7 Llm Training Jobs

You are an experienced Tech Lead with 3+ years of software development experience, seeking to drive the development of cutting-edge AI-powered applications. As the Tech Lead AI & Full Stack Development, you will play a crucial role in designing, developing, and deploying AI agents, training Large Language Models (LLMs), and leading a team in building scalable full-stack applications. Your expertise in OpenAI, JavaScript (ReactJS, Node.js), cloud infrastructure (GCP), and relational databases (MongoDB, SQL) will be instrumental in shaping innovative AI-driven solutions. In this role, you will be responsible for guiding and mentoring a team of developers to ensure best practices in coding, architecture, and AI development. You will work on training and fine-tuning Large Language Models (LLMs) using OpenAI and other frameworks, as well as designing and implementing AI agents for automation, decision-making, and NLP-based solutions. Additionally, you will be involved in building and optimizing web applications using ReactJS, MongoDB, or SQL-based relational databases. Your role will also require experience with Google Cloud Platform (GCP), AWS, or Azure for cloud-based deployment and infrastructure management. You will design efficient database schemas using MongoDB (NoSQL) or SQL-based relational databases to ensure data integrity and performance. Collaboration with cross-functional teams to integrate AI capabilities into enterprise solutions will be a key aspect of your responsibilities. Moreover, you will be responsible for ensuring high-quality code through reviews, documentation, and adherence to software development standards. The ideal candidate will have proficiency in JavaScript (ReactJS, Node.js) for building scalable front-end and back-end applications, hands-on experience with OpenAI APIs and fine-tuning LLMs (GPT, BERT, etc.), and strong knowledge of AI agent development, prompt engineering, and NLP solutions. Expertise in MongoDB (NoSQL) or SQL-based relational databases, as well as experience with GCP services such as Cloud Functions, Firestore, BigQuery, and AI/ML tools or Azure will be essential for this role. A strong understanding of API development, microservices architecture, and cloud-native applications is required, with experience in DevOps, CI/CD, and containerization (Docker, Kubernetes) being a plus. If you have any queries or require further information, please feel free to reach out to Kirthi at 8431429375.,

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider-of-choice for 4 out of 5 of the worlds biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine. By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, were helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms. Our global workforce includes over 5,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. About the role: We are seeking a highly analytical and detail-oriented linguist to support AI training initiatives and linguistic content creation. This role is ideal for someone with a strong academic background in linguistics (syntax, semantics, pragmatics, morphology, phonology, sociolinguistics, etc.) and a passion for language, technology, and clear communication. You will play a crucial role in shaping the capabilities of large language models (LLMs) and NLP-based systems through high-quality linguistic data curation, annotation, and evaluation. Job Title: Linguistics Expert AI Training & Content Writing Experience Level: Degree in Linguistics or a related field Key Responsibilities: Create or edit linguistically- rich content including grammar guides, syntactic analyses, usage explanations, or examples for NLP pipelines. Identify and resolve issues related to ambiguity, bias, and grammaticality. Perform quality assurance (QA) on model outputs for fluency, tone, factual accuracy, and language appropriateness. Annotate linguistic datasets with syntactic, semantic, or pragmatic labels. Support internal teams by conducting linguistic research and summarizing findings. Apply linguistic knowledge to evaluate model behavior, error patterns, and generalization issues. Qualifications: Degree in Linguistics, Applied Linguistics, Computational Linguistics, or a related field. Deep understanding of linguistic theory and language structure. Experience with one or more of the following is a plus: computational linguistics, corpus analysis, language data annotation, LLM training. Strong writing, editing, and communication skills. Show more Show less

