87 Llama Jobs - Page 2

As an AI Application Engineer at SAP, you will play a pivotal role in designing and constructing AI applications by harnessing the power of machine learning and deep learning techniques. Your primary responsibility will involve collaborating with diverse teams to comprehend business objectives and translating them into precise technical requirements. You will be instrumental in developing data analysis prompts and conducting model training to ensure exceptional accuracy and performance levels. Additionally, your role will encompass the optimization of existing AI models and applications to enhance efficiency. Troubleshooting technical issues during development or deployment phases will also be part of your routine tasks. It is paramount that you stay abreast of the latest trends in AI to contribute innovative ideas to ongoing projects. Your tenure at SAP, a global leader in enterprise software, will expose you to a dynamic and innovative team environment. The organization is currently embarking on an AI-first journey, integrating artificial intelligence into every facet of product development. You will work on cutting-edge AI projects, including enhancing chatbots to efficiently handle customer inquiries across various industries. Moreover, you will have the opportunity to contribute to groundbreaking initiatives, particularly in the realm of AI agents. SAP fosters a collaborative culture that thrives on knowledge sharing, offering ample prospects for your professional growth in enterprise AI development. Join our vibrant team and play a pivotal role in shaping the future landscape of AI applications. **Duties and Responsibilities:** - Lead the complete lifecycle development of AI applications, from inception to deployment, leveraging hands-on expertise to ensure seamless functionality and optimal performance. - Collaborate with cross-functional teams to grasp business requirements and translate them into effective technical solutions. - Apply profound knowledge of prominent large language models like GPT and Llama, along with other relevant AI technologies, to drive innovation in AI application development. - Conduct thorough testing and meticulous optimization of AI applications, encompassing performance testing, accuracy validation, and resolution of identified issues to enhance overall quality and efficiency. - Oversee the data pipeline for AI model training, including data collection, cleaning, preprocessing, and ensuring data integrity to support accurate model training. - Integrate AI features into existing systems and architectures. - Stay abreast of industry trends, emerging technologies, and best practices in the field of AI. - Provide continuous support and maintenance for deployed AI applications, monitoring performance, addressing user feedback, and implementing necessary updates to ensure optimal functionality. **What you bring:** - Bachelor's degree or higher in a relevant field. - 4-6 years of hands-on experience in AI-related domains. - Demonstrated experience in AI product development. - Proficiency in writing prompts. - Experience in Agentic AI, Knowledge Graph, and other related areas. - Proficient in large language model principles. - Strong programming skills. - Excellent problem-solving abilities. - Familiarity with data processing and analysis. - Knowledge of cloud computing platforms such as AWS and Azure. - Eagerness to learn new AI technologies and a strong aptitude for learning. - Strong teamwork and communication skills. - Excellent English communication skills. Join the team at SAP and be part of a transformative journey towards leveraging AI to drive business success and innovation. As we continue to pioneer the development of AI applications, your contributions will play a pivotal role in shaping the future landscape of enterprise AI. Embrace this opportunity to grow professionally in a collaborative and forward-thinking environment, where your skills and expertise will be valued and nurtured.,

As a Senior Software Engineer at Wells Fargo, you will take the lead in driving complex technology initiatives that have a companywide impact. You will be instrumental in setting standards and best practices for engineering large-scale technology solutions across various technology disciplines. Your responsibilities will include designing, coding, testing, debugging, and documenting projects and programs. Your role will involve reviewing and analyzing complex technology solutions to address tactical and strategic business objectives within the enterprise technological environment. You will be making critical decisions in developing best practices for engineering solutions, leveraging industry standards and new technologies to guide and influence the technology team towards meeting deliverables and driving new initiatives. Collaboration and consultation with technical experts, senior technology team members, and external industry groups will be key to resolving technical challenges and achieving set goals. Moreover, you will lead projects, teams, or serve as a mentor to peers. The job requires a minimum of 5 years of Software Engineering experience or an equivalent combination of work experience, training, military service, or education. Desired qualifications for this role include strong Python programming skills, expertise in RPA tools like UI Path, proficiency in Workflow automation tools such as Power Platform, and a minimum of 2 years of hands-on experience in AI/ML and Gen AI. Additionally, experience in LLMs (Gemini, GPT, or Llama), prompt engineering, model fine-tuning, and AI/Gen AI certifications from premier institutions are preferred. Hands-on experience in ML ops tools like MLflow and CICD pipelines is also valued. In terms of job expectations, you will be involved in designing and developing AI-driven automation solutions, implementing AI automation to improve process automation, developing and maintaining automation, BOTS, and AI-based workflows, integrating AI automation with existing applications, API's and databases, and building and optimizing prompt engineering workflows. Furthermore, you will fine-tune and integrate pre-trained models for specific use cases and deploy models in production using robust ML ops practices. If you believe you are the ideal candidate for this role, we encourage you to apply before the job posting ends on 23rd July 2025. Wells Fargo is committed to providing equal opportunities, and we welcome applications from all qualified candidates, including women, persons with disabilities, aboriginal peoples, and visible minorities. If you require any accommodations during the recruitment process due to a disability, please reach out to Disability Inclusion at Wells Fargo.,

