17 Distributed Training Jobs

As a member of the AI Models team at AMD, you will have the opportunity to work on innovative training and inference techniques for large language models (LLMs), large multimodal models (LMMs), and image/video generation. You will be part of a world-class research and development team focused on efficient pre-training, instruction tuning, alignment, and optimization. Your contributions will play a significant role in shaping the direction and strategy of this important charter. This role is ideal for individuals who are passionate about staying updated on the latest literature, generating novel ideas, and implementing them through high-quality code to push the boundaries of scale and performance. The ideal candidate will possess both theoretical expertise and practical experience in developing LLMs, LMMs, and/or diffusion models. Familiarity with hyper-parameter tuning methods, data preprocessing & encoding techniques, and distributed training approaches for large models is crucial for success in this role. Key Responsibilities: - Pre-train and post-train models over large GPU clusters while optimizing for various trade-offs. - Enhance Generative AI model architectures, data, and training techniques to improve upon the state-of-the-art. - Accelerate training and inference speed across AMD accelerators. - Develop agentic frameworks to address diverse problem sets. - Disseminate research findings through publication at top-tier conferences, workshops, and technical blogs. - Engage with academia and open-source ML communities. - Drive continuous improvement of infrastructure and development ecosystem. Preferred Experience: - Proficient in Python with strong development and debugging skills. - Experience with deep learning frameworks such as PyTorch or TensorFlow and distributed training tools like DeepSpeed or PyTorch Distributed. - Familiarity with fine-tuning methods (e.g., RLHF & DPO) and parameter-efficient techniques (e.g., LoRA & DoRA). - Solid understanding of various transformers and state space models. - Demonstrated publication record in top-tier conferences, workshops, or journals. - Strong communication and problem-solving abilities. - Enthusiasm for continuous learning and innovation in the field. Academic Credentials: - Advanced degree (Masters or PhD) in machine learning, computer science, artificial intelligence, or related field is preferred. - Exceptional candidates with a Bachelor's degree may also be considered. Join us at AMD to be a part of a culture that values innovation, excellence, and diversity. Together, we advance the frontiers of technology and create products that impact the world.,

We are looking for a skilled and innovative Machine Learning Engineer with expertise in Large Language Models (LLMs) to join our team. The ideal candidate should have hands-on experience in developing, fine-tuning, and deploying LLMs, along with a deep understanding of the machine learning lifecycle. Your responsibilities will include developing and optimizing LLMs such as OpenAI's GPT, Anthropic's Claude, Google's Gemini, or AWS Bedrock. You will customize pre-trained models for specific use cases to ensure high performance and scalability. Additionally, you will be responsible for designing and maintaining end-to-end ML pipelines from data preprocessing to model deployment, optimizing training workflows for efficiency and accuracy. Collaboration with cross-functional teams, integration of ML solutions into production environments, experimentation with new approaches to improve model performance, and staying updated with advancements in LLMs and generative AI technologies will also be part of your role. You will collaborate with data scientists, engineers, and product managers to align ML solutions with business goals and provide mentorship to junior team members. The qualifications we are looking for include at least 5 years of professional experience in machine learning or AI development, proven expertise with LLMs and generative AI technologies, proficiency in Python (required) and/or Java (bonus), hands-on experience with APIs and tools like OpenAI, Anthropic's Claude, Google Gemini, or AWS Bedrock, familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face, and a strong understanding of data structures, algorithms, and distributed systems. Cloud expertise in AWS, GCP, or Azure, including services relevant to ML workloads such as AWS SageMaker and Bedrock, proficiency in handling large-scale datasets and implementing data pipelines, experience with ETL tools and platforms for efficient data preprocessing, strong analytical and problem-solving skills, and the ability to debug and resolve issues quickly are also required. Preferred qualifications include experience with multi-modal models, generative AI for images, text, or other modalities, understanding of ML Ops principles and tools like MLflow and Kubeflow, familiarity with reinforcement learning and distributed training techniques and tools like Horovod or Ray, and an advanced degree (Master's or Ph.D) in Computer Science, Machine Learning, or a related field.,

