3 Research Engineer Jobs

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

Process, Research Engineer, , Industry - zinc, copper, gold, silver. Lab Experience a plus worked in refining process industry only, prefer from Birla Copper, Hindustan Zinc, Hindustan Platinum, Bangalore Refinery, Reliance Refinery for global co.

Key Responsibilities: Develop advanced computer vision and state-of-the-art deep learning models to understand software applications and derive user intent. Research and implement ML and deep learning algorithms for production use. Build and maintain infrastructure for AI/ML systems, including model inference, automated (re-)training, monitoring, explainability, and more. Stay updated on cutting-edge AI research from leading labs by reading papers and experimenting with code. Assist AI product managers and business stakeholders in understanding the capabilities and limitations of AI for the products. Fine-tune, retrain, and scale existing model deployments. Conduct necessary ML tests and benchmarks for model validation. Our Ideal candidate: Experience: 4+ years of expertise in machine learning. Deep Learning Expertise: Strong understanding of deep learning principles in both Computer Vision and Natural Language Processing (NLP). LLM Knowledge: Familiarity with LLM architectures like BERT and GPT, with hands-on experience fine-tuning these models for enhanced performance. Model Development: Proven experience in developing deep learning models, such as CNNs and Vision Transformers, for image-based tasks in production systems. Research and Application: Extensive experience in algorithms for image processing, content-based video/image analysis, object detection, segmentation, and tracking. Libraries: Proficiency in machine learning and deep learning libraries like PyTorch and Hugging Face. Technical Skills: Demonstrated ability to implement, improve, debug, and maintain machine learning models. Nice to Have: Strong programming skills in Python. Expertise in optimization and debugging. Familiarity with version control systems such as Git. Self-motivated and responsible, with excellent written and verbal communication skills. Experience in handling and visualizing large datasets and creating performance reports.