We are hiring experienced AI Engineers for a full-time, 6-month on-premise role in Bengaluru (Electronic City) The role involves working on AI/ML solutions with open-source LLMs such as LLaMA, DeepSeek, and Mistral Strong Python programming skills, including data structures and algorithmic problem-solving, are essential Candidates must be comfortable deploying models on-premise and solving system-level challenges in Python Fine-tuning of LLMs, performance optimization, and working in Linux environments are desirable The role is hands-on and requires excellent analytical thinking and full-time office presence

Position Summary: We are looking for a visionary and deeply experienced Principal Data Scientist with 15+ years of experience in advanced data science and machine learning, and proven leadership in Generative AI (GenAI) . You will be responsible for conceptualizing and delivering high-impact AI solutions using large language models (LLMs), diffusion models, and other GenAI techniques, while also mentoring teams and influencing AI strategy across the organization. Key Responsibilities: AI Strategy & Leadership Drive the strategic direction of Generative AI initiatives aligned with business objectives. Evaluate, prototype, and implement GenAI technologies (e.g., GPT, Claude, LLaMA, Stable Diffusion). Serve as an AI thought leader, influencing executive decision-making and shaping the company's AI roadmap. Model Development & Deployment Design and build advanced GenAI solutions, including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG). Lead the end-to-end development and deployment of ML/GenAI models into production environments. Develop scalable architectures for serving LLMs and other foundation models. Research & Innovation Stay at the forefront of GenAI advancements by engaging with academic research, open-source communities, and industry forums. Contribute to internal AI research initiatives and explore novel applications of generative models. Publish whitepapers, patents, or present at top AI conferences as applicable. Cross-functional Collaboration Collaborate closely with data engineering, product, design, and business stakeholders to translate complex needs into AI-powered solutions. Educate teams on the capabilities, limitations, and ethical considerations of GenAI. Mentorship & Governance Mentor and coach junior and mid-level data scientists. Establish best practices for model governance, ethical AI, bias mitigation, and model explainability. Define frameworks for AI evaluation, monitoring, and lifecycle management. Required Qualifications: 15+ years of experience in data science, machine learning, or artificial intelligence. Demonstrated expertise in building and deploying GenAI solutions, particularly with large-scale language and vision models. Deep knowledge of ML/DL frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain). Strong programming skills in Python and experience with cloud-based ML platforms (AWS SageMaker, Azure ML, Vertex AI). Strong grounding in statistics, probability, optimization, and deep learning theory. Experience working with multimodal data (text, image, audio, video) and advanced NLP/NLG techniques. Preferred Qualifications: Ph.D. or Master's in Computer Science, Machine Learning, Mathematics, or related field. Experience with enterprise applications of GenAI (e.g., content generation, synthetic data, co-pilots, document understanding). Familiarity with MLOps and AI model lifecycle management in production environments. Knowledge of AI regulations, data privacy, and responsible AI frameworks.

The position of Gen AI / AI Engineer (Mid-Level) in Hyderabad requires a candidate with at least 2 years of experience in developing and deploying AI/ML solutions, focusing particularly on Generative AI and RAG (Retrieval-Augmented Generation) architectures. As an AI Engineer, you will be involved in working with cutting-edge models, fine-tuning, and integrating systems to create scalable AI products. Your responsibilities will include fine-tuning and optimizing Large Language Models (LLMs) and generative models for both text and image data. You will also be responsible for designing and implementing RAG pipelines that incorporate knowledge bases, developing APIs, microservices, and scalable AI pipelines, collaborating with MLOps teams for production deployment, and staying updated on the latest AI trends to apply innovative techniques effectively. The ideal candidate should possess expertise in Python programming language, PyTorch or TensorFlow frameworks, Generative AI tools such as OpenAI, Anthropic, LLaMA, RAG architecture, Natural Language Processing (NLP), Computer Vision, API development, MLOps practices, and experience working with Cloud Platforms like AWS, Azure, or GCP. Qualifications for this role include a Bachelor's degree in Computer Science or a related field, a minimum of 2 years of experience in AI/ML with a focus on GenAI and RAG, and hands-on experience in deploying models at a production level. If you are enthusiastic about contributing to the development of next-generation AI solutions, we encourage you to apply for this exciting opportunity.,

