9 Nlp Models Jobs

This role is for one of the Weekday's clients. We are an innovative company at the forefront of AI-driven solutions, specializing in cutting-edge technologies to solve real-world problems. We are seeking a talented and passionate Computer Vision Engineer with expertise in both Computer Vision and Natural Language Processing (NLP) to join our dynamic team. Key Responsibilities: Develop and implement state-of-the-art computer vision algorithms for image and video processing tasks such as object detection, image segmentation, feature extraction, and recognition. Design, build, and deploy NLP models for tasks such as text recognition from images (OCR), sentiment analysis, and text classification. Collaborate with data scientists and machine learning engineers to integrate computer vision and NLP models into production systems. Work with large datasets to train and fine-tune models, ensuring high accuracy and performance. Conduct research to stay updated on the latest advancements in computer vision and NLP, and apply them to ongoing projects. Optimize model performance for real-time applications on various platforms (e.g., cloud, mobile, edge devices). Analyze and preprocess datasets including images, videos, and text for training and validation. Collaborate with cross-functional teams to ensure seamless integration of computer vision and NLP components within larger applications. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Proven experience (3+ years) in developing computer vision solutions and NLP models. Strong proficiency in Python and relevant libraries such as OpenCV, TensorFlow, PyTorch, Keras, and scikit-learn. Hands-on experience with deep learning frameworks (e.g., CNNs, RNNs, Transformers) for both computer vision and NLP tasks. Expertise in Natural Language Processing tasks such as tokenization, text embedding, and sequence-to-sequence models. Familiarity with Optical Character Recognition (OCR) tools and techniques. Experience working with datasets for object detection, semantic segmentation, and text recognition from visual data. Proficiency in deploying and scaling machine learning models in production environments (AWS, GCP, Azure). Strong problem-solving skills and the ability to work independently and collaboratively in a team environment. Preferred Skills: Knowledge of Reinforcement Learning (RL) and how it can be applied to vision tasks. Familiarity with multimodal machine learning, integrating vision and language models. Experience in edge computing for deploying models in real-time environments. Strong understanding of cloud-based AI/ML pipelines.,

As an AI/ML Engineer Generative AI Specialist with over 5 years of experience, you will be expected to possess the following must-have skills: You should have a strong background in AI/ML frameworks such as PyTorch, TensorFlow, and proficient in Python programming. Your experience with AWS services, specifically AWS Bedrock and Lambda functions, will be crucial. Hands-on expertise in LangChain components (agents, chains, memories, parsers, document loaders), developing and optimizing GenAI, NLP models, and CrewAI is essential for this role. You should be capable of building and deploying RAG (Retrieval-Augmented Generation) systems, chatbots, and AI applications using OpenAI APIs, Ollama, Llama, and llamaparse. Advanced prompt engineering techniques like Chain of Thought (CoT) prompting should be within your skill set. Additionally, experience with Docker, CI/CD pipelines, YML files, and GitHub repository management is required. A strong understanding of system design principles, focusing on security, scalability, and performance optimization, is a must. Good-to-have skills include experience in responsible AI practices, knowledge of event-driven architecture, and familiarity with cloud deployments and Kubernetes. Experience with large-scale AI model training and fine-tuning would be beneficial. Your key responsibilities will involve designing and implementing AI/ML solutions using cutting-edge technologies to ensure scalability, efficiency, and alignment with business objectives. You will be responsible for developing and optimizing LangChain components, CrewAI, GenAI, and NLP models customized to specific applications. Building and deploying production-ready RAG systems, chatbots, and AI-driven applications utilizing OpenAI APIs, Ollama, Llama, and llamaparse will be part of your role. Leveraging AWS Bedrock and other AWS services to deliver high-performance AI solutions is crucial. You will need to apply prompt engineering techniques like Chain of Thought (CoT) prompting to enhance AI interactions, maintain CI/CD pipelines, manage YML files, and utilize GitHub for version control. Implementing containerization using Docker and deploying AI solutions in cloud environments will also fall under your responsibilities. Ensuring that solutions adhere to best practices in system design, focusing on security, performance, and efficiency considerations is essential. You will also need to incorporate responsible AI practices and ensure compliance with ethical AI guidelines. Collaboration with cross-functional teams to translate AI insights into impactful solutions and effective communication of complex technical concepts to both technical and non-technical stakeholders will be expected from you.,

Design, implement, and optimize NLP models for tasks such as text classification, sentiment analysis, named entity recognition, and language generation. - Utilize libraries such as NLTK, SpaCy, TensorFlow, or PyTorch for model development. Preprocess and clean large datasets, ensuring data quality and integrity for NLP applications. - Develop scripts to automate data extraction, transformation, and loading (ETL) processes. Work closely with data scientists, analysts, and other stakeholders to understand project requirements and deliver effective NLP solutions. - Collaborate in an Agile environment, participating in sprint planning and code reviews. Analyze and improve the performance of existing NLP models and algorithms. - Implement best practices for model evaluation and validation. Document processes, methodologies, and model performance metrics. - Present findings and insights to technical and non-technical stakeholders.