As a Senior Machine Learning Engineer at TrueFan in Gurugram, you will play a crucial role in designing, developing, and deploying cutting-edge models for end-to-end content generation using AI-driven technologies. Your responsibilities will include working on advanced generative models such as Diffusion Models, 3D VAEs, and GANs to create highly realistic AI-generated media. You will collaborate with software engineers to deploy models efficiently on cloud-based architectures and stay updated with the latest trends in deep generative models and transformer-based vision systems to enhance content quality. Your main responsibilities will revolve around designing and implementing state-of-the-art generative models, building AI pipelines for image/video generation and lipsyncing, developing lipsyncing and multimodal generation models for hyper-realistic content, implementing real-time content generation systems, and conducting experiments to evaluate and improve model performance. Additionally, you will participate in code reviews, improve model efficiency, and document research findings to enhance team knowledge-sharing and product development. To be successful in this role, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, along with at least 3 years of experience working with deep generative models like Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks such as PyTorch is essential. Strong problem-solving abilities, a research-oriented mindset, and familiarity with generative adversarial techniques, reinforcement learning, and large-scale AI model training are also required. Preferred qualifications include experience with transformers and vision-language models, a background in text-to-video and lipsync generation, familiarity with cloud-based AI pipelines, and contributions to open-source projects or published research in AI-generated content.,

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world's most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ THE ROLE: T he AI Models team is looking for exceptional machine learning scientists and engineers to explore and innovate on training and inference techniques for large language models (LLMs), large multimodal models (LMMs), image/video generation and other foundation models . You will be part of a world-class research and development team focussing on efficient and scalable pre-training, instruction tuning, alignment and optimization . As an early member of the team, you can help us shap e the direction and strategy to fulfill this important charter. THE PERSON: This role is for you if you are passionate about reading through the latest literature, coming up with novel ideas, and implementing those through high quality code to push the boundaries on scale and performance. The ideal candidate will have both theoretical expertise and hands-on experience with developing LLMs, LMMs, and/or diffusion models. We are looking for someone who is familiar with hyper-parameter tuning methods, data preprocessing & encoding techniques and distributed training approaches for large models. KEY RESPONSIBILITIES: Pre-train and post-train models over large GPU clusters while optimizing for various trade-offs . Improve upon the state-of-the- art in G enerat ive AI model architectures, data and training techniques. Accelerate the training and inference speed across AMD accelerators . Build agentic frameworks to solve various kinds of problems Publish your research at top-tier conferences, workshops and/ or through technical blogs. Engage with academia and open-source ML communities. Drive continuous improvement of infrastructure and development ecosystem. PREFERRED EXPERIENCE: Strong development and debugging skills in Python. Experience in deep learning frameworks ( like PyTorch or TensorFlow ) and distributed training tools (like DeepSpeed or Pytorch Distributed ) . Experience with fine-tuning methods (like RLHF & DPO) as well as parameter efficient techniques (like LoRA & DoRA). Solid understanding o f various types of transformer s and state space models . Strong publication record in top-tier conferences, workshops or journals. S olid communication and problem-solving skills. Passionate about learning new stuffs in this domain as well as innovating on top of it ACADEMIC CREDENTIALS: Advanced degree ( Master's or PhD) in machine learning, computer science, artificial intelligence, or a related field is expected. Exceptional Bachelor's degree candidates may also be considered . #LI-MK1 Benefits offered are described: . AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants needs under the respective laws throughout all stages of the recruitment and selection process.

We are seeking an experienced Gen AI and LLM Developer to design, develop, and deploy generative AI models and large language models (LLMs) for advanced natural language processing (NLP) tasks. The ideal candidate will have 6-9 years of experience with LLM architectures (e.g., GPT, BERT), deep learning frameworks (PyTorch, TensorFlow), and cloud platforms (AWS, GCP, Azure). Responsibilities include training and fine-tuning models, optimizing for performance, collaborating with cross-functional teams, and staying updated on the latest AI trends. Strong technical skills in Python, NLP techniques, model optimization, and distributed training are essential.Experience designing scalable system with Generative AI and Exposure to full stack development on .net or Java based platform

You will be part of our team as a Researcher at Infosys Applied AI research team. Your role will involve designing, developing, and training transformer-based models for multiple-modality to support various AI-powered applications. You will experiment with different architectures, training techniques, and optimization methods to enhance the models" understanding and generative capabilities. Additionally, you will be responsible for innovating robust and scalable architectures to meet future requirements and troubleshooting model issues to ensure their robustness and adaptability. To qualify for this position, you should have at least 8 years of experience and hold a Master's degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related fields (Ph.D. preferred). You must have proven experience in training models, particularly text and multi-modal models, along with a strong knowledge of transformer architectures and their underlying principles. Experience with model pre-training, fine-tuning, and distributed training is essential. Moreover, having one or more scientific publication submissions for conferences, journals, or public repositories (e.g., ICML, ICLR, NeurIPS) will be advantageous. By joining our team, you will have the opportunity to work on cutting-edge projects that are at the forefront of artificial intelligence. You will play a crucial role in contributing to groundbreaking advancements in NLP and AI while working in an innovative and dynamic environment. We offer competitive compensation and benefits package, along with a flexible work environment. While Bangalore is preferred, we are open to considering candidates from multiple locations in India.,

