147 Nlp Engineer jobs in India
AI Bot Developer
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Job Description
We have an opening of AI specialist/machine learning head
Responsibilities:
- Develop controlled AI models using Amazon Bedrock
- Integrate existing machine learning models into new systems
- Design, implement, and maintain holistic AI solutions
- Collaborate with cross-functional teams to deploy scalable AI tools
Requirements:
- Proven experience in machine learning and AI development
- Strong proficiency in Python and relevant AI/ML libraries
- Experience with large language models (e.g., Amazon-based systems)
- Ability to work independently and manage end-to-end model development
- EXPERIENCE IS NECESSARY!
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NLP Engineer
Posted today
Job Viewed
Job Description
Experience: 4–8 Years
Location: Bangalore (Hybrid – Work from Office)
Availability: Immediate Joiners or
Candidates with Last Working Day by End of This Month
About the Role
We are seeking an experienced NLP Engineer to design, develop, and deploy advanced natural language processing solutions. This role involves working with cutting-edge NLP frameworks and Azure cloud services to process and analyze logistics-related text data at scale. The ideal candidate will have a strong background in building production-grade NLP models, integrating them into enterprise systems, and driving continuous improvement through feedback and monitoring mechanisms.
4-8 Years of Experience
Key Responsibilities
Model Development: Design, fine-tune, and deploy NLP models for extracting, classifying, and analyzing logistics-related text data using frameworks like Hugging Face, spaCy, or Azure Cognitive Services.
Use Case Implementation: Develop models for SKU classification, anomaly detection, and automated routing in supply chain workflows.
Deployment & Serving: Deploy and manage models on Azure Machine Learning or Azure Kubernetes Service , ensuring high availability, scalability, and low latency.
Data Pipelines: Build robust data ingestion and pre-processing pipelines integrating with warehouse management systems, APIs, and outputs from image recognition models.
Performance Monitoring: Establish feedback loops, enable model retraining, and monitor model performance using Azure Application Insights and other analytics tools.
Collaboration: Work closely with data engineers, solution architects, and operations teams to ensure smooth integration of NLP solutions into business workflows.
Required Skills & Experience
- Core NLP Expertise: Hands-on experience with Hugging Face Transformers, spaCy, and/or Azure Cognitive Services for NLP.
- Cloud Deployment: Strong experience with Azure Machine Learning and Azure Kubernetes Service for model deployment and scaling.
- Data Engineering: Skills in building and maintaining NLP data pipelines, including preprocessing, tokenization, and entity extraction.
- ML Lifecycle Management: Familiarity with continuous training workflows, MLOps best practices, and performance optimization for NLP systems.
- Programming: Proficiency in Python and experience with libraries like Pandas, NumPy, and PyTorch/TensorFlow.
- Problem-Solving: Ability to translate business requirements into technical NLP solutions for real-world logistics challenges.
Requirements
Education
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.
Requirements
Hugging Face Azure Machine Learning spaCy Azure Kubernetes Service
NLP Engineer
Posted today
Job Viewed
Job Description
Experience: 4–8 Years
Location: Bangalore (Hybrid – Work from Office)
Availability: Immediate Joiners or
Candidates with Last Working Day by End of This Month
About the Role
We are seeking an experienced NLP Engineer to design, develop, and deploy advanced natural language processing solutions. This role involves working with cutting-edge NLP frameworks and Azure cloud services to process and analyze logistics-related text data at scale. The ideal candidate will have a strong background in building production-grade NLP models, integrating them into enterprise systems, and driving continuous improvement through feedback and monitoring mechanisms.
4-8 Years of Experience
Key Responsibilities
Model Development: Design, fine-tune, and deploy NLP models for extracting, classifying, and analyzing logistics-related text data using frameworks like Hugging Face, spaCy, or Azure Cognitive Services.
Use Case Implementation: Develop models for SKU classification, anomaly detection, and automated routing in supply chain workflows.
Deployment & Serving: Deploy and manage models on Azure Machine Learning or Azure Kubernetes Service , ensuring high availability, scalability, and low latency.
Data Pipelines: Build robust data ingestion and pre-processing pipelines integrating with warehouse management systems, APIs, and outputs from image recognition models.
