23 Transformer Models Jobs

As the Chief Technology Officer (CTO) of our AI vertical, you will be at the forefront of revolutionizing the way ad films, content, and experiences are crafted through cutting-edge Generative AI technology. You will play a pivotal role in leading the development of AI solutions across various domains such as LLMs, multimodal AI, image/video generation, and no-code tooling. Your responsibilities will extend to not only scaling AI workflows but also building internal systems that facilitate rapid and creative experimentation for our filmmaking and brand teams. This hands-on leadership position is tailored for individuals who are passionate about coding, adept at developing innovative GenAI tools, and have a keen focus on automation. Your key responsibilities will include architecting and overseeing the full AI stack, from model selection to real-time deployment. You will be tasked with building workflows that integrate various tools such as Runway, MidJourney, Google Veo, Suno, ElevenLabs, GPT, SDXL, among others. Additionally, you will design and optimize custom no-code pipelines utilizing platforms like ComfyUI, ControlNet, Deforum, InvokeAI, and more. Your role will involve writing and managing backend tools in Python, integrating APIs, automation scripts, and model wrappers. Leading a team of ML engineers, prompt engineers, and creative technologists will also be part of your responsibilities, along with developing reusable libraries and systems for content creation. To excel in this role, you must possess expertise in Python for AI pipelines, tooling, and backend scripting. Deep knowledge of machine learning, transformer models, diffusion models, and LLMs is essential. Hands-on experience with no-code GenAI platforms such as ComfyUI, Deforum, ControlNet, and proficiency in MLOps, inference optimization, and managing GPU workflows are critical. Your ability to bridge technology and creativity, enabling fast prototyping for image, video, and voice workflows, will be highly valued. Desirable qualifications include prior experience with AI-driven film/video tools, exposure to custom model training, LoRA tuning, and familiarity with platforms like HuggingFace, OpenAI, Replicate, and RunwayML. If you have built creative or experimental AI tools, sharing a repository or demo would be advantageous. Experience in startup environments or leadership roles in fast-paced, zero-to-one settings will be beneficial. In this role, you will take ownership of all AI tooling and workflow automation, internal platforms utilized by creative and production teams, and scaling GenAI pipelines to enhance production efficiency and output quality. You will also drive technical innovation and foster an experimentation culture within the company. This is a full-time, permanent position with a day shift schedule from Monday to Friday, requiring in-person work at the specified location.,

The position available is for the role of Data Scientist on a permanent, full-time basis. The ideal candidate should possess at least 7 years of experience in the field. The job location can be in Noida, Gurgaon, Pune, or Bangalore, with the standard working week being 5 days. The work mode for this role is Hybrid. The mandatory skills required for this position include expertise in Transformer Models, with experience in either finetuning or training on Open-Source Transformer-based models. The candidate should have completed projects involving LLM, NLP, LLAMA, Hugging face, and RAG. Proficiency in Python coding is a must, along with experience in Gen AI projects. Additionally, the candidate should have knowledge of either Machine Learning or Deep Learning. Experience with Conversational AI/Chatbot is considered a plus for this role.,

As a Senior Machine Learning Engineer at our AI/ML team, you will be responsible for designing and building intelligent search systems. Your focus will be on utilizing cutting-edge techniques in vector search, semantic similarity, and natural language processing to create innovative solutions. Your key responsibilities will include designing and implementing high-performance vector search systems using tools like FAISS, Milvus, Weaviate, or Pinecone. You will develop semantic search solutions that leverage embedding models and similarity scoring for precise and context-aware retrieval. Additionally, you will be expected to research and integrate the latest advancements in ANN algorithms, transformer-based models, and embedding generation. Collaboration with cross-functional teams, including data scientists, backend engineers, and product managers, will be essential to bring ML-driven features from concept to production. Furthermore, maintaining clear documentation of methodologies, experiments, and findings for technical and non-technical stakeholders will be part of your role. To qualify for this position, you should have at least 3 years of experience in Machine Learning, with a focus on NLP and vector search. A deep understanding of semantic embeddings, transformer models (e.g., BERT, RoBERTa, GPT), and hands-on experience with vector search frameworks is required. You should also possess a solid understanding of similarity search techniques such as cosine similarity, dot-product scoring, and clustering methods. Strong programming skills in Python and familiarity with libraries like NumPy, Pandas, Scikit-learn, and Hugging Face Transformers are necessary. Exposure to cloud platforms, preferably Azure, and container orchestration tools like Docker and Kubernetes is preferred. This is a full-time position with benefits including health insurance, internet reimbursement, and Provident Fund. The work schedule consists of day shifts, fixed shifts, and morning shifts, and the work location is in-person. The application deadline for this role is 18/04/2025.,