You will be joining a European-based MNC that is transitioning its operations to Bangalore in a Hybrid work mode. As part of the team, you will need to demonstrate expertise in Core Machine Learning & Deep Learning. This includes a solid grasp of Transformer architectures such as ViT, CLIP, and BERT, as well as experience with contrastive learning techniques like SimCLR, MoCo, and CLIP. Additionally, knowledge of temporal embeddings and sequence modeling for video, fine-tuning large pre-trained models, and a comprehensive understanding of Deep Learning concepts will be essential for this role. Your technical and engineering skills should include proficiency in Python and deep learning frameworks like PyTorch (preferred) or TensorFlow. Familiarity with StreetClip or similar multimodal models, experience with video data pipelines, and the ability to optimize model training and inference for performance and scalability will be key responsibilities. In terms of data and evaluation, you should have experience working with large-scale video datasets such as Kinetics, HowTo100M, etc. Knowledge of evaluation metrics for video understanding and retrieval tasks, familiarity with embedding spaces, similarity metrics, and retrieval systems will also be required. It would be beneficial to have experience with multimodal learning (vision + text), familiarity with distributed training and model deployment, as well as contributions to open-source projects or publications in relevant areas. Ideally, you should hold a degree in Computer Science, Machine Learning, or a related field (Masters or PhD preferred) and have at least 3 years of experience in deep learning or computer vision projects. If you meet these qualifications and skills, please share your profiles at hiring@khey-digit.com.,

As a Senior Machine Learning Engineer at TrueFan, you will be at the forefront of AI-driven content generation, leveraging cutting-edge generative models to build next-generation products. Your mission will be to redefine the content generation space through advanced AI technologies, including deep generative models, text-to-video, image-to-video, and lipsync generation. Your responsibilities will include designing, developing, and deploying cutting-edge models for end-to-end content generation. This will involve working on the latest advancements in deep generative modeling to create highly realistic and controllable AI-generated media. You will research and develop state-of-the-art generative models such as Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. Additionally, you will build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models. Furthermore, you will be responsible for developing advanced lipsyncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Your role will also involve implementing and optimizing models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques. Collaboration with software engineers to deploy models efficiently on cloud-based architectures will be a key aspect of your work. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, along with 3+ years of experience working with deep generative models like Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks such as PyTorch is essential. Strong problem-solving abilities, a research-oriented mindset, and familiarity with generative adversarial techniques are also required. Preferred qualifications include experience with transformers and vision-language models, background in text-to-video generation and lipsync generation, expertise in cloud-based AI pipelines, and contributions to open-source projects or published research in AI-generated content. If you are passionate about AI-driven content generation and have a strong background in generative AI, this is the perfect opportunity for you to drive research and development in AI-generated content and real-time media synthesis at TrueFan.,

As a Senior Machine Learning Engineer, you will have the exciting opportunity to be involved in designing, developing, and deploying cutting-edge models for end-to-end content generation. This includes working on AI-driven image/video generation, lip syncing, and multimodal AI systems. You will be at the forefront of the latest advancements in deep generative modeling, striving to create highly realistic and controllable AI-generated media. Your responsibilities will encompass researching and developing state-of-the-art generative models like Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. You will focus on building and optimizing AI pipelines for high-fidelity image/video generation and lip syncing. Additionally, you will be tasked with developing advanced lip-syncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Implementing and optimizing models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques will also be part of your role. Collaboration with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure) will be crucial. Staying updated with the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality will be an essential aspect of the role. Furthermore, designing and conducting experiments to evaluate model performance, improve fidelity, realism, and computational efficiency, as well as refining model architectures will be expected. Active participation in code reviews, improving model efficiency, and documenting research findings to enhance team knowledge-sharing and product development will also be part of your responsibilities. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field. You should have a minimum of 3 years of experience working with deep generative models, such as Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks like PyTorch is essential. Expertise in multi-modal AI, text-to-image, and image-to-video generation, as well as audio to lip sync, is required. A strong understanding of machine learning principles and statistical methods is necessary. It would be beneficial to have experience in real-time inference optimization, cloud deployment, and distributed training. Strong problem-solving abilities and a research-oriented mindset to stay updated with the latest AI advancements are qualities that would be valued. Familiarity with generative adversarial techniques, reinforcement learning for generative models, and large-scale AI model training will also be beneficial. Preferred qualifications include experience with transformers and vision-language models (e.g., CLIP, BLIP, GPT-4V), a background in text-to-video generation, lip-sync generation, and real-time synthetic media applications, as well as experience in cloud-based AI pipelines (AWS, Google Cloud, or Azure) and model compression techniques (quantization, pruning, distillation). Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis would be advantageous.,

