1,516 Large Language Models jobs in India

• Develop, train, and deploy machine learning models for Natural Language Processing tasks.
• Implement NLP algorithms for text classification, sentiment analysis, named entity recognition, machine translation, and question answering.
• Preprocess and clean large volumes of text data for model training.
• Design and perform experiments to evaluate and improve model performance.
• Tune hyperparameters and optimize model architectures for efficiency and accuracy.
• Collaborate with software engineers to integrate ML models into production systems.
• Stay current with state-of-the-art research and techniques in NLP and ML.
• Write clean, maintainable, and well-documented code.
• Contribute to the design and development of AI-powered features and products.
• Present findings and results to both technical and non-technical stakeholders.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field with a specialization in NLP.
• Proven experience in developing and deploying NLP models in a production environment.
• Proficiency in Python and key NLP libraries (e.g., NLTK, spaCy, Hugging Face Transformers).
• Strong experience with machine learning frameworks such as TensorFlow or PyTorch.
• Solid understanding of deep learning architectures (e.g., RNNs, LSTMs, Transformers).
• Experience with data preprocessing and feature engineering techniques for text data.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration skills for remote teamwork.
• Ability to work independently and manage project timelines effectively.

• Design, develop, and implement state-of-the-art NLP models for tasks such as text classification, sentiment analysis, named entity recognition, question answering, and machine translation.
• Preprocess and clean large volumes of text data, ensuring its suitability for model training.
• Train, evaluate, and fine-tune machine learning models using various frameworks and libraries.
• Deploy NLP models into production environments, ensuring scalability, reliability, and performance.
• Collaborate with software engineers to integrate NLP capabilities into existing applications and platforms.
• Conduct research on new NLP techniques and algorithms, evaluating their potential applications.
• Analyze model performance, identify areas for improvement, and implement necessary optimizations.
• Stay abreast of the latest research papers, industry trends, and advancements in NLP and deep learning.
• Work with large datasets and distributed computing frameworks.
• Document models, algorithms, and experimental results clearly and concisely.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field.
• Minimum of 4-7 years of experience in machine learning, with a specialization in Natural Language Processing.
• Strong proficiency in Python and experience with ML/DL frameworks such as TensorFlow, PyTorch, or Keras.
• Deep understanding of NLP techniques, including tokenization, stemming, lemmatization, word embeddings (Word2Vec, GloVe), and transformer models (BERT, GPT).
• Experience with libraries like NLTK, SpaCy, Hugging Face Transformers.
• Proven ability to develop, train, and deploy ML models in production.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills, with the ability to explain complex technical concepts.

Job description

A job where you increase the depth of your expertise in computer vision.

A job where you learn and implement the SOTA papers.

A job where you write vectorized code that runs in seconds, not in minutes.

A job where models learn to see and understand the world around them.

A job where models run real-time because you optimize every byte.

A job where you keep the career promises that you made to yourself.

A job where you keep the learning promises that you made to yourself.

If this scares you, don't read. If this excites you, we might love you.

We are looking for a passionate Machine Learning Engineer to join our team. The ideal candidate will be an enthusiastic developer with 3-5 years of experience in the field of Computer Vision and Artificial Intelligence. If building things and writing code excite you, this is the startup you belong.

Key Technologies:

• Must be an expert in Python and Numpy.
• Experience with Tensorflow/Keras/Pytorch is required.
• Unsatiable hunger for writing beautiful code.
• Knowledge of python design-patterns.
• Some experience with C++ is preferred.
• Knowledge working closely with version control (GIT).
• Excellent communication skills and being able to work independently.
• Strong problem-solving and coding skills override everything else written above.

About AIMonk:

Run by IIT Kanpur alumni, AIMonk is a deep tech startup. We build beautiful and scalable software using computer vision and deep learning. We pride ourselves in solving problems nobody else can in the space.