As a Senior Specialist in Software Development (Artificial Intelligence) at Accelya, you will lead the design, development, and implementation of AI and machine learning solutions to tackle complex business challenges. Your expertise in AI algorithms, model development, and software engineering best practices will be crucial in working with cross-functional teams to deliver intelligent systems that optimize business operations and decision-making. Your responsibilities will include designing and developing AI-driven applications and platforms using machine learning, deep learning, and NLP techniques. You will lead the implementation of advanced algorithms for supervised and unsupervised learning, reinforcement learning, and computer vision. Additionally, you will develop scalable AI models, integrate them into software applications, and build APIs and microservices for deployment in cloud environments or on-premise systems. Collaboration with data scientists and data engineers will be essential in gathering, preprocessing, and analyzing large datasets. You will also implement feature engineering techniques to enhance the accuracy and performance of machine learning models. Regular evaluation of AI models using performance metrics and fine-tuning them for optimal accuracy will be part of your role. Furthermore, you will collaborate with business stakeholders to identify AI adoption opportunities, provide technical leadership and mentorship to junior team members, and stay updated with the latest AI trends and research to introduce innovative techniques to the team. Ensuring ethical compliance, security, and continuous improvement of AI systems will also be key aspects of your role. You should hold a Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field, along with at least 5 years of experience in software development focusing on AI and machine learning. Proficiency in AI frameworks and libraries, programming languages such as Python, R, or Java, and cloud platforms for deploying AI models is required. Familiarity with Agile methodologies, data structures, and databases is essential. Preferred qualifications include a Master's or PhD in Artificial Intelligence or Machine Learning, experience with NLP techniques and computer vision technologies, and certifications in AI/ML or cloud platforms. Accelya is looking for individuals who are passionate about shaping the future of the air transport industry through innovative AI solutions. If you are ready to contribute your expertise and drive continuous improvement in AI systems, this role offers you the opportunity to make a significant impact in the industry.,

As a Data Scientist AI/ML Developer, you will be responsible for various key tasks related to data collection, analysis, model development, and implementation of advanced technologies. You should have a strong understanding of data science methodologies and experience in working with machine learning models. This position is suitable for freshers as well as candidates with up to 5 years of experience. Your primary responsibilities will include gathering, cleaning, and analyzing large datasets for diverse applications. You will also be involved in building, training, and evaluating machine learning and deep learning models for tasks related to computer vision, natural language processing (NLP), and generative AI. You will utilize OpenCV to create solutions for image classification, object detection, facial recognition, and other vision-based tasks. Additionally, you will develop and fine-tune Generative Adversarial Networks (GANs) for synthetic data generation and image manipulation. Collaboration with cross-functional teams is essential in this role, as you will work closely with data engineers, software developers, and business analysts to integrate data-driven insights into production environments. Staying updated with the latest developments in AI, data science, and generative AI is crucial, and you should be able to apply best practices to projects effectively. Ensuring that machine learning models and data pipelines are scalable, efficient, and ready for production deployment is also a key part of your responsibilities. In terms of required skills, you should have strong proficiency in computer vision techniques using OpenCV, hands-on experience with Generative Adversarial Networks (GANs), and familiarity with LangChain, GPT models, and other generative AI frameworks. Proficiency in Python and relevant ML libraries such as TensorFlow and PyTorch is essential. Expertise in data preprocessing, feature engineering, and working with large datasets is also required. Preferred skills include experience in Natural Language Processing (NLP), model deployment using cloud services and containerization, familiarity with transformer architectures, and knowledge of big data technologies. Additionally, possessing soft skills such as strong problem-solving abilities, effective communication, and a continuous learning mindset will be advantageous in this role.,

