1,440 Language Models jobs in India

• Design, develop, and implement advanced NLP models and algorithms, with a focus on LLMs like GPT, BERT, and their successors.
• Conduct research into new methods for pre-training, fine-tuning, and evaluating LLMs for various downstream tasks.
• Collaborate with cross-functional teams to integrate AI solutions into existing products and services.
• Analyze and interpret complex datasets to extract meaningful insights and inform model development.
• Stay abreast of the latest advancements in AI, NLP, and related fields through continuous learning and participation in academic communities.
• Publish research findings in top-tier conferences and journals.
• Mentor junior researchers and engineers, fostering a collaborative and innovative research environment.
• Contribute to the ethical development and deployment of AI technologies.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Proven track record of research and development in NLP and LLMs, evidenced by publications or contributions to open-source projects.
• Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Expertise in at least one major LLM architecture and familiarity with transformer-based models.
• Excellent problem-solving and analytical skills, with the ability to tackle complex challenges.
• Strong communication and collaboration skills, essential for a remote-first team.
• Experience with cloud computing platforms (AWS, GCP, Azure) is a plus.
• A passion for pushing the boundaries of AI and a commitment to scientific excellence.

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.

• Design and architect scalable deep learning systems and pipelines.
• Develop, train, and optimize deep learning models for various applications.
• Select appropriate model architectures and frameworks (TensorFlow, PyTorch, etc.).
• Lead the implementation of MLOps best practices for deep learning workflows.
• Collaborate with data scientists and engineers to integrate models into production.
• Evaluate and benchmark model performance, identifying areas for improvement.
• Mentor junior deep learning engineers and contribute to team growth.
• Stay current with state-of-the-art research in deep learning and AI.
• Contribute to the technical strategy and roadmap for AI initiatives.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
• 5+ years of experience in deep learning, with a focus on model architecture and development.
• Proven experience in designing and deploying large-scale deep learning models.
• Expertise in Python and deep learning frameworks like TensorFlow and PyTorch.
• Strong understanding of MLOps principles and tools.
• Experience with cloud platforms (AWS, Azure, GCP) for ML workloads.
• Excellent analytical, problem-solving, and algorithmic thinking skills.
• Strong communication and collaboration skills.
• Experience with distributed training and model optimization techniques.

• Conducting cutting-edge research in deep learning and artificial intelligence.
• Developing and implementing novel AI algorithms and models.
• Designing and executing experiments to validate research hypotheses.
• Analyzing large datasets and extracting meaningful insights.
• Collaborating with engineering teams to integrate AI models into products and systems.
• Staying current with the latest advancements in AI and machine learning research.
• Publishing research findings in top-tier conferences and journals.
• Contributing to the intellectual property of the organization.

• Lead the design, development, and implementation of advanced deep learning models and algorithms for diverse AI applications.
• Architect scalable and robust AI systems, from initial concept to production deployment.
• Conduct cutting-edge research in areas such as computer vision, natural language processing, reinforcement learning, and generative models.
• Optimize model performance, efficiency, and scalability for deployment in various environments.
• Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to integrate AI solutions into products and services.
• Stay abreast of the latest research papers, industry trends, and advancements in AI and machine learning.
• Mentor junior AI engineers and contribute to the team's technical growth and innovation.
• Develop and maintain high-quality code and comprehensive documentation for AI models and systems.
• Evaluate and select appropriate AI frameworks and tools for project needs.
• Contribute to the company's intellectual property through patents and publications.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum of 8 years of experience in AI and machine learning, with a strong specialization in deep learning.
• Proven track record of successfully designing, building, and deploying deep learning models in production environments.
• Expertise in deep learning frameworks such as TensorFlow, PyTorch, Keras, and associated libraries.
• Proficiency in programming languages like Python, and experience with relevant AI/ML libraries.
• Deep understanding of various neural network architectures (CNNs, RNNs, Transformers, GANs).
• Strong knowledge of cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Excellent problem-solving, analytical, and research skills.
• Exceptional communication and leadership abilities, with experience mentoring teams.

• Lead and conduct cutting-edge research in Deep Learning, Reinforcement Learning, Computer Vision, Natural Language Processing, or related AI fields.
• Develop novel AI algorithms and models, and advance the state-of-the-art in machine learning.
• Design and implement experiments to test and validate AI hypotheses and models.
• Publish research findings in top-tier academic conferences and journals.
• Collaborate with engineering teams to translate research breakthroughs into practical applications and products.
• Mentor junior researchers and contribute to the growth of the AI research community within the organization.
• Stay abreast of the latest advancements in AI and machine learning, identifying emerging trends and opportunities.
• Contribute to the strategic direction of the company's AI research initiatives.
• Develop and maintain high-quality, well-documented code for AI models and experiments.
• Present research findings to technical and non-technical audiences.
• Protect intellectual property through patent applications and other means.
• Evaluate and benchmark new AI technologies and frameworks.

• Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a closely related quantitative field.
• 10+ years of experience in AI research and development, with a strong focus on Deep Learning.
• Demonstrated track record of significant contributions to the field, evidenced by publications in top venues (e.g., NeurIPS, ICML, CVPR, ICLR).
• Expertise in one or more core AI areas (e.g., deep neural networks, reinforcement learning, generative models, computer vision, NLP).
• Proficiency in programming languages such as Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Strong analytical, problem-solving, and critical-thinking skills.
• Proven ability to lead research projects and mentor other researchers.
• Excellent communication, presentation, and interpersonal skills.
• Experience with large-scale data processing and distributed computing environments is a plus.
• Ability to work independently and collaboratively in a remote research environment.

• Conduct fundamental and applied research in deep learning and artificial intelligence.
• Design, implement, and evaluate novel deep learning models and algorithms.
• Experiment with various neural network architectures and training techniques.
• Optimize model performance for accuracy, efficiency, and scalability.
• Process and analyze large-scale datasets for model training and validation.
• Collaborate with engineering teams to integrate research prototypes into production systems.
• Stay abreast of the latest advancements in AI and machine learning research.
• Publish research findings in leading academic journals and conferences.
• Contribute to the intellectual property and patent portfolio.
• Mentor junior researchers and interns.

• PhD or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Strong publication record in top AI/ML venues (e.g., NeurIPS, ICML, ICLR, CVPR).
• Deep understanding of machine learning, deep learning, and statistical modeling.
• Proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, Keras).
• Experience with large-scale data processing and distributed computing.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong programming skills and software development practices.
• Effective communication and presentation skills for conveying complex research ideas.