• Lead the design, development, and implementation of advanced NLP models (e.g., transformers, LSTMs, BERT, GPT).
• Develop and optimize algorithms for tasks such as text classification, sentiment analysis, named entity recognition, question answering, and machine translation.
• Build and maintain robust data pipelines for training and evaluating NLP models.
• Collaborate with product managers, data scientists, and software engineers to integrate AI solutions into existing and new products.
• Evaluate and select appropriate machine learning frameworks and tools.
• Mentor and guide junior AI engineers, fostering a culture of technical excellence and continuous learning.
• Stay current with the latest research and advancements in AI, NLP, and machine learning.
• Present technical findings and project progress to stakeholders.
• Contribute to the overall AI strategy and roadmap.
• Ensure the scalability, reliability, and performance of deployed AI systems.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 5+ years of hands-on experience in developing and deploying NLP models in a production environment.
• Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn.
• Expertise in various NLP techniques and frameworks (e.g., Hugging Face Transformers, spaCy, NLTK).
• Experience with large language models (LLMs) and their applications.
• Solid understanding of data structures, algorithms, and software engineering principles.
• Proven ability to lead technical projects and mentor team members.
• Excellent problem-solving skills and the ability to work effectively in a fast-paced, remote setting.
• Strong communication skills, both written and verbal.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.

• Lead research initiatives in cutting-edge NLP areas, including but not limited to, large language models (LLMs), transformer architectures, sentiment analysis, machine translation, information extraction, and dialogue systems.
• Design, implement, and evaluate novel algorithms and models for various NLP applications.
• Develop and maintain robust data pipelines for training and evaluating NLP models, ensuring data quality and scalability.
• Collaborate with software engineering teams to deploy research prototypes into production systems.
• Publish research findings in top-tier AI conferences and journals.
• Mentor junior scientists and engineers, fostering a collaborative and innovative research environment.
• Stay abreast of the latest research trends and advancements in AI and NLP, and identify opportunities for innovation.
• Contribute to the strategic direction of the AI research roadmap.
• Present research results to technical and non-technical audiences.
• Engage with the broader AI community through contributions to open-source projects or academic initiatives.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related quantitative field.
• Minimum of 8 years of post-doctoral research experience in NLP and deep learning.
• Demonstrated track record of innovation and publications in top NLP/AI conferences (e.g., ACL, EMNLP, NeurIPS, ICML).
• Expertise in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Proficiency in programming languages such as Python, and libraries like Hugging Face Transformers, spaCy, NLTK.
• Strong theoretical understanding of machine learning algorithms, statistical modeling, and deep neural networks.
• Experience with large-scale data processing and distributed computing frameworks (e.g., Spark).
• Excellent analytical, problem-solving, and research skills.
• Exceptional communication and presentation abilities.
• Ability to work independently and as part of a remote, globally distributed team.

• Conduct research into state-of-the-art NLP techniques, including but not limited to transformer models, large language models (LLMs), sentiment analysis, named entity recognition, and machine translation.
• Develop, train, and fine-tune NLP models for various applications, such as chatbots, text summarization, question answering, and content generation.
• Implement and optimize NLP algorithms for performance and scalability in production environments.
• Collaborate with data scientists, software engineers, and product managers to integrate NLP capabilities into our products and services.
• Stay current with the latest advancements in AI, machine learning, and NLP research through academic papers and conferences.
• Design and conduct experiments to evaluate model performance and identify areas for improvement.
• Contribute to the development of internal tools and libraries to accelerate NLP research and development.
• Document research findings, methodologies, and model architectures.
• Present research results and technical designs to both technical and non-technical audiences.
• Mentor junior researchers and engineers on NLP best practices.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field.
• Proven experience (3+ years) in developing and deploying NLP models in a research or commercial setting.
• Strong programming skills in Python and experience with ML/DL frameworks such as TensorFlow, PyTorch, or Keras.
• Deep understanding of NLP concepts, algorithms, and libraries (e.g., spaCy, NLTK, Hugging Face Transformers).
• Experience with large language models (LLMs) and prompt engineering is highly desirable.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Excellent analytical, problem-solving, and research skills.
• Strong communication and collaboration abilities, capable of working effectively in a remote, distributed team.
• Ability to work independently, manage time effectively, and drive projects to completion.
• Experience with data preprocessing and feature engineering for text data.