As an AI/ML Engineer, you will be a valuable member of our team, contributing to the development of intelligent systems that harness the power of machine learning and artificial intelligence. Your primary responsibilities will include designing, creating, and implementing machine learning models to address a variety of use cases, such as prediction, classification, NLP, and computer vision. You will collaborate closely with diverse teams to deliver innovative solutions that tackle real-world challenges effectively. Your key responsibilities will involve: - Designing and implementing machine learning models and algorithms for different applications. - Analyzing and preprocessing extensive datasets to establish resilient training pipelines. - Staying abreast of the latest advancements in AI/ML through research and integrating relevant techniques into projects. - Training, fine-tuning, and optimizing models to ensure high performance and scalability. - Deploying models into production environments using tools like Docker, Kubernetes, or cloud services (AWS, GCP, Azure). - Working alongside software engineers, data scientists, and product teams to seamlessly integrate AI/ML solutions into applications. - Monitoring model performance in production, continuously iterating for enhancements, and documenting design decisions, code, and models for transparency and reproducibility. Preferred qualifications for this role include: - Proficiency in NLP libraries (e.g., Hugging Face Transformers, spaCy) or computer vision tools (e.g., OpenCV). - Familiarity with deep learning architectures like CNNs, RNNs, GANs, or transformer models. - Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker). - Previous contributions to open-source AI/ML projects or publications in relevant conferences/journals. If you are passionate about AI/ML technologies and eager to work on cutting-edge solutions that make a meaningful impact, we encourage you to apply for this exciting opportunity to join our dynamic team.,

As a Senior AI Engineer (Tech Lead) at EY, you will have the opportunity to leverage your technical expertise to develop and implement cutting-edge AI solutions. With a minimum of 4 years of experience in Data Science and Machine Learning, including NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture, you will play a crucial role in driving innovation and creating impactful solutions for enterprise industry use cases. Your responsibilities will include contributing to the design and implementation of state-of-the-art AI solutions, leading a team of 4-6 developers, and collaborating with stakeholders to identify business opportunities and define AI project goals. You will stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. By utilizing generative AI techniques, such as LLMs and Agentic Framework, you will develop innovative solutions tailored to specific business requirements. Your role will also involve integrating with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to enhance generative AI capabilities. Additionally, you will be responsible for implementing and optimizing end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Your expertise in data engineering, DevOps, and MLOps practices will be valuable in curating, cleaning, and preprocessing large-scale datasets for generative AI applications. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, and demonstrate proficiency in Python, Data Science, Machine Learning, OCR, and document intelligence. Strong collaboration with software engineering and operations teams, along with excellent problem-solving and analytical skills, will be essential in translating business requirements into technical solutions. Moreover, your familiarity with trusted AI practices, data privacy, security, and ethical considerations will ensure the fairness, transparency, and accountability of AI models and systems. Additionally, having a solid understanding of NLP techniques, frameworks like TensorFlow or PyTorch, and cloud platforms such as Azure, AWS, or GCP will be beneficial in deploying AI solutions in a cloud environment. Proficiency in designing or interacting with agent-based AI architectures, implementing optimization tools and techniques, and driving DevOps and MLOps practices will also be advantageous in enhancing the performance and efficiency of AI models. Join EY to build an exceptional experience for yourself and contribute to creating a better working world for all through the power of AI and technology.,

As a research scientist at AryaXAI, you will have the unique opportunity to be part of a team that is revolutionizing the field of AI. Our mission is to develop explainable, safe, and scalable AI systems that empower researchers, engineers, and organizations while ensuring transparency and safety. Our team at AryaXAI is driven by a shared passion for innovation, collaboration, and excellence. In our flat organizational structure, everyone actively contributes to our mission, embodying values of curiosity, initiative, and outstanding performance. In this role, you will tackle advanced challenges in ML explainability, safety, and alignment. You will have the flexibility to specialize in various ML/DL areas that address these challenges, and develop new techniques around ML Observability & Alignment. Collaborating with MLEs and SDEs, you will lead the rollout of features and ensure their quality and stability. Additionally, you will be responsible for creating and maintaining technical and product documentation. To excel in this position, you should have a strong academic background in machine learning and deep learning concepts. Hands-on experience with frameworks like Tensorflow and Pytorch is essential. An enthusiasm for working on diverse DL problems involving different data sets (textual, tabular, categorical, images) is crucial. Proficiency in deploying code in cloud/on-premise environments, along with solid knowledge of MLOps and productionizing ML models, is required. Moreover, prior experience in ML explainability methods such as LRP, SHAPE, LIME, IG, CEM, and at least 2 years of hands-on experience in Deep Learning or Machine Learning are preferred. Hands-on experience in implementing techniques like Transformer models, GANs, and other deep learning models will be beneficial for this role.,