As a Senior Machine Learning Engineer, your primary role will involve designing, developing, and deploying advanced models for end-to-end content generation. This includes AI-driven image/video generation, lip syncing, and multimodal AI systems. Your focus will be on leveraging cutting-edge deep generative modeling techniques to produce highly realistic and controllable AI-generated content. You will be responsible for researching and developing state-of-the-art generative models, such as Diffusion Models, 3D VAEs, and GANs, to power AI-driven media synthesis. Additionally, you will work on building and optimizing AI pipelines for high-fidelity image/video generation and lip syncing using diffusion and autoencoder models. Your expertise will also be utilized in developing advanced lip-syncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. In addition to model development, you will implement and optimize models for real-time content generation and interactive AI applications. Collaboration with software engineers to efficiently deploy models on cloud-based architectures (AWS, GCP, or Azure) will be a key aspect of your role. Staying updated on the latest trends in deep generative models, diffusion models, and transformer-based vision systems will be essential to enhance the quality of AI-generated content. Your responsibilities will include designing and conducting experiments to evaluate model performance, improve fidelity, realism, and computational efficiency. Participation in code reviews, enhancing model efficiency, and documenting research findings for team knowledge-sharing will also be part of your duties. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, along with at least 3 years of experience working with deep generative models. Proficiency in Python and deep learning frameworks like PyTorch is required. Expertise in multi-modal AI, text-to-image, image-to-video generation, and audio to lip sync is essential. A strong understanding of machine learning principles, statistical methods, and problem-solving abilities are also necessary. Additionally, experience with transformers, vision-language models, cloud-based AI pipelines, and model compression techniques is advantageous. Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis will be beneficial. This position offers a dynamic opportunity to work on cutting-edge AI technologies and collaborate with a team of experts in the field. If you are passionate about pushing the boundaries of AI-generated content and staying at the forefront of AI advancements, this role is ideal for you.,

As a senior engineer at NVIDIA, you will be at the forefront of groundbreaking developments in High-Performance Computing, Artificial Intelligence, and Visualization. Your role will involve understanding, analyzing, profiling, and optimizing deep learning workloads on cutting-edge hardware and software platforms. You will collaborate with cross-functional teams to enhance cloud application performance on diverse GPU architectures and identify bottlenecks for optimization. Your responsibilities will include building tools to automate workload analysis, optimization, and other critical workflows. You will drive platform optimization from hardware to application levels and design performance benchmarks to evaluate application efficiency. Your expertise in deep learning model architectures, Pytorch, and large-scale distributed training will be essential in proposing optimizations to enhance GPU utilization. To excel in this role, you should hold a Masters in CS, EE, or CSEE, or possess equivalent experience with at least 5 years in application performance engineering. Experience with large-scale multi-node GPU infrastructure, application profiling tools, and a deep understanding of computer architecture is required. Proficiency in Python and C/C++ for analyzing and optimizing application code is also crucial. Standing out from the crowd can be achieved through strong fundamentals in algorithms, GPU programming experience, and hands-on experience in performance optimization on distributed systems. An understanding of NVIDIA's server and software ecosystem, coupled with expertise in storage systems, Linux file systems, and RDMA networking will set you apart. Join NVIDIA, a leading technology company driving the AI revolution, and play a direct role in shaping the hardware and software roadmap while impacting deep learning users globally. If you are a creative and autonomous individual who is unafraid to push the boundaries of performance analysis and optimization, we invite you to be part of our innovative team. JR1986479,