About the role: We are seeking a highly analytical and detail-oriented linguist to support AI training initiatives and linguistic content creation. This role is ideal for someone with a strong academic background in linguistics (syntax, semantics, pragmatics, morphology, phonology, sociolinguistics, etc.) and a passion for language, technology, and clear communication. You will play a crucial role in shaping the capabilities of large language models (LLMs) and NLP-based systems through high-quality linguistic data curation, annotation, and evaluation. Job Title: Linguistics Expert AI Training & Content Writing Experience Level: Master&aposs or PhD in Linguistics or a related field Key Responsibilities: Create or edit linguistically- rich content including grammar guides, syntactic analyses, usage explanations, or examples for NLP pipelines. Identify and resolve issues related to ambiguity, bias, and grammaticality. Perform quality assurance (QA) on model outputs for fluency, tone, factual accuracy, and language appropriateness. Annotate linguistic datasets with syntactic, semantic, or pragmatic labels. Support internal teams by conducting linguistic research and summarizing findings. Apply linguistic knowledge to evaluate model behavior, error patterns, and generalization issues. Qualifications: Deep understanding of linguistic theory and language structure. Experience with one or more of the following is a plus: computational linguistics, corpus analysis, language data annotation, LLM training. Strong writing, editing, and communication skills. Show more Show less

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with deep expertise in training Large Language Models (LLMs) and building Retrieval-Augmented Generation (RAG) workflows. As a key member of our AI Solutions team, you'll drive innovation and impact in real-world deployments of cutting-edge generative AI technology. What You Will Be Doing Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows. Collaborate with customers to understand business problems and translate them into tailored LLM-based solutions. Design and lead workshops and technical sessions to define, optimize, and deploy RAG-based and LLM-powered systems. Train and fine-tune state-of-the-art LLMs on NVIDIA platforms, optimizing for performance, cost, and efficiency. Deploy and integrate LLMs and RAG workflows in cloud and on-premise environments, enabling real-world applications. Work closely with NVIDIA engineering and product teams, influencing the evolution of generative AI tools and technologies. Build and share best practices for model training, deployment, and performance optimization using NVIDIA GPUs and AI platforms. What We Need To See Master's or Ph.D. in Computer Science, AI, or a related field 5+ years of hands-on experience with LLM training, deployment, and production optimization Deep understanding of language models like GPT-3, BERT, and experience with RAG Proficient in PyTorch, TensorFlow, and Hugging Face Transformers Familiar with GPU acceleration, distributed computing, and inference tuning on NVIDIA hardware Experience presenting to clients and leading cross-functional collaboration Strong communication skillsable to clearly explain technical details to diverse audiences Ways To Stand Out From The Crowd Experience deploying LLMs in cloud (AWS, Azure, GCP) and on-prem clusters Proficiency with Docker, Kubernetes, and GPU cluster management Proven ability to optimize LLM inference for speed, memory, and cost Hands-on experience with NVIDIA GPU technologies, profiling, and distributed model execution If you're passionate about the future of AI and want to help define how organizations use LLMs at scale, we want to hear from you. NVIDIA is widely considered one of the most desirable employers in techjoin us in shaping what's next. We are an equal opportunity employer and committed to diversity in our workforce.

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with deep expertise in training Large Language Models (LLMs) and building Retrieval-Augmented Generation (RAG) workflows. As a key member of our AI Solutions team, you'll drive innovation and impact in real-world deployments of cutting-edge generative AI technology. What You Will Be Doing Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows. Collaborate with customers to understand business problems and translate them into tailored LLM-based solutions. Design and lead workshops and technical sessions to define, optimize, and deploy RAG-based and LLM-powered systems. Train and fine-tune state-of-the-art LLMs on NVIDIA platforms, optimizing for performance, cost, and efficiency. Deploy and integrate LLMs and RAG workflows in cloud and on-premise environments, enabling real-world applications. Work closely with NVIDIA engineering and product teams, influencing the evolution of generative AI tools and technologies. Build and share best practices for model training, deployment, and performance optimization using NVIDIA GPUs and AI platforms. What We Need To See Master's or Ph.D. in Computer Science, AI, or a related field 5+ years of hands-on experience with LLM training, deployment, and production optimization Deep understanding of language models like GPT-3, BERT, and experience with RAG Proficient in PyTorch, TensorFlow, and Hugging Face Transformers Familiar with GPU acceleration, distributed computing, and inference tuning on NVIDIA hardware Experience presenting to clients and leading cross-functional collaboration Strong communication skillsable to clearly explain technical details to diverse audiences Ways To Stand Out From The Crowd Experience deploying LLMs in cloud (AWS, Azure, GCP) and on-prem clusters Proficiency with Docker, Kubernetes, and GPU cluster management Proven ability to optimize LLM inference for speed, memory, and cost Hands-on experience with NVIDIA GPU technologies, profiling, and distributed model execution If you're passionate about the future of AI and want to help define how organizations use LLMs at scale, we want to hear from you. NVIDIA is widely considered one of the most desirable employers in techjoin us in shaping what's next. We are an equal opportunity employer and committed to diversity in our workforce.