As a Senior AI/ML Engineer, you will be responsible for designing, developing, and deploying advanced AI models with a focus on generative AI, including transformer architectures such as GPT, BERT, T5, and other deep learning models utilized for text, image, or multimodal generation. You will work with extensive and complex datasets by cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training. Additionally, you will collaborate with cross-functional teams to identify project objectives and create solutions using generative AI tailored to business needs. Your role will involve implementing, fine-tuning, and scaling generative AI models in production environments to ensure robust model performance and efficient resource utilization. You will also be responsible for developing pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production. It is essential to stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability. Furthermore, documenting and communicating technical specifications, algorithms, and project outcomes to technical and non-technical stakeholders with an emphasis on explainability and responsible AI practices. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field. A relevant Ph.D. or research experience in generative AI would be advantageous. You should have 12-16 years of experience in machine learning, with at least 8 years in designing and implementing generative AI models or working specifically with transformer-based models. The ideal candidate will possess expertise in generative AI, transformer models, GANs, VAEs, text generation, and image generation. Strong knowledge of machine learning algorithms, deep learning, neural networks, and programming skills in Python and SQL are required. Familiarity with libraries such as Hugging Face Transformers, PyTorch, TensorFlow, and experience with MLOps tools like Docker, Kubernetes, MLflow, and Cloud Platforms (AWS, GCP, Azure) is essential. Additionally, proficiency in data engineering concepts such as data preprocessing, feature engineering, and data cleaning is preferred. Joining our team will provide you with an opportunity to work on technical challenges with global impact, vast opportunities for self-development through online university access and sponsored certifications, sponsored Tech Talks & Hackathons, and a generous benefits package including health insurance, retirement benefits, flexible work hours, and more. You will work in a supportive environment with forums to explore passions beyond work, offering an exciting opportunity to contribute to cutting-edge solutions while advancing your career in a dynamic and collaborative setting.,

You are a skilled AI Developer with 24 years of experience, and you will be joining a dynamic team. Your main responsibility will be to design, develop, and fine-tune AI models for image and text data, focusing on Generative AI technologies such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer models. You will be implementing, training, and optimizing deep learning models for Natural Language Processing (NLP), Computer Vision (CV), and multimodal AI tasks. Your role will also involve managing the end-to-end lifecycle of AI projects, including data collection, pre-processing, model training, evaluation, and deployment. Collaboration with data scientists, software engineers, and product managers to integrate AI solutions into existing systems and products will be crucial. Staying updated with the latest advancements in AI research and applying innovative techniques to solve complex problems will be expected from you. Your qualifications should include a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, along with 2 - 4 years of hands-on experience in developing AI solutions, particularly in Generative AI models. Proficiency in programming languages such as Python and experience with AI frameworks like TensorFlow, PyTorch, or Keras is necessary. A strong understanding of deep learning algorithms, especially in generative models like GANs, VAEs, and transformer architectures, is required. Experience in pre-processing and augmenting large datasets for training AI models will be advantageous. Moreover, familiarity with cloud platforms (AWS, GCP, Azure) for model training and deployment is preferred. Excellent problem-solving skills and the ability to work collaboratively in a team are essential. Experience with Natural Language Processing (NLP) techniques and frameworks, knowledge of MLOps practices and tools for continuous integration and deployment of AI models, and familiarity with ethical AI practices, including strategies for mitigating bias and ensuring responsible AI usage, will be beneficial for this role.,

As a member of the Classical ML+NLP+Gen AI - L4 team at Tredence, you will be involved in tasks such as Model Fine-tuning, Model Pre-training, Named Entity Recognition, Prompt Engineering, Pyspark, Python, Regular expressions, SQL, Supervised ML, Tokenization, Transformer Models, Transformers, Unstructured Data Pre-processing, and Unsupervised ML. Tredence, founded in 2013, is a company dedicated to transforming data into actionable insights. With a focus on helping over 50 Fortune 500 clients succeed in their industries, we operate globally with our headquarters in San Jose and a presence in 5 countries. Our goal is to be the world's most indispensable analytics partner by combining deep domain expertise with advanced AI and data science to deliver exceptional business value. We welcome you to be a part of our team and contribute to our innovative journey.,