As a senior engineer at NVIDIA, you will play a crucial role in the optimization of deep learning workloads on cutting-edge hardware and software platforms. Your primary responsibility will be to understand, analyze, and profile these workloads to achieve peak performance. By building automated tools for workload analysis and optimization, you will contribute to enhancing the efficiency of GPU utilization and cloud application performance across diverse GPU architectures. Collaboration with cross-functional teams will be essential as you identify bottlenecks and inefficiencies in application code, proposing optimizations to drive end-to-end platform optimization. Your role will involve designing and implementing performance benchmarks and testing methodologies to evaluate application performance accurately. To qualify for this role, you should hold a Master's degree in CS, EE, or CSEE, or possess equivalent experience. With at least 5 years of experience in application performance engineering, you are expected to have a background in deep learning model architectures, proficiency in tools such as NVIDIA NSight and Intel VTune, and a deep understanding of computer architecture and GPU fundamentals. Proficiency in Python and C/C++ will be essential for analyzing and optimizing application code effectively. To stand out from the crowd, strong fundamentals in algorithms and GPU programming experience (CUDA or OpenCL) will be highly beneficial. Hands-on experience in performance optimization and benchmarking on large-scale distributed systems, familiarity with NVIDIA's server and software ecosystem, and expertise in storage systems, Linux file systems, and RDMA networking will further distinguish you as a top candidate. Joining NVIDIA means being part of a dynamic team that leads the AI revolution, offering you the opportunity to directly impact the hardware and software roadmap in a fast-growing technology company. If you are unafraid to tackle challenges across the hardware/software stack and are passionate about achieving peak performance in deep learning workloads, we want to hear from you.,

You should have a B.Tech, M.Tech, or higher degree in Computer Engineering, Computer Science, Electronics, Robotics Engineering, or related fields. Your written and verbal communication skills should be strong, and you should possess excellent problem-solving abilities. Proficiency in C++ for robotics and machine perception, along with knowledge in data structures and algorithms, is required. Extensive experience with OpenCV, PCL, and ROS2 is essential. You should be well-versed in Modern C++ with a deep understanding of features like RAII, STL, templates, etc. Experience in implementing Deep Learning Algorithms on GPU cluster for tasks like object detection and segmentation is necessary. Familiarity with Unix/Linux environments is a must, and you should be capable of developing software for real-time processing of sensor data from cameras, LIDAR, and other sensors. Your responsibilities will include building robust solutions to cutting-edge Autonomous driving problems and developing advanced algorithms for tasks like object detection, tracking, multi-task learning, distributed training, and multi-sensor fusion. Experience with developing production-ready software is a plus, along with maintaining large-scale libraries and working with parallel computing libraries like TBB and CUDA. Additional desirable qualifications include familiarity with linear algebra libraries such as Eigen, machine learning, software version management tools like Git, and agile development workflows and CI/CD processes.,

Job Description: Strategic Technology Group is a core team within Infosys supported by Power Programmers who are tech polyglots Our team of Power Programmers works on complex projects and builds solutions to solve some of the world s most challenging business problems Introduction We are looking for a passionate and talented Researcher to join Infosys Applied AI research team As an Researcher you will work on architecting building refining and optimizing state of the art Models that drive cutting edge multi modal multi domain understanding and generation capabilities If you have experience building LLM SLM Multimodal models we would love to hear from you Why Join Us Work with an innovative team on cutting edge projects that are pushing the boundaries of artificial intelligence Opportunity to grow professionally and contribute to groundbreaking advancements in NLP and AI Competitive compensation and benefits package Bangalore preferred Flexible work environment with remote work options available Key Responsibilities: Design develop and train transformer based models for multiple modality to support a variety of AI powered applications Experiment with various architectures training techniques and optimization methods to improve the model s understanding and generative capabilities Innovate robust and scalable architectures to accommodate the future requirements Troubleshoot and debug model issues ensuring the models remain robust and adaptable Technical Requirements: We are looking for a passionate and talented Researcher to join Infosys Applied AI research team As an Researcher you will work on architecting building refining and optimizing state of the art Models that drive cutting edge multi modal multi domain understanding and generation capabilities If you have experience building LLM SLM Multimodal models we would love to hear from you Additional Responsibilities: Master s degree or PhD in Computer Science Artificial Intelligence Machine Learning or related fields Ph D preferred Proven experience in training models both text and multi modal models Strong knowledge of transformer architectures and their underlying principles Experience with model pre training finetuning and distributed training One or more scientific publication submissions for conferences journals or public repositories e g ICML ICLR NeurIPS Preferred Skills: Technology->Artificial Intelligence->Artificial Intelligence - ALL