As an Engineering Lead at Bolo AI, a company dedicated to utilizing AI to optimize Energy processes, you will play a crucial role in expanding the engineering team and overseeing the delivery of cutting-edge products focused on Generative AI systems. Your responsibilities will encompass managing a talented group of applied scientists, MLOps engineers, and backend developers who are dedicated to developing high-performance platforms for LLM training, RAG, LLM agent orchestration, and enterprise deployments. Your primary objective will be to ensure that the team collaborates effectively to deliver top-tier products within set timelines and with exceptional quality standards. You will be instrumental in driving product excellence, facilitating the swift introduction of new features, functionalities, and AI-driven solutions for our valued customers. Moreover, you will be tasked with defining the technical roadmap, establishing operational frameworks, and upholding engineering standards. Reporting to the CTO and closely working with the CEO, you will engage with research and product teams to shape the company's trajectory and achieve tangible outcomes through state-of-the-art AI technologies. Key Responsibilities: - Architecting scalable and high-performance systems to support LLM pipelines, RAG infrastructure, and agentic workflows - Building, nurturing, and expanding a top-tier engineering team spanning platform engineering, ML infra, and backend systems - Overseeing the end-to-end delivery process of mission-critical AI products from conceptualization to deployment - Collaborating effectively with founders, research scientists, and product managers to align on technical strategies and business objectives - Establishing best practices in software development, MLOps, DevSecOps, and system design to ensure code quality and architectural integrity - Spearheading initiatives to enhance system performance, optimize LLM inference efficiency, and drive cost efficiencies across cloud environments - Engaging with enterprise clients and partners to comprehend requirements, solicit feedback, and facilitate solution delivery Qualifications: - Over 10 years of engineering experience with a minimum of 5 years in building and leading engineering teams, ideally in dynamic startup environments - Profound expertise in constructing production ML systems, encompassing model training, optimization, and large-scale deployment (LLM, RAG, agents, classification, etc.) - Strong background in backend and systems engineering with proficiency in Python and microservice architecture - Prior exposure to hybrid deployments (on-prem, VPC) and cloud-native infrastructure (AWS, GCP, Azure) - Demonstrated ability to scale engineering organizations, implement processes, and drive cross-functional collaborations - Passion for addressing real-world challenges using innovative ML and AI solutions - Educational background in Computer Science or related field (M.Tech/MS/PhD), with preference for candidates from esteemed institutions like IIT/NIT/BITS Desirable Skills: - Familiarity with CPU- and GPU-optimized ML inference frameworks such as BOLT, TorchScript, Triton, ONNX, or vLLM - Proficiency in LLM training methodologies (e.g., LoRA, QLoRA, RLHF, MoE), LLM Agents, multilingual NLP, or recommendation systems - Track record of publications in renowned ML/NLP conferences or patents in the AI/ML domain - Previous involvement in startup environments, particularly within the enterprise or SaaS sectors Join us at Bolo AI for: - Competitive Compensation: A competitive base salary - Ownership & Impact: Equity options to participate in our growth and success - Hybrid Work Environment: Flexibility to collaborate in-person and work remotely to ensure work-life balance - Growth & Opportunity: Engage in a pivotal stage where your contributions will shape our journey and unlock new opportunities - Culture of Respect & Collaboration: Join a team that values humility, respect, and teamwork, celebrating collective achievements.,

Strong experience with vLLM, HuggingFace Transformers, LoRA/QLoRA, and cybersecurity data— MITRE ATT&CK, CVE/NVD, YARA rules, Snort/Suricata rules, STIX/TAXII, or malware datasets, Python, ML libraries (PyTorch, Transformers), and MLOps practices.