As a Firefly models & Services architect within Adobe's Firefly Gen AI Models and services group, you will play a crucial role in supporting the creation, enhancement, and deployment of model pipelines for Adobe's top products across various domains. Your expertise in machine learning will be essential in shaping the future of digital experiences by architecting the pipelines of the future foundation models at Adobe. You will collaborate closely with a talented team of ML and service engineers to drive innovation and bring impactful features to Adobe's products, reaching millions of users worldwide. Your responsibilities will include designing and optimizing large-scale foundation model pipelines in Generative AI, developing GenAI backend services for Firefly, and collaborating with Applied researchers and engineers to bring ideas to production. As a technical leader, you will provide mentorship to junior team members, explore new ML technologies to enhance engineering effectiveness, and contribute to the continuous improvement of Adobe's GenAI engineering processes. Your strong communication skills, technical leadership abilities, and hands-on experience with Generative AI technologies will be instrumental in your success in this role. To thrive in this position, you should possess a Master's or Ph.D. in Computer Science, AI/ML, or related fields, along with at least 12 years of experience and 3+ years in a Lead/Architect role. Your expertise in the latest Generative AI technologies, such as GAN, diffusion, and transformer models, as well as your experience with large-scale GenAI model pipelines and ML feature shipping, will set you up for success. Additionally, your collaboration skills and experience in tech leading time-sensitive and business-critical GenAI projects will be valuable assets in this role. Preferred qualifications include experience in training or optimizing models using CUDA, Triton, TRT, and converting models from frameworks like PyTorch and TensorFlow to ensure compatibility and optimized performance across different platforms. A good publication record in Computer Science, AI/ML, or related fields will further strengthen your candidacy for this position. At Adobe, you will have the opportunity to immerse yourself in a supportive work environment that fosters creativity, curiosity, and continuous learning. If you are seeking to make a significant impact and grow your career in a dynamic and innovative setting, Adobe is the place for you. Join us in shaping the future of digital experiences and explore the meaningful benefits we offer to our employees. Please note that Adobe is committed to accessibility, and if you require accommodation during the application process, you can reach out to accommodations@adobe.com or call (408) 536-3015.,

You should have a minimum of 5 - 8 years of experience in Data Science and Machine Learning. Your expertise should include in-depth knowledge of machine learning, Deep learning in Computer Vision (CV), and generative AI techniques. It is essential to be proficient in programming languages such as Python and frameworks like TensorFlow or PyTorch. A strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models is required. Experience with cloud platforms like Azure, AWS, or GCP and deploying AI solutions in a cloud environment is necessary. You should have expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, like fairness, transparency, and accountability in AI models and systems, is essential for this role. Collaborating with engineering teams to ensure seamless integration and deployment of AI models is crucial. Excellent problem-solving and analytical skills will be beneficial for translating business requirements into technical solutions. Strong communication and interpersonal skills are required to collaborate effectively with stakeholders at various levels. Understanding data privacy, security, and ethical considerations in AI applications is important. You should have a track record of driving innovation and staying updated with the latest trends in the field. Skills Required: - AI/ML, Machine Learning - TensorFlow, PyTorch - NLP techniques - BERT, GPT, Transformer models - Cloud Platforms: Azure, AWS, GCP - Data Engineering: data curation, cleaning, preprocessing - Trusted AI practices - Collaboration with engineering teams - Problem-solving and analytical skills - Communication and interpersonal skills - Data privacy, security, ethical considerations - Innovation and staying updated with the latest trends Mandatory Skills: - Generative AI techniques - NLP techniques - BERT, GPT, Transformer models - Azure Open AI GPT models, Hugging Face Transformers, Prompt Engineering - Python - TensorFlow, PyTorch - Deploying AI solutions in Azure, AWS, GCP - Deep learning in Computer Vision (CV), Large Language Model (LLM) Good To Have Skills: - DevOps and MLOps practices - Implementing CI/CD pipelines - Utilizing tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.,

AryaXAI stands at the forefront of AI innovation, revolutionizing AI for mission-critical, highly regulated industries by building explainable, safe, and aligned systems that scale responsibly. The mission of AryaXAI is to create AI tools that empower researchers, engineers, and organizations, including banks, financial institutions, and large enterprises, to unlock AI's full potential while maintaining transparency, safety, and regulatory compliance. The team at AryaXAI thrives on a shared passion for cutting-edge innovation, collaboration, and a relentless drive for excellence. Each team member contributes hands-on in a flat organizational structure that values curiosity, initiative, and exceptional performance, ensuring that the work not only advances technology but also meets the rigorous demands of regulated sectors. As a Senior Data Scientist at AryaXAI, you will be uniquely positioned to tackle large-scale, enterprise-level challenges in regulated environments. You will lead complex AI implementations that prioritize explainability, risk management, and compliance, directly impacting mission-critical use cases in the financial services industry and beyond. Your expertise will be crucial in deploying sophisticated models that address the nuances and stringent requirements of regulated sectors. Responsibilities include: - Model Evaluation & Customization - Architectural Assessment - Enterprise Integration - Advanced AI Techniques - Specialization & Innovation - Collaboration & Quality Assurance - Documentation & Compliance Qualifications: - Educational & Professional Background - Regulated Industry Experience (FS, Banking or Insurance is preferred) - Technical Expertise - Diverse Data Handling - Deployment Proficiency - Publications & Contributions A solid academic background in machine learning, deep learning, or reinforcement learning, ideally complemented by experience in regulated industries such as financial services or enterprise sectors, is required. The ideal candidate will have a proven track record (2+ years) of hands-on experience in data science within highly regulated environments, with a deep understanding of the unique challenges and compliance requirements in these settings. Demonstrated proficiency with deep learning frameworks (TensorFlow, PyTorch, etc.) and experience in implementing advanced techniques (Transformer models, GANs, etc.) is essential. Experience working with varied data types, including textual, tabular, categorical, and image data, and the ability to develop models that handle complex, enterprise-level datasets is also required. Expertise in deploying AI solutions in both cloud and on-premise environments, ensuring robust, scalable, and secure integrations with enterprise systems, is a key qualification. Peer-reviewed publications or significant contributions to open-source tools in AI are highly regarded.,