Key Responsibilities: Hands-on Development: Develop and implement machine learning models and algorithms , including supervised, unsupervised, deep learning, and reinforcement learning techniques. Implement Generative AI solutions using technologies like RAG (Retrieval-Augmented Generation), Vector DBs , and frameworks such as LangChain and Hugging Face, Agentic AI . Utilize popular AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn . Design and deploy NLP models and techniques , including text classification, RNNs, CNNs, and Transformer-based models like BERT. Ensure robust end-to-end AI/ML solutions, from data preprocessing and feature engineering to model deployment and monitoring. Technical Proficiency: Demonstrate strong programming skills in languages commonly used for data science and ML, particularly Python . Leverage cloud platforms and services for AI/ML, especially AWS , with knowledge of AWS Sagemaker, Lambda, DynamoDB, S3 , and other AWS resources. Mentorship: Mentor and coach a team of data scientists and machine learning engineers, fostering skill development and professional growth. Provide technical guidance and support, helping team members overcome challenges and achieve project goals. Set technical direction and strategy for AI/ML projects, ensuring alignment with business goals and objectives. Facilitate knowledge sharing and collaboration within the team, promoting best practices and continuous learning. Strategic Advisory: Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and products. Provide strategic insights and recommendations to support decision-making processes. Communicate effectively with stakeholders at various levels, including technical and non-technical audiences. Required Skills: Extensive proficiency with generative AI technologies , including RAG, Vector DBs , and frameworks such as LangChain and Hugging Face, Agentic AI . Proficiency in machine learning algorithms and techniques , including supervised and unsupervised learning, deep learning, and reinforcement learning. Extensive proficiency with AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn . Strong knowledge of natural language processing (NLP) techniques and models , including Transformer-based models like BERT. Proficient programming skills in Python . Proficiency with cloud platforms like AWS , including AWS Sagemaker, Lambda, DynamoDB, S3 , and other AWS resources. Proven ability to lead a team of data scientists or machine learning engineers on complex projects. Strong project management skills, with the ability to prioritize tasks, allocate resources, and meet deadlines. Excellent communication skills and the ability to convey complex technical concepts to diverse audiences. Strong problem-solving and analytical abilities. Proven ability to manage projects and activities. Preferred Skills: Proficiency in setting technical direction and strategy for AI/ML projects. Knowledge of the Insurance domain. Ability to mentor and coach junior team members, fostering growth and development. Proven track record of successfully managing AI/ML projects from conception to deployment.

As an LLM Expert with 3+ years of experience, you should have a strong background in designing and tuning advanced models. You must have at least 3 years of experience in LLM, NLP Models, and Machine Learning, along with 2.5 years of experience in AI. Excellent communication skills are essential for this role, as well as previous experience in team handling. Professionals with backgrounds such as Datascientist, Data Annotator AI, and AI Engineer are encouraged to apply. This position is based in Bangalore and is a full-time role with a day shift schedule. The work location is in person.,

Title: Senior Data Scientist Years of Experience : 8+ years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Description The Senior Data Scientist will lead the development and implementation of advanced analytics and AI/ML models to solve complex business problems. This role requires deep statistical expertise, hands-on model building experience, and the ability to translate raw data into strategic insights. The candidate will collaborate with business stakeholders, data engineers, and AI engineers to deploy production-grade models that drive innovation and value. Key responsibilities Lead end-to-end model lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring Develop predictive models, recommendation systems, anomaly detection, NLP models, and generative AI applications Conduct statistical analysis and hypothesis testing for business experimentation Optimize model performance using hyperparameter tuning, ensemble methods, and explainable AI (XAI) Collaborate with data engineering teams to improve data pipelines and quality Document methodologies, build reusable ML components, and publish technical artifacts Mentor junior data scientists and contribute to CoE-wide model governance Technical Skills ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost Statistical tools: Python (NumPy, Pandas, SciPy), R, SAS NLP & LLMs: Hugging Face Transformers, GPT APIs, BERT, LangChain Model deployment: MLflow, Docker, Azure ML, AWS Sagemaker Data visualization: Power BI, Tableau, Plotly, Seaborn SQL and NoSQL (CosmosDB, MongoDB) Git, CI/CD tools, and model monitoring platforms Qualification Masters in Data Science, Statistics, Mathematics, or Computer Science Microsoft Certified: Azure Data Scientist Associate or equivalent Proven success in delivering production-ready ML models with measurable business impact Publications or patents in AI/ML will be considered a strong advantage.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.