We are looking for a highly motivated Mid-Level AI Engineer to join our growing AI team. Your main responsibility will be to develop intelligent applications using Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. Working closely with data scientists, backend engineers, and product teams, you will build and deploy AI-powered solutions that provide real-world value. Your key responsibilities will include designing, developing, and optimizing applications utilizing LLMs such as GPT, LLaMA, and Claude. You will also be tasked with implementing RAG pipelines to improve LLM performance using domain-specific knowledge bases and search tools. Developing and maintaining robust Python codebases for AI-driven solutions will be a crucial part of your role. Additionally, integrating vector databases like Pinecone, Weaviate, and FAISS, as well as embedding models for information retrieval, will be part of your daily tasks. You will work with APIs, frameworks like LangChain and Haystack, and various tools to create scalable AI workflows. Collaboration with product and design teams to define AI use cases and deliver impactful features will also be a significant aspect of your job. Conducting experiments to assess model performance, retrieval relevance, and system latency will be essential for continuous improvement. Staying up-to-date with the latest research and advancements in LLMs, RAG, and AI infrastructure is crucial for this role. To be successful in this position, you should have at least 3-5 years of experience in software engineering or AI/ML engineering, with a strong proficiency in Python. Experience working with LLMs such as OpenAI and Hugging Face Transformers is required, along with hands-on experience in RAG architecture and vector-based retrieval techniques. Familiarity with embedding models like SentenceTransformers and OpenAI embeddings is also necessary. Knowledge of API design, deployment, performance optimization, version control (e.g., Git), containerization (e.g., Docker), and cloud platforms (e.g., AWS, GCP, Azure) is expected. Preferred qualifications include experience with LangChain, Haystack, or similar LLM orchestration frameworks. Understanding NLP evaluation metrics, prompt engineering best practices, knowledge graphs, semantic search, and document parsing pipelines will be beneficial. Experience deploying models in production, monitoring system performance, and contributing to open-source AI/ML projects are considered advantageous for this role.,

You will be responsible for managing various servers such as Active Directory, File Server, Web Server (IIS, Apache, Nginx), and Application Server. This includes installation, troubleshooting, and backup of Database Servers like MS-SQL, MySQL, MongoDB, Redis, and PostgreSQL. Additionally, you will handle the installation of new Windows Server, Linux, and Desktop systems, as well as the installation and troubleshooting of applications like VB, C#, .NET, etc. Basic knowledge of managing Public Cloud services such as AWS, Azure is required along with experience in Virtual Hypervisor management using Hyper-V or Esxi. You will be tasked with managing Virtual Machines/Servers and ensuring proper backups are in place. Troubleshooting server hardware and OS issues, assisting in patch deployment and server upgrades, monitoring server performance and availability, and addressing end-user issues escalated from Desktop Support are also part of your responsibilities. Moreover, you will work on ongoing IT projects as assigned, contributing to the overall success of transformative AI projects within our technology-driven publishing and legal-tech organization.,

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.,

The ideal candidate for this position in Ahmedabad should be a graduate with at least 3 years of experience. At Bytes Technolab, we strive to create a cutting-edge workplace infrastructure that empowers our employees and clients. Our focus on utilizing the latest technologies enables our development team to deliver high-quality software solutions for a variety of businesses. You will be responsible for leveraging your 3+ years of experience in Machine Learning and Artificial Intelligence to contribute to our projects. Proficiency in Python programming and relevant libraries such as NumPy, Pandas, and scikit-learn is essential. Hands-on experience with frameworks like PyTorch, TensorFlow, Keras, Facenet, and OpenCV will be key in your role. Your role will involve working with GPU acceleration for deep learning model development using CUDA, cuDNN. A strong understanding of neural networks, computer vision, and other AI technologies will be crucial. Experience with Large Language Models (LLMs) like GPT, BERT, LLaMA, and familiarity with frameworks such as LangChain, AutoGPT, and BabyAGI are preferred. You should be able to translate business requirements into ML/AI solutions and deploy models on cloud platforms like AWS SageMaker, Azure ML, and Google AI Platform. Proficiency in ETL pipelines, data preprocessing, and feature engineering is required, along with experience in MLOps tools like MLflow, Kubeflow, or TensorFlow Extended (TFX). Expertise in optimizing ML/AI models for performance and scalability across different hardware architectures is necessary. Knowledge of Natural Language Processing (NLP), Reinforcement Learning, and data versioning tools like DVC or Delta Lake is a plus. Skills in containerization tools like Docker and orchestration tools like Kubernetes will be beneficial for scalable deployments. You should have experience in model evaluation, A/B testing, and establishing continuous training pipelines. Working in Agile/Scrum environments with cross-functional teams, understanding ethical AI principles, model fairness, and bias mitigation techniques are important. Familiarity with CI/CD pipelines for machine learning workflows and the ability to communicate complex concepts to technical and non-technical stakeholders will be valuable.,