As a Firefly models & Services architect in the Adobe Firefly Gen AI Models and services group, you will play a crucial role in supporting the creation, improvement, and deployment of model pipelines for Adobe's top products across various domains. Your expertise in machine learning will be essential in designing and optimizing large-scale foundation model pipelines in Generative AI. You will collaborate with outstanding Applied researchers and engineers to bring innovative ideas to production, providing technical leadership and mentorship for junior team members. Your responsibilities will include designing and developing the GenAI backend services for Firefly, creating efficient model pipelines that power the generative AI features on various Adobe applications like PPro, Photoshop, Illustrator, Express, and Stock. You will lead the exploration and research of new ML and MLOps technologies to enhance Adobe's GenAI engineering effectiveness continuously. Your strong hands-on experience with large-scale GenAI model pipelines and collaboration skills will be key in driving alignment and achieving project goals within a Matrix organization. To succeed in this role, you should have a Master's or Ph.D. in Computer Science, AI/ML, or related fields, or a B.Tech with significant experience in AI/ML. With 12+ years of experience and at least 3 years as a Lead/Architect, you should possess excellent communication and technical leadership skills. Experience in the latest Generative AI technologies, such as GAN, diffusion, and transformer models, along with a track record of tech leading contributors on time-sensitive GenAI projects, will be advantageous. Preferred experience includes training or optimizing models using frameworks like CUDA, Triton, and TRT, as well as converting models from PyTorch and TensorFlow to other formats for optimized performance. A good publication record in Computer Science, AI/ML, or related fields is also beneficial. At Adobe, creativity, curiosity, and continuous learning are encouraged, offering you a unique career growth journey. Update your Resume/CV and Workday profile to showcase your Adobe experiences and volunteer work. Visit the Internal Mobility page on Inside Adobe to explore opportunities, and prepare for interviews by checking out helpful tips. Adobe provides an exceptional work environment, recognized globally, where ongoing feedback is valued through the Check-In approach. If you are driven to make an impact, Adobe is the place for you. Discover more about career experiences on the Adobe Life blog and explore the meaningful benefits offered. If you require accommodation to navigate the website or complete the application process due to a disability or special need, reach out to accommodations@adobe.com or call (408) 536-3015.,

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 a research scientist at AryaXAI, you will be part of a team that is revolutionizing the field of AI with a focus on building explainable, safe, and aligned systems at scale. Our mission is to empower researchers, engineers, and organizations to leverage AI effectively while prioritizing transparency and safety. Our team is driven by a shared passion for innovation, collaboration, and excellence. In our flat organizational structure, everyone contributes actively to our mission, valuing curiosity, initiative, and outstanding performance. In this role, you will tackle advanced challenges in ML explainability, safety, and alignment. You will have the flexibility to specialize in specific areas within ML/DL and address various problem types related to these challenges. Additionally, you will be involved in creating new techniques around ML Observability & Alignment, collaborating with MLEs and SDEs to implement features, ensuring their quality and stability, and managing technical and product documentation. To excel in this position, you should have a solid academic foundation in machine learning and deep learning concepts. Hands-on experience with deep learning frameworks like Tensorflow and PyTorch is essential. You should enjoy working on diverse DL problems that involve different types of training datasets such as textual, tabular, categorical, and images. Proficiency in deploying code in cloud/on-premise environments, strong fundamentals in MLOps, and prior experience with ML explainability methods like LRP, SHAPE, LIME, IG, CEM are required. Ideally, you should have at least 2 years of hands-on experience in Deep Learning or Machine Learning, along with practical experience in implementing techniques such as Transformer models, GANs, and other deep learning paradigms. Join us at AryaXAI where startup culture meets research innovation, driving speed and reliability in AI technologies.,