Role & Responsibilities Conduct original research on AI applications, focusing on machine learning algorithms and data-driven methodologies. Design, implement, and evaluate innovative algorithms to solve complex problems in various domains. Collaborate with cross-functional teams to integrate research findings into production systems and prototypes. Analyze and interpret large datasets to extract meaningful insights and validate research hypotheses. Stay current with the latest developments in the AI field and contribute to scholarly publications. Mentor junior researchers and contribute to a collaborative and stimulating research environment. Skills & Qualifications Must-Have Master's degree or PhD in Computer Science, Artificial Intelligence, or related field. Strong knowledge of machine learning and AI algorithms. Proficiency in Python programming for AI applications. Experience in statistical modeling and data analysis techniques. Hands-on experience with natural language processing (NLP) methods. Preferred Familiarity with deep learning frameworks such as TensorFlow or PyTorch. Experience in conducting peer-reviewed research and publications. Excellent problem-solving skills and creativity. Benefits & Culture Highlights Collaborative and innovative work environment that nurtures creativity. Opportunities for professional development and continuous learning. Supportive team culture valuing diversity and inclusion.

IBM Research is the innovation and growth engine of the IBM corporation. It is the largest industrial research organization in the world with 12 labs on 6 continents. IBM Research produces more breakthroughsmore than 9 patents are produced every daythan any other organization in the world. IBM employs over 3200 researchers worldwide. IBM Research India (IRL) is the leading industrial research lab in India, shaping the future of computing across AI, Hybrid Cloud and Quantum Computing. IRL has a long legacy of ground-breaking innovation in the areas of computer science and its applications to a wide variety of disciplines and offerings for IBM. IRL researchers are working on projects that are pushing the state of the art across Foundation Models, optimized runtime stacks for FM workloads such as tuning, large scale data engineering and pre-training, multi-accelerator model optimization, agentic workflows and modalities across language, code, time series, IT automation and geospatial. We are strong proponents of open-source community-driven software and model development, and our work spans a wide spectrum from research collaborations with academia to developing enterprise-grade commercial software. Your role and responsibilities Research Engineer position at IBM India Research Lab is a challenging, dynamic and highly innovative role. Some of our current areas of work where we are actively looking for top talent are: Optimized runtime stacks for foundation model workloads including fine-tuning, inference serving and large-scale data engineering, with a focus on multi-stage tuning including reinforcement learning, inference-time compute, and data preparation needs for complex AI systems. Optimizing models to run on multiple accelerators including IBM's AIU accelerator leveraging compiler optimizations, specialized kernels, libraries and tools. Developing use cases that effectively leverage the infrastructure and models to deliver value Pre-training language and multi-modal foundation models working with large scale distributed training procedures, model alignment, creating specialized pipelines for various tasks including effective LLM-generated data pipelines, creating frameworks for collecting human data and deploying models in user-centric platforms. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise You should have one or more of the following: A master's degree in computer science, AI or related fields from a top institution 0-8 years of experience working with modern ML techniques including but not limited to model architectures, data processing, fine-tuning techniques, reinforcement learning, distributed training, inference optimizations Experience with big data platforms like Ray and Spar Experience working with Pytorch FSDP and HuggingFace libraries Programming experience in one of the following: Python, web development technologies Growth mindset and a pragmatic attitude Preferred technical and professional experience Peer-reviewed research at top machine learning or systems conferences Experience working with pytorch.compile, CUDA, triton kernels, GPU scheduling, memory management Experience working with open-source communities