You will be working as a Consultant with 4 to 7 years of experience in Bangalore/Gurgaon in a Hybrid work mode. Your primary skills should include Machine Learning, Python, and Gen AI. Additionally, proficiency in Python is preferred, and familiarity with other programming languages like R and Java would be a plus. Experience with frameworks such as TensorFlow, PyTorch, or scikit-learn is required. You should also have experience working with generative AI models like GPT, BERT, LLaMA, or other transformer-based architectures. Your responsibilities will include designing and implementing AI/ML models and data-driven solutions to address complex challenges in healthcare and life sciences. You will be analyzing large datasets to identify trends, generate insights, and support data-informed decision-making. Collaboration with consultants, data engineers, and scientists to build end-to-end data pipelines and analytical workflows is crucial. Client engagement through interviews, workshops, and presentations will be a part of your role, contributing to deliverables and building strong relationships. Moreover, you will be translating complex analyses into clear, actionable insights for both technical and non-technical stakeholders. Continuous learning and mentorship are essential as you need to stay current with AI/ML advancements, contribute to research and proposals, and mentor junior team members. Proficiency in data manipulation, cleaning, and analysis, as well as creating clear and insightful visualizations using tools like Matplotlib, Seaborn, or Tableau, is required. Familiarity with cloud services like AWS, Google Cloud, or Azure for deploying AI solutions will be an added advantage.,

You should have hands-on experience in Machine Learning Model and deep learning development using python. You will be responsible for Data Quality Analysis and Data preparation, Exploratory Data Analysis, and visualization of data. Additionally, you will define validation strategies, preprocessing or feature engineering on a given dataset, and data augmentation pipelines. Text processing using Machine Learning and NLP for processing documents will also be part of your role. Your tasks will include training models, tuning their hyperparameters, analyzing model errors, and designing strategies to overcome them. You should have experience with python packages such as Numpy, Scipy, Scikit-learn, Theano, TensorFlow, Keras, PyTorch, Pandas, and Matplotlib. Experience in working on Azure open AI studio or openai using python or LLAMA or Langchain is required. Moreover, experience in working on Azure function and python flask/api development/streamlit, prompt engineering, conversational AI, and LLM models like word2Vec, Glove, spacy, BERT embedding models is preferred. You are expected to possess distinctive problem-solving, strategic, and analytical capabilities, as well as excellent time-management and organization skills. Strong knowledge in Programming languages like Python, reactjs, SQL, big data is essential. Excellent verbal and written communication skills are necessary for effective interaction between business and technical architects and developers. You should have 2 - 4 years of relevant experience and a Bachelors Degree in Computer Science, Computer Engineering, masters in computer application, MIS, or a related field. End-to-End development experience in deployment of the Machine Learning model using python and Azure ML studio is required. Exposure in developing client-based or web-based software solutions and Certification of Machine Learning and Artificial Intelligence will be beneficial. Good to have experience in power platform or power pages or Azure OpenAI studio. Grant Thornton INDUS comprises GT U.S. Shared Services Center India Pvt Ltd and Grant Thornton U.S. Knowledge and Capability Center India Pvt Ltd. Grant Thornton INDUS is the shared services center supporting the operations of Grant Thornton LLP, the U.S. member firm of Grant Thornton International Ltd. Established in 2012, Grant Thornton INDUS employs professionals across a wide range of disciplines including Tax, Audit, Advisory, and other operational functions. The culture at Grant Thornton INDUS promotes empowered people, bold leadership, and distinctive client service. Working at Grant Thornton INDUS offers an opportunity to be part of something significant and serves communities in India through inspirational and generous services to give back to the communities they work in. Grant Thornton INDUS has its offices in two locations in India Bengaluru and Kolkata.,

You will be responsible for managing Active Directory, file server, web server (IIS, Apache, Nginx), and application server. This includes the installation, troubleshooting, and backup of Database Servers such as MS-SQL, MySQL, MongoDB, Redis, and PostgreSQL. Your role will involve installing new Windows Server, Linux, and Desktop systems, as well as handling the installation and troubleshooting of Windows Server and Linux applications/software like VB, C#, .NET, etc. Additionally, you should have a basic understanding of public cloud management services like AWS, Azure, etc. As an AI Solution Architect, you will manage virtual hypervisors like Hyper-V or Esxi, virtual machine/server management, and backup procedures. You will be responsible for troubleshooting basic server hardware and operating system issues, assisting in patch deployment and server upgrades, and monitoring server performance and availability while troubleshooting OS-related issues. Furthermore, you will respond to end-user issues escalated from Desktop Support and collaborate on ongoing IT projects as assigned.,