Chennai, India Role Overview We are looking for an exceptional ML Engineer who can help us to provide a great user experience while we wow our users with the power of AI for advanced document understanding. Strong working knowledge of using Python is critical for this position. This is an exciting opportunity to work closely with our platform team and help drive our technology forward bridging the gap between research & engineering in the field of machine comprehension. If you want to realign your career towards Machine Learning/Artificial Intelligence, look no further. This position offers an opportunity to work closely with best of minds in this field and to learn the tricks by doing amazing things along with them. In this role you will focus on developing engaging interfaces for our users, enhancing the AI experience they get in our platform. You will enable people by making their work of reading documents enjoyable through blending the power of AI with rich UX in our first of its kind DIY SaaS for advanced document understanding using AI. Qualifications Excellent problem-solving skills and critical thinking abilities. Solid experience in machine learning, deep learning, and large language models. Expert proficiency in Python. Familiarity with LLMs like Llama, Zephyr, Mistral, and OpenAI APIs. Experience with transformer models (BERT, GPT, RoBERTa, etc.). Knowledge of ML frameworks (PyTorch, Langchain, Spacy, etc.). MLOps infrastructure development experience. 2-5 years of experience in AI/ML in the software industry. Roles and Responsibilities Develop and Implement ML Models: Design, build, and deploy advanced machine learning models, with a focus on Large Language Models (LLMs) and Deep Learning Model Optimization: Fine-tune models to improve performance, latency, memory efficiency, and throughput. Software Development: Apply strong programming skills, particularly in Python, to create robust AI solutions. MLOps Infrastructure: Construct and manage infrastructure for ML experimentation, A/B testing, and production deployment. LLM Pipeline Development: Oversee LLM pipelines using frameworks like Langchain, LlamaIndex, etc. AI Solutioning: Collaborate with cross-functional teams to devise AI solutions for complex business challenges.,

Job Title: Senior AI Engineer LLM Infrastructure & Tooling Location: Remote / Hybrid / Onsite (as applicable) Experience: 7+ Years in Software Engineering | 1+ Year with LLMs in Production Key Responsibilities: Build core AI components (frontend & backend) including observability and feedback tools. Develop and optimize LLM-powered APIs , vector search tools, and orchestration workflows. Monitor performance, reliability, and safety of AI agents and design improvement feedback loops. Identify gaps in tooling and standardize best practices for deploying and maintaining AI services. Collaborate with product, infrastructure, and data teams to ensure reusability and scalability of AI solutions. Stay updated on emerging LLMs, retrieval methods, and modern deployment techniques. Must-Have Skills: 7+ years of hands-on software development experience, with 5+ years in building cloud-based web applications. 1+ year experience working with LLMs in production environments. Proficient in TypeScript or other typed programming languages. Solid understanding of transformer models , agent architectures , and attention mechanisms . Experience with cloud infrastructure and full-lifecycle AI/ML system deployment. Strong problem-solving and stakeholder communication skills. Good to Have: Experience with RAG systems , vector databases, chunking strategies. Familiarity with semantic search and LLM evaluation frameworks . Exposure to frontend development , particularly in scalable, modular AI interfaces. Background in documenting technical trade-offs and performance benchmarks.

Min 1-3 yrs of exp in data science,NLP&Python Exp in PyTorch,Scikit-learn,and NLP libraries(NLTK,SpaCy,Hugging Face) Help deploy AI/ML solutions on AWS,GCP/Azure Exp in SQL for data manipulation & analysis Exp in Big Data processing Spark,Pandas,Dask

Technical Skills Experience: Programming Languages: Proficiency in Python for AI/ML model development.. Machine Learning Deep Learning: Hands-on experience with TensorFlow and PyTorch for model training and deployment. Data Science Analytics: Strong knowledge of scikit-learn, NumPy, and pandas for data processing and manipulation. Natural Language Processing (NLP): Expertise in text preprocessing, tokenization, embeddings, and NLP techniques. Large Language Models (LLMs): Experience with transformer models like GPT, BERT, T5, and LLaMA, including fine-tuning and prompt engineering. Retrieval-AugmentedGeneration (RAG): Knowledge of RAG pipelines and experience with vector databases such as FAISS, Pinecone, or Chroma. Multi-Agent Systems: Familiarity with multi-agent frameworks like LangChain, LangGraph, or CrewAI. Data Handling Databases: Strong skills in data preprocessing, feature engineering, and working with SQL/NoSQL databases. API Development: Experience in building and deploying APIs using FastAPI, Flask, or Django. Version Control Collaboration: Strong understanding of Git/GitHub for version control and team collaboration. Hugging Face: Experience with Hugging Face for model training, deployment, and inference.