The Oracle Global Business Unit (GBU) Generative AI team is responsible for leading Generative AI and Agent needs of business applications serving variety of markets including Finance, Hospitality, Construction and Engineering, Energy & Water etc. Our goal is to enable customers to apply AI to solve their business problems with Oracle's assistance and expertise in Generative AI. In this role, you will have an opportunity to work with teams of applied scientists and engineers to deliver high quality generative ai and agent features that delights our customers with the confidence that their data are safe and protected. Your Opportunity We are seeking a Principal Applied Scientist (IC4) to spearhead Generative AI and Agent use cases that support GBU business applications as well as GBU consulting. As an applied scientist, you will be responsible for driving the development and implementation of cutting-edge technologies.We are building a core talented team specialized in Generative AI. We are looking for candidates who are passionate about building state-of-the-art technologies to solve real-world problems and have a solid technical background in deep learning, especially natural language processing (NLP) and multimodal models, to join this team. You will collaborate with a team of world-class scientists, engineers and product managers.We're looking for a person who will bring a passion for innovative products, strong collaboration skills and the ability to work closely with both development and consulting teams. You'll be a Generative AI expert who is hands-on as well as be adept at evangelizing and influencing multiple stakeholders without direct authority on best practices and to get things done efficiently. Most importantly - we believe in a people-first approach. Our team consists of people from a wide variety of backgrounds, with different professional and life experiences, who support each other to build things the right way and enjoy ourselves while doing it. What we offer Being part of one of the most visionary and mission-driven organizations in Oracle, cooperating with talented peers with diverse backgrounds worldwide. High visibility to senior leadership, as well as technical leaders and partners. Opportunity to build state-of-the-art technologies in large language models and generative AI at scale. Close partnership with product managers and software engineers to deploy Generative AI features into products in various business-critical scenarios. Building performance evaluations of Generative AI systems for continuous improvement of alignment with stakeholders growing expectations. What You'll Do Develop, implement, and optimize large language models and generative AI technologies, including training/finetuning and computation optimizations. Collaborate with software engineers to deploy LLM / Generative AI models and Agents into production environments. Stay up-to-date with the latest advancements in the field of generative AI. Collaborate with cross-functional teams to drive the development and adoption of LLM and generative AI solutions across various organizations in the company. Work directly with key customers and accompany them on their AI journey - understanding their requirements, help them envision and design the right solutions and work together with their engineering and data science team to remove blockers and translate the feedback into actionable items for individual service owners. Design and build solutions and help GBU development teams reach successful pilots, PoCs and feature releases with our AI/Gen AI and DS technologies. Bring back learnings from these engagements to standardize Generative AI and Agent implementations for efficiency, scale and ease of maintenance. Support GBU consulting with re-usable solution patterns and reference solutions / showcases that can apply across multiple customers. Being enthusiastic, self-motivated, and a great collaborator. Lead patent filings and author papers to show innovative enterprise grade developments. Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc. Qualifications: PhD, MS in computer science, engineering, mathematics or a field related to deep learning. Strong knowledge of ML fundamentals - supervised vs unsupervised modeling, time series, highly unbalanced and noisy data sets, complex feature engineering, recommendation systems, using and optimizing gradient boosting models, NLP, deep learning on all kinds of unstructured data. 5+ (for Senior), 7+ (for Principal), 10+ (for Sr Principal) years of work experience including a minimum of 2-year experience in developing large-scale ML solutions, and in particular deep learning solutions in the NLP field. Proficiency with deep learning frameworks (such as PyTorch or TensorFlow) and deep learning architectures (especially Transformers). Hands-on experience with distributed training of large language models. Strong development experience of deep learning modeling in Python. Familiarity with the latest advancements in LLM and generative AI technologies. Familiarity with engineering best practices, including shared codebase, version control, containerization, etc. Passionate about being a builder and working with talented peers to solve hard problems at scale. Good communication skills to convey technical concepts in straightforward terms with product managers and various stakeholders. Preferred Skills Publications in top-tier deep learning conferences or significant contributions to prominent deep learning repositories Industrial experience in system design, software development, and production deployment Excel in transforming ambiguous requirements into actionable plans with deep learning techniques for problem-solving. First-hand experience with deep reinforcement learning First-hand experience with the latest technologies in LLM and generative AI such as parameter-efficient finetuning and instruction finetuning is a plus Familiarity with the latest advancements in computer vision and multimodal models is a plus Top-tier performance in prestigious deep learning leaderboards or large model-related competitions is a plus. Career Level - IC5 Drives and plans implementation of company policy for achieving business goals. Defines the bar for science practices, and helps teams achieve those goals. Identifies and mitigates risks across full set of systems, particularly at the intersection of business and engineering. Innovate AI and ML powered solutions (rich APIs, ML models and end to end services) with strategic ISVs and customers. Develop deep product intuition to influence future product roadmaps and drive decision making. Clearly articulate technical work to audiences of all levels and across multiple functional areas in both internal and external settings. Engage in forward looking research both internal and with academic institutions globally. Hires and mentors across the org. Perform an active role in team planning, review and retrospective events. Ensures experiments are ready for hand-off to Software Developers ship into production. May perform other duties as assigned.