Imagine what you could do here. At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Every single day, people do amazing things at Apple. Do you want to impact the future of Manufacturing here at Apple through cutting edge ML techniques This position involves a wide variety of skills, innovation, and is a rare opportunity to be working on ground breaking, new applications of machine-learning, research and implementation. Ultimately, your work would have a huge impact on billions of users across the globe. You can help inspire change, by using your skills to influence globally recognized products" supply chain. The goal of Apple's Manufacturing & Operations team is to take a vision of a product and turn it into a reality. Through the use of statistics, the scientific process, and machine learning, the team recommends and implements solutions to the most challenging problems. Were looking for experienced machine learning professionals to help us revolutionize how we manufacture Apples amazing products. Put your experience to work in this highly visible role. The Operations Advanced Analytics team is looking for creative and motivated hands-on individual contributors who thrive in a dynamic environment and enjoy working with multi-functional teams. As a member of our team, you will work on applied machine-learning algorithms to seek problems that focus on topics such as classification, regression, clustering, optimizations, and other related algorithms to impact and optimize Apple's supply chain and manufacturing processes. As a part of this role, you would work with the team to build end-to-end machine learning systems and modules, and deploy the models to our factories. You'll be collaborating with Software Engineers, Machine Learning Engineers, Operations, and Hardware Engineering teams across the company. Minimum Qualifications: - 3+ years experience in machine learning algorithms, software engineering, and data mining models with an emphasis on large language models (LLM) or large multimodal models (LMM). - Masters in Machine Learning, Artificial intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering, or related field. Preferred Qualifications: - Proven experience in LLM and LMM development, fine-tuning, and application building. Experience with agents and agentic workflows is a major plus. - Experience with modern LLM serving and inference frameworks, including vLLM for efficient model inference and serving. - Hands-on experience with LangChain and LlamaIndex, enabling RAG applications and LLM orchestration. - Strong software development skills with proficiency in Python. Experienced user of ML and data science libraries such as PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn. - Familiarity with distributed computing, cloud infrastructure, and orchestration tools, such as Kubernetes, Apache Airflow (DAG), Docker, Conductor, Ray for LLM training and inference at scale is a plus. - Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA) and their optimization for low-latency inference. - Ability to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non-technical audiences. - Experience applying ML techniques in manufacturing, testing, or hardware optimization is a major plus. - Proven experience in leading and mentoring teams is a plus. Submit CV,

The Consultant role requires 4 to 7 years of work experience and is based in Bangalore/Gurgaon with a Hybrid work mode. The ideal candidate should possess Machine Learning, Python, and Gen AI skills. Additionally, proficiency in Python is preferred, with knowledge of other programming languages like R and Java being a plus. Experience with frameworks such as TensorFlow, PyTorch, or scikit-learn is essential. Familiarity with generative AI models like GPT, BERT, LLaMA, or other transformer-based architectures is a significant advantage. Candidates should have experience in developing, testing, and deploying high-quality AI models and solutions and be proficient in data manipulation, cleaning, and analysis. Ability to create clear visualizations using tools like Matplotlib, Seaborn, or Tableau is required. Familiarity with cloud services like AWS, Google Cloud, or Azure for deploying AI solutions is beneficial. Key Responsibilities include designing and implementing AI/ML models and data-driven solutions for complex challenges in healthcare and life sciences. The role involves analyzing large datasets to identify trends, generate insights, and support data-informed decision-making. Collaboration with consultants, data engineers, and scientists is essential to build end-to-end data pipelines and analytical workflows. Interacting with clients through interviews, workshops, and presentations to contribute to deliverables and foster strong relationships is a key aspect of the role. The candidate should be able to communicate complex analyses into actionable insights for both technical and non-technical stakeholders. Continuous learning, staying updated with AI/ML advancements, contributing to research and proposals, and mentoring junior team members are also part of the responsibilities.,

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 company is seeking a Gen AI / AI Engineer with at least 2 years of experience in the field of AI/ML solutions, specifically focusing on Generative AI and RAG (Retrieval-Augmented Generation) architectures. The role involves working on cutting-edge models, fine-tuning, and integrating systems to develop scalable AI products. Responsibilities include fine-tuning and optimizing Large Language Models (LLMs) and generative models for text and image, designing and implementing RAG pipelines with knowledge bases, developing APIs, microservices, and scalable AI pipelines, collaborating with MLOps teams for production deployment, and staying updated on the latest AI trends to apply innovative techniques. The ideal candidate should possess skills in Python, PyTorch/TensorFlow, Generative AI (OpenAI, Anthropic, LLaMA), RAG architecture, Natural Language Processing (NLP), Computer Vision, API development, MLOps, and have experience working with Cloud Platforms such as AWS/Azure/GCP. Qualifications include a Bachelors degree in Computer Science or a related field, at least 2 years of experience in AI/ML with a focus on GenAI & RAG, and hands-on experience with production-grade model deployment. If you are enthusiastic about contributing to the development of next-generation AI solutions, we encourage you to apply for this exciting opportunity now!,