Job Summary: We are seeking a passionate and skilled AI Engineer to design, develop, and deploy cutting-edge AI solutions across domains such as large language models (LLMs), computer vision, and autonomous agent workflows. You will collaborate with data scientists, researchers, and engineering teams to build intelligent systems that solve real-world problems using deep learning, transformer-based architectures, and multi-modal AI models. Key Responsibilities: Design and implement AI/ML models, especially transformer-based LLMs (e.g., BERT, GPT, LLaMA) and vision models (e.g., ViT, YOLO, Detectron2). Develop and deploy computer vision pipelines for object detection, segmentation, OCR, and image classification tasks. Build and orchestrate intelligent agent workflows using prompt engineering, memory systems, retrieval-augmented generation (RAG), and multi-agent coordination. Fine-tune and optimize pre-trained models on domain-specific datasets using frameworks like PyTorch or TensorFlow. Collaborate with cross-functional teams to understand problem requirements and translate them into scalable AI solutions. Implement inference pipelines and APIs to serve AI models efficiently using tools such as FastAPI, ONNX, or Triton Inference Server. Conduct model evaluation, benchmarking, A/B testing, and performance tuning. Stay updated with state-of-the-art research in deep learning, generative AI, and multi-modal learning. Ensure reproducibility, versioning, and documentation of all experiments and production models. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 35 years of hands-on experience in designing and deploying deep learning models. Strong knowledge of LLMs (e.g., GPT, BERT, T5), Vision Models (e.g., CNNs, Vision Transformers), and Computer Vision techniques. Experience building intelligent agents or using frameworks like LangChain, Haystack, AutoGPT, or similar. Proficiency in Python, with expertise in libraries such as PyTorch, TensorFlow, Hugging Face Transformers, OpenCV, and Scikit-learn. Familiarity with MLOps concepts and deployment tools (Docker, Kubernetes, MLflow). Strong understanding of NLP, image processing, model fine-tuning, and optimization. Experience with cloud platforms (AWS, GCP, Azure) and GPU environments. Excellent problem-solving, communication, and teamwork skills. Preferred Qualifications: Experience in building multi-modal AI systems (e.g., combining vision + language models). Exposure to real-time inference systems and low-latency model deployment. Contributions to open-source AI projects or research publications. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG pipelines. Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India

Roles and Responsibilities Design, develop, and deploy advanced AI models with a focus on generative AI, including transformer architectures (e.g., GPT, BERT, T5) and other deep learning models used for text, image, or multimodal generation. Work with extensive and complex datasets, performing tasks such as cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training. Collaborate with cross-functional teams (e.g., product, engineering, data science) to identify project objectives and create solutions using generative AI tailored to business needs. Implement, fine-tune, and scale generative AI models in production environments, ensuring robust model performance and efficient resource utilization. Develop pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production. Stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability. Documentandcommunicatetechnicalspecifications, algorithms, and project outcomes to technical and non-technical stakeholders, with an emphasis on explainability and responsible AI practices. Qualifications Required Educational Background: Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field. Relevant Ph.D. or research experience in generative AI is a plus. Experience: 8-12 years of experience in machine learning, with 2+ years in designing and implementing generative AI models or working specifically with transformer-based models. Skills and Experience Required GenerativeAI: Transformer Models, GANs, VAEs, Text Generation, Image Generation Machine Learning: Algorithms, Deep Learning, Neural Networks Programming: Python, SQL; familiarity with libraries such as Hugging Face Transformers, PyTorch, Tensor Flow MLOps: Docker, Kubernetes, MLflow, Cloud Platforms (AWS, GCP, Azure) Data Engineering: Data Preprocessing, Feature Engineering, Data Cleaning Why you'll love working with us: Opportunity to work on technical challenges with global impact. Vast opportunities for self-development, including online university access and sponsored certifications. Sponsored Tech Talks &Hackathons to foster innovation and learning. Generous benefits package including health insurance, retirement benefits, flexible work hours, and more. Private and Confidential www.fissionlabs.com info@fissionlabs.com Supportive work environment with forums to explore passions beyond work. This role presents an exciting opportunity for a motivated individual to contribute to the development of cutting-edge solutions while advancing their career in a dynamic and collaborative environment.