tech), or Computer Applications (MCA) would be an added benefit for this role.,

As an AI Azure Architect, your primary responsibility will be to develop the technical vision for AI systems that cater to the existing and future business requirements. This involves architecting end-to-end AI applications, ensuring seamless integration with legacy systems, enterprise data platforms, and microservices. Collaborating closely with business analysts and domain experts, you will translate business objectives into technical requirements and AI-driven solutions. Additionally, you will partner with product management to design agile project roadmaps aligning technical strategies with market needs. Coordinating with data engineering teams is essential to ensure smooth data flows, quality, and governance across different data sources. Your role will also involve leading the design of reference architectures, roadmaps, and best practices for AI applications. Evaluating emerging technologies and methodologies to recommend suitable innovations for integration into the organizational strategy is a crucial aspect of your responsibilities. You will be required to identify and define system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems. Leveraging containerization (Docker, Kubernetes) and cloud services will streamline the deployment and scaling of AI systems. Implementation of robust versioning, rollback, and monitoring mechanisms to ensure system stability, reliability, and performance will be part of your duties. Moreover, you will oversee the planning, execution, and delivery of AI and ML applications, ensuring they are completed within budget and timeline constraints. Managing project goals, allocating resources, and mitigating risks will fall under your project management responsibilities. You will be responsible for overseeing the complete lifecycle of AI application developmentfrom conceptualization and design to development, testing, deployment, and post-production optimization. Emphasizing security best practices during each development phase, focusing on data privacy, user security, and risk mitigation, is crucial. In addition to technical skills, the ideal candidate for this role should possess key behavioral attributes such as the ability to mentor junior developers, take ownership of project deliverables, and contribute towards risk mitigation. Understanding business objectives and functions to support data needs is also essential. Mandatory technical skills for this position include a strong background in working with agents using langgraph, autogen, and CrewAI. Proficiency in Python, along with knowledge of machine learning libraries like TensorFlow, PyTorch, and Keras, is required. Experience with cloud computing platforms (AWS, Azure, Google Cloud Platform), containerization tools (Docker), orchestration frameworks (Kubernetes), and DevOps tools (Jenkins, GitLab CI/CD) is essential. Proficiency in SQL and NoSQL databases, designing distributed systems, RESTful APIs, GraphQL integrations, and event-driven architectures are also necessary. Preferred technical skills include experience with monitoring and logging tools, cutting-edge libraries like Hugging Face Transformers, and large-scale deployment of ML projects. Training and fine-tuning of Large Language Models (LLMs) is an added advantage. Educational qualifications for this role include a Bachelor's/Master's degree in Computer Science, along with certifications in Cloud technologies (AWS, Azure, GCP) and TOGAF certification. The ideal candidate should have 11 to 14 years of relevant work experience in this field.,

The ideal candidate for this position will be responsible for understanding business problems and formulating analytical solutions. You will apply machine learning, data mining, and text mining techniques to develop scalable solutions for various business challenges. You will also be involved in speech to text translation for Video/Audio NLP Analysis and generative AI application for Market Research data. Additionally, you will solve problems using advanced AI techniques, including GenAI methods, by designing NLP/LLM/GenAI applications/products with robust coding practices. Experience in LLM models like PaLM, GPT4, and Mistral is preferred. You will be expected to train, tune, validate, and monitor predictive models, as well as analyze and extract relevant information from large amounts of historical business data in structured and unstructured formats. Furthermore, you will establish scalable, efficient, automated processes for large-scale data analyses and develop and deploy Data Science models on cloud platforms like GCP, Azure, and AWS. Working with large, complex data sets using tools such as SQL, Google Cloud Services, Hadoop, Alteryx, and Python will be part of your daily responsibilities. Preferred qualifications for this role include 2+ years of experience in market research, data mining, statistical analysis, Gen AI, modeling, deep learning, optimization, or similar analytics. Additionally, having 2+ years of work experience with Python, SQL, and/or visualization/dashboard tools like Tableau, PowerBI, or Qliksense is desired. Comfort with working in an environment where problems are not always well-defined and the ability to effectively advocate technical solutions to various audiences are also important. Candidates with 3-4 years of industry experience and a Bachelor's or Master's degree in a quantitative field such as Statistics, Computer Science, Economics, Mathematics, Data Science, or Operations Research are required for this position. You should have 3+ years of experience using SQL for acquiring and transforming data, as well as experience with real-world data, data cleaning, data collection, or other data wrangling challenges. Knowledge in fundamental text data processing and excellent problem-solving, communication, and data presentation skills are essential. Moreover, you should be flexible to work on multiple projects/domains/tools, possess collaborative skills to work with business teams, and be comfortable coding in Tensorflow and/or Pytorch, Numpy, and Pandas, Scikit-learn. Experience with open-source NLP modules like SpaCy, HuggingFace, TorchText, fastai.text, and others is beneficial. Proven quantitative modeling and statistical analysis skills, along with a proactive and inquisitive attitude towards learning new tools and techniques, are highly valued.,

We're looking for a skilled Python Developer with strong hands-on experience integrting any modern LLMs such as OpenAI , Claude , Amazon Titan , Gemini , etc. The ideal candidate will have deep experience in building and fine-tuning LLM-powered features.

Role & responsibilities Develop and implement generative AI solutions, leveraging Microsofts cutting end technologies Work closely with cross-functional teams to prototype generative AI solutions and validate business needs and requirements Collaborate closely with stakeholders to align solutions to business needs Consider production deployment requirements as part of solution design Optimize solutions using the most appropriate models and design for cost effectiveness, efficiency, and accuracy Collaborate with data scientists to integrate machine learning models into proposed solutions Preferred candidate profile Skills: Proficiency in Python and C# (especially in Azure-integrated environments) Experience with or exposure to the following Microsoft technologies: Azure AI Studio Azure OpenAI Services Azure AI Search (Cognitive Search) Fabric Copilot Studio Cognetive Services (Language, Speech, Vision APIs) Experience with foundation models such as GPT3.5 Turbo, GPT 4.0, etc and RAG (retrieval augmented generation) using Azure AI Search or other vector databases Event Driven Architectures and cloud services that support them (e.g., Azure Service Bus, Kafka, Azure Event Grid, RabbitMQ, etc.) Cloud Software development including coding, testing, and debugging on the Microsoft technology stack including .NET (Core/6+), Entity Framework, C#, Typescript, MS SQL, Azure SQL, CosmosDB Prompt flow and evaluation flow for testing/validating models, and exposure to Azure Content Safety is considered an asset Experience with the following is considered an asset: Data modeling and analytics Azure SQL Azure Synapse Azure Data Bricks Azure Data Factory Certifications : 1. Microsoft Certified: Azure AI Engineer Associate (AI-102) with focus on NLP, vision, responsible AI, Azure Cognitive Services, Azure OpenAI