Key Responsibilities: LLM Deployment & Optimization Deploy, fine-tune, and optimize open-source LLMs (e.g., LLaMA, Mistral, CodeS, DeepSeek). Implement quantization (e.g., 4-bit, 8-bit) and pruning for efficient inference on commodity hardware. Build and manage inference APIs (REST/gRPC) for production use. Infrastructure Management Set up and manage on-premise GPU servers and VM-based deployments. Build scalable cloud-based LLM infrastructure using AWS (SageMaker, EC2), Azure ML, or GCP Vertex AI. Ensure cost efficiency by choosing appropriate hardware and job scheduling strategies. MLOps & Reliability Engineering Develop CI/CD pipelines for model training, testing, evaluation, and deployment. Integrate version control for models, data, and hyperparameters. Set up logging, tracing, and monitoring tools (e.g., MLflow, Prometheus, Grafana) for model performance and failure detection. Security, Compliance & Performance Ensure data privacy (FERPA/GDPR) and enforce security best practices across deployments. Apply secure coding standards and implement RBAC, encryption, and network hardening for cloud/on-prem. Cross-functional Integration Work closely with AI solution engineers, backend developers, and product owners to integrate LLM services into the platform. Support performance benchmarking and A/B testing of AI features across modules. Documentation & Internal Enablement Document LLM pipelines, configuration steps, and infrastructure setup in internal playbooks. Create guides and reusable templates for future deployments and models. Key Requirements: Education: Bachelors or Masters in Computer Science, AI/ML, Data Engineering, or related field. Technical Skills: Strong Python experience with ML libraries (e.g., PyTorch, Hugging Face Transformers). Familiar with LangChain, LlamaIndex, or other RAG frameworks. Experience with Docker, Kubernetes, and API gateways (e.g., Kong, NGINX). Working knowledge of vector databases (FAISS, Pinecone, Qdrant). Familiarity with GPU deployment tools (CUDA, Triton Inference Server, HuggingFace Accelerate). Experience: 4+ years in an AI/MLOps role, including experience in LLM fine-tuning and deployment. Hands-on work with model inference in production environments (both cloud and on-prem). Exposure to SaaS and modular product environments is a plus.

You should have more than 12 years of IT experience, with 5 to 7 years spent working as a designer and developer using Python. Additionally, you should have at least 3 years of experience in implementing Large Language Models (LLM). Exposure to Llama would be considered a strong advantage in this role. In this position, you will be responsible for design and architecture, with 2 to 3 years of relevant experience in these areas. As an independent resource, you should possess a strong understanding of design patterns and be familiar with best practices in AI, including generating AI. Excellent communication and presentation skills are essential, as you will be collaborating with client technical stakeholders. You should also demonstrate the ability to make informed decisions and influence technical stakeholders effectively. Furthermore, you should be capable of conducting in-depth analyses of the client's technical landscape and proposing solutions that not only benefit the customer but also contribute to new business opportunities.,

We will count on you to: Identify opportunities which add value to the business and make the process more efficient. Invest in understand the core business including products, process, documents, and data points with the objective of identifying efficiency and value addition opportunities. Design and develop end-to-end NLP/LLM solutions for document parsing, information extraction, and summarization from PDFs and scanned text. Develop AI applications to automate manual and repetitive tasks using generative AI and machine learning. Fine-tune open-source LLMs (like LLaMA, Mistral, Falcon, or similar) or build custom pipelines using APIs (OpenAI, Anthropic, Azure OpenAI). Build custom extraction logic using tools like LangChain, Haystack, Hugging Face Transformers, and OCR libraries like Tesseract or Azure Form Recognizer. Create pipelines to convert outputs into formatted Microsoft Word or PDF files using libraries like docx, PDFKit, ReportLab, or LaTeX. Collaborate with data engineers and software developers to integrate AI models into production workflows. Ensure model performance, accuracy, scalability, and cost-efficiency across business use cases. Stay updated with the latest advancements in generative AI, LLMs, and NLP research to identify innovative solutions. Design, develop, and maintain robust data pipelines for extracting, transforming, and loading (ETL) data from diverse sources. As the operational scales updesign and implement scalable data storage solutions and integrate them with existing systems. Utilize cloud platforms (AWS, Azure, Google Cloud) for data storage and processing. Conduct code reviews and provide mentorship to junior developers. Stay up-to-date with the latest technology trends and best practices in data engineering and cloud services. Ability to lead initiatives and deliver results by engaging with cross-functional teams and resolving data ambiguity issues. Be responsible for the professional development of your projects and institute a succession plan. What you need to have: Bachelors degree in Engineering, Analytics, or a related field, MBA, Computer Applications, IT, Business Analytics, or any discipline. Proven experience of 8-12 years in Python development Hands-on experience with frameworks and libraries like Transformers, LangChain, PyTorch/TensorFlow, spaCy, Hugging Face, and Haystack. Strong expertise in document parsing, OCR (Tesseract, AWS Textract, Azure Form Recognizer), and entity extraction. Proficiency in Python and familiarity with cloud-based environments (Azure, AWS, GCP). Experience deploying models as APIs/microservices using FastAPI, Flask, or similar. Familiarity with PDF parsing libraries (PDFMiner, PyMuPDF, Apache PDFBox) and Word generation libraries (python-docx, PDFKit). Solid understanding of prompt engineering and prompt-tuning techniques. Proven experience with data automation and building data pipelines. Proven track record in building and maintaining data pipelines and ETL processes. Strong knowledge of Python libraries such as Pandas, NumPy, and PySpark, Camelot. Familiarity with database management systems (SQL and NoSQL databases). Experience in designing and implementing system architecture. Ability to operate in a multi layered technology architecture and shape the technology maturity of the organization. Solid understanding of software development best practices, including version control (Git), code reviews, and testing frameworks (PyTest, UnitTest). Strong attention to detail and ability to work with complex data sets. Effective communication skills to present findings and insights to both technical and non-technical stakeholders. Specify superior listening, verbal and written communication skills Excellent project management and organization skills Superlative stakeholder management skills - ability to positively influence stakeholders. Synthesis skills- Ability to connect the dots and answer the business question. Excellent problem-solving, structuring and critical-thinking skills. Ability to work independently and collaboratively in a fast-paced environment.