• Lead the design, development, and deployment of large-scale NLP models and applications, ensuring scalability, reliability, and performance.
• Architect robust NLP pipelines, incorporating techniques such as text classification, named entity recognition, topic modeling, summarization, and question answering.
• Champion the adoption of state-of-the-art NLP research and technologies, including transformer models (BERT, GPT variants), attention mechanisms, and transfer learning.
• Collaborate closely with AI researchers, data scientists, and software engineers to translate research concepts into production-ready systems.
• Provide technical leadership and mentorship to a team of AI engineers, fostering a culture of innovation, code quality, and best practices.
• Define and implement best practices for NLP model training, evaluation, and deployment, including MLOps for NLP.
• Optimize NLP models for efficiency and performance in production environments, considering latency, memory footprint, and computational cost.
• Identify and address complex challenges in areas like low-resource NLP, cross-lingual NLP, and ethical AI considerations in language processing.
• Contribute to the strategic roadmap for AI and NLP initiatives within the organization.
• Stay abreast of the latest advancements in NLP research and industry trends, evaluating their applicability to our business needs.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Computational Linguistics, or a related field.
• 10+ years of professional experience in AI/ML engineering, with a significant specialization in NLP.
• Proven track record of successfully designing, building, and deploying production-grade NLP systems.
• Deep expertise in Python and core NLP libraries (e.g., spaCy, NLTK, Hugging Face Transformers).
• Extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and transformer architectures.
• Strong understanding of linguistic principles and various NLP tasks.
• Experience with cloud platforms (AWS, GCP, Azure) and associated ML services.
• Proficiency in software engineering best practices, including version control (Git), CI/CD, and testing methodologies.
• Excellent leadership, communication, and interpersonal skills, with the ability to influence technical direction.
• Experience with distributed systems and big data technologies is a plus.

• Conduct groundbreaking research in Natural Language Processing, focusing on areas such as sentiment analysis, machine translation, text summarization, and question answering.
• Develop, implement, and evaluate advanced NLP models using state-of-the-art deep learning frameworks (e.g., TensorFlow, PyTorch).
• Design and execute experiments to test hypotheses, validate algorithms, and measure performance improvements.
• Stay current with the latest advancements in AI, machine learning, and NLP research by reading academic papers, attending conferences, and engaging with the research community.
• Collaborate with cross-functional teams, including software engineers and product managers, to translate research findings into deployable AI solutions.
• Contribute to the development of intellectual property, including patents and publications in top-tier conferences and journals.
• Mentor junior researchers and engineers, fostering a culture of learning and innovation.
• Analyze and interpret large datasets to extract meaningful insights and inform model development.
• Present research findings clearly and effectively to both technical and non-technical audiences.
• Contribute to the strategic direction of the AI research roadmap.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a closely related field.
• 3+ years of research experience in Natural Language Processing.
• Proven track record of publications in leading AI/NLP conferences (e.g., ACL, EMNLP, NeurIPS, ICML).
• Strong programming skills in Python and experience with relevant libraries (e.g., spaCy, NLTK, Hugging Face Transformers).
• In-depth knowledge of deep learning architectures (e.g., LSTMs, Transformers, BERT) and their application to NLP tasks.
• Experience with large-scale data processing and distributed computing frameworks.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration abilities.
• Ability to work independently and as part of a collaborative research team.

• Conduct groundbreaking research in Natural Language Processing and Machine Learning.
• Develop and implement novel algorithms and models for language understanding, generation, and translation.
• Design and execute rigorous experiments to evaluate model performance.
• Analyze large datasets to extract meaningful insights and identify patterns.
• Collaborate with cross-functional teams, including engineers and product managers, to integrate research findings into products.
• Publish research results in leading AI conferences and journals.
• Stay abreast of the latest advancements in NLP, deep learning, and related fields.
• Mentor junior researchers and contribute to the team's knowledge base.
• Contribute to the strategic direction of the AI research roadmap.
• Develop prototypes and proofs-of-concept for new NLP applications.
• Ensure the ethical and responsible development of AI technologies.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, or a related quantitative field.
• Proven track record of research contributions in NLP, demonstrated through publications in top conferences (e.g., ACL, EMNLP, NeurIPS) and journals.
• Deep understanding of machine learning principles and deep learning architectures, especially transformer models and RNNs.
• Proficiency in programming languages such as Python and ML frameworks like TensorFlow or PyTorch.
• Experience with large-scale data processing and analysis.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills, with the ability to present complex technical information clearly.
• Ability to work independently and as part of a collaborative research team.
• Passion for innovation and a drive to contribute to the field of AI.