Key Responsibilities : We are seeking a highly skilled and motivated AI Engineer to join our team. In this role, you will leverage your expertise in AI technologies and the Microsoft ecosystem to design, build, and deploy intelligent agents and automation solutions that enhance business processes and deliver value to our clients. Candidates must have extensive experience in the Microsoft environment. You will collaborate with cross-functional teams to create innovative solutions using Microsoft tools and platforms. Responsibilities : Agent Development : - Design, implement, and optimize AI agents using Microsoft Azure Framework and related technologies. - Develop custom AI solutions leveraging Power Automate, Azure OpenAI, and other Microsoft tools. Solution Integration : - Deploy AI solutions within client environments, ensuring scalability and seamless integration with existing systems. - Work with stakeholders to identify automation opportunities and tailor solutions to business needs. AI Algorithm and Model Implementation : - Design and implement machine learning algorithms, focusing on natural language processing (NLP) and conversational AI. - Perform data preprocessing, feature engineering, and model training to create high-performing solutions. Collaboration and Support : - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to deliver integrated solutions. - Provide technical guidance and support to ensure the successful adoption and use of AI-driven tools. Continuous Improvement : - Stay updated on advancements in AI, machine learning, and Microsofts AI technologies. - Contribute to knowledge sharing by conducting training sessions and documenting best practices. Preferred Skills : - Strong knowledge of Azure OpenAI, Azure AI Search Index and open source libraries such as LangChain and LlamaIndex. - Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Familiarity with building and managing cloud-based solutions, preferably on Microsoft Azure. - Understanding of conversational AI technologies and chatbot frameworks. - Experience with data analysis tools and techniques to uncover insights and optimize models. Requirements : - Bachelors or Masters degree in Computer Science, Data Science, or a related field. - Proven experience in developing and deploying AI/ML models in real-world applications. - Strong programming skills, especially in Python, and familiarity with version control systems like Git. - Extensive experience in the Microsoft environment and related technologies.

Required Skills & Experience: 4+ years of experience in penetration testing, red teaming or offensive security. 1+ years working with AI/ML or LLM-based systems. Deep familiarity with LLM architectures (e.g., GPT, Claude, Mistral, LLaMA) and pipelines (e.g., LangChain, Haystack, RAG-as-a-Service). Strong understanding of embedding models, vector databases (Pinecone, Weaviate, FAISS), and API-based model deployments. Experience with adversarial ML, secure inference, and data integrity in training pipelines. Experience with red team infrastructure and tooling such as Cobalt Strike, Mythic, Sliver, Covenant, and custom payload development. Proficient in scripting languages such as Python, PowerShell, Bash or Go.

We are looking for a junior engineer passionate about Trainee-Generative AI (GenAI) to join our team. In this role, you will assist in designing, prototyping, and deploying GenAI applications using models such as GPT, LLaMA, or other transformer-based architectures. You will work closely with senior engineers, data scientists, and product managers to explore GenAIs potential across various use cases. Key Responsibilities: Support the development of applications using foundation models (e.g., GPT, Claude, Gemini, LLaMA, Mistral). Assist in fine-tuning or prompt-engineering of large language models (LLMs) for specific business use cases. Build and test LLM pipelines using APIs (OpenAI, Hugging Face, Cohere, etc.). Contribute to prompt design, evaluation, and benchmarking of GenAI model outputs. Collaborate on building GenAI-powered chatbots, copilots, summarizers, and content generation tools. Participate in data preparation, cleaning, and formatting for model training and evaluation. Implement simple RAG (Retrieval-Augmented Generation) pipelines under guidance. Contribute to documentation, model evaluation reports, and performance dashboards.

We are looking for a junior engineer passionate about Trainee-Generative AI (GenAI) to join our team. In this role, you will assist in designing, prototyping, and deploying GenAI applications using models such as GPT, LLaMA, or other transformer-based architectures. You will work closely with senior engineers, data scientists, and product managers to explore GenAIs potential across various use cases. Key Responsibilities: Support the development of applications using foundation models (e.g., GPT, Claude, Gemini, LLaMA, Mistral). Assist in fine-tuning or prompt-engineering of large language models (LLMs) for specific business use cases. Build and test LLM pipelines using APIs (OpenAI, Hugging Face, Cohere, etc.). Contribute to prompt design, evaluation, and benchmarking of GenAI model outputs. Collaborate on building GenAI-powered chatbots, copilots, summarizers, and content generation tools. Participate in data preparation, cleaning, and formatting for model training and evaluation. Implement simple RAG (Retrieval-Augmented Generation) pipelines under guidance. Contribute to documentation, model evaluation reports, and performance dashboards.

Key Responsibilities: Fine-tune and deploy LLMs (e.g., GPT, LLaMA, Mistral) using frameworks like Hugging Face Transformers and LangChain. Build and optimize RAG pipelines with vector databases (e.g., Pinecone, FAISS, Weaviate). Engineer prompts for structured and reliable outputs across diverse use cases such as chatbots, summarization tools, and coding assistants. Implement scalable inference pipelines; optimize for latency, throughput, and cost using quantization, distillation, and other model optimization techniques. Collaborate with product, design, and engineering teams to integrate generative AI capabilities into user-facing features. Monitor and improve model performance, accuracy, safety, and compliance in production. Ensure responsible AI practices through content filtering, output sanitization, and ethical deployment. Required Skills: Proficiency in Python and familiarity with modern machine learning tools and libraries. Hands-on experience with LLM development using Hugging Face Transformers, LangChain, or LlamaIndex. Experience building and deploying RAG pipelines, including managing embeddings and vector search. Strong understanding of transformer architectures, tokenization, and prompt engineering techniques. Comfortable working with LLM APIs (e.g., OpenAI, Anthropic, Cohere) and serving models with FastAPI, Flask, or similar frameworks. Familiarity with deploying ML systems using Docker, Kubernetes, and cloud services (AWS, GCP, Azure). Experience with model evaluation, logging, and inference pipeline troubleshooting. Nice to Have: Exposure to multimodal models (e.g., text-to-image, video generation, TTS). Experience with reinforcement learning from human feedback (RLHF) or alignment techniques. Familiarity with open-source LLMs (e.g., Mistral, Mixtral, LLaMA, Falcon) and optimization tools (LoRA, quantization, PEFT). Knowledge of LangChain agents, tool integration, and memory management. Contributions to open-source GenAI projects, public demos, or blogs in the generative AI space. Basic proficiency in frontend development (e.g., React, Next.js) for rapid prototyping.

Hi all , we are looking for a role AI Engineer experience : 3 - 6 years notice period : Immediate - 15 days location : Bengaluru Generative AI Engineer Position Overview: We are looking for a Generative AI Engineer with expertise in Azure OpenAI and hands-on experience with models such as GPT-4o, GPT-o1, and open source LLMs like Llama, mistral. You will work on GenAI solutions development, RAG, fine-tuning, and deploying resources in Azure environment. Proficiency in prompt engineering, Python, PostgreSQL, FastAPI, Streamlit, Django and Angular is essential. This role also requires strong skills in AI models orchestration using intent mapping, Semantic Kernel or function calling, along with proficiency in presentation and public speaking. Key Responsibilities: • RAG, fine-tune, and deploy Azure OpenAI models (e.g., GPT-4o, GPT-o1) and other open-source large language models (LLMs). • Build AI-powered applications using frameworks such as FastAPI, Streamlit, Django, and Angular. • Design and execute AI workflows using tools like prompt flow, Semantic Kernel and implement function calling for complex use cases. • Conduct prompt engineering to improve model performance for specific business cases. • Visualize data and create user interaction insights using Power BI. • Ensure smooth deployment and maintenance of models on Azure cloud infrastructure, including scalability and optimization. • Prepare and deliver presentations, demos, and technical documentation to internal and external stakeholders. • Stay updated with advancements in generative AI, NLP, and machine learning to continuously improve models and methodologies. Required Skills & Qualifications: • Bachelors degree in Computer science, Artificial intelligence, Machine learning, or related field. • At least 2+ year of hands-on experience working on generative AI projects. • Strong expertise in Azure OpenAI models (GPT-4o, GPT-3.5, GPT-o1 etc.). • Proficient in Prompt Engineering, Python, Streamlit, Django, FastAPI, and Angular. • Basics of html, css, javascript, typescript and angular. • Basic understanding of neural networks, machine and transformer architectures. • Experience in retrieval-augmented generation (RAG) and fine-tuning Large language models. • Familiarity with AI model orchestration tools such as Semantic Kernel, intent mapping and function calling techniques. • Excellent public speaking and presentation skills to convey technical concepts to business stakeholders. • Azure Certified AZ900 or AI900 Preferred Qualifications: • Masters degree in Artificial Intelligence, Machine Learning, or related field. • At least 3+ years of experience working on generative AI, NLP, and machine learning projects. • Strong understanding of neural networks, machine learning and transformer architectures. • Implemented GenAI solutions in production. • Familiarity with Automotive Industry • Hands on experience in RAG, RAFT and optimized fine-tuning. • Azure Certified AI-102, DP-100, AZ-204 or DP-203