Performance Monitoring: Establish feedback loops, enable model retraining, and monitor model performance using Azure Application Insights and other analytics tools.
Collaboration: Work closely with data engineers, solution architects, and operations teams to ensure smooth integration of NLP solutions into business workflows.
Required Skills & Experience
- Core NLP Expertise: Hands-on experience with Hugging Face Transformers, spaCy, and/or Azure Cognitive Services for NLP.
- Cloud Deployment: Strong experience with Azure Machine Learning and Azure Kubernetes Service for model deployment and scaling.
- Data Engineering: Skills in building and maintaining NLP data pipelines, including preprocessing, tokenization, and entity extraction.
- ML Lifecycle Management: Familiarity with continuous training workflows, MLOps best practices, and performance optimization for NLP systems.
- Programming: Proficiency in Python and experience with libraries like Pandas, NumPy, and PyTorch/TensorFlow.
- Problem-Solving: Ability to translate business requirements into technical NLP solutions for real-world logistics challenges.
Requirements
Education
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.
NLP Engineer
Posted today
Job Viewed
Job Description
Design end to end java applications
Perform statistical analysis of results and refine models
Find and implement the right algorithms and tools for NLP tasks
Study and transform data science prototypes
Extend ML libraries and frameworks to apply in NLP tasks
Design Database to store NLP entities and relationship
Remain updated in the rapidly changing field of machine learning
write robust and testable code
Training and evaluating models
Use effective text representation techniques and classification algorithms
Designing and developing NLP applications for medical entity extraction and text mining
Candidate should have:
Experience with machine learning frameworks (like Keras or openly) and libraries (like sci-kit-learn)
Understanding of NLP techniques for text representation, semantic extraction techniques, data structures, and modeling
Familiarity with Ontology tools and technologies
Knowledge of Python, SQL
Proven experience as an NLP Engineer or similar role/Track record in NLP/NLU and related technologies
Clinical NLP experience (cTakes, UIMA)
Strong Java development experience would be preferred.
NLP Engineer
Posted today
Job Viewed
Job Description
Experience: 4–8 Years
Location: Bangalore (Hybrid – Work from Office)
Availability: Immediate Joiners or
Candidates with Last Working Day by End of This Month
About the Role
We are seeking an experienced NLP Engineer to design, develop, and deploy advanced natural language processing solutions. This role involves working with cutting-edge NLP frameworks and Azure cloud services to process and analyze logistics-related text data at scale. The ideal candidate will have a strong background in building production-grade NLP models, integrating them into enterprise systems, and driving continuous improvement through feedback and monitoring mechanisms.
4-8 Years of Experience
Key Responsibilities
Model Development: Design, fine-tune, and deploy NLP models for extracting, classifying, and analyzing logistics-related text data using frameworks like Hugging Face, spaCy, or Azure Cognitive Services.
Use Case Implementation: Develop models for SKU classification, anomaly detection, and automated routing in supply chain workflows.
Deployment & Serving: Deploy and manage models on Azure Machine Learning or Azure Kubernetes Service , ensuring high availability, scalability, and low latency.
Data Pipelines: Build robust data ingestion and pre-processing pipelines integrating with warehouse management systems, APIs, and outputs from image recognition models.
Performance Monitoring: Establish feedback loops, enable model retraining, and monitor model performance using Azure Application Insights and other analytics tools.
Collaboration: Work closely with data engineers, solution architects, and operations teams to ensure smooth integration of NLP solutions into business workflows.
Required Skills & Experience
- Core NLP Expertise: Hands-on experience with Hugging Face Transformers, spaCy, and/or Azure Cognitive Services for NLP.
- Cloud Deployment: Strong experience with Azure Machine Learning and Azure Kubernetes Service for model deployment and scaling.
- Data Engineering: Skills in building and maintaining NLP data pipelines, including preprocessing, tokenization, and entity extraction.
- ML Lifecycle Management: Familiarity with continuous training workflows, MLOps best practices, and performance optimization for NLP systems.
- Programming: Proficiency in Python and experience with libraries like Pandas, NumPy, and PyTorch/TensorFlow.
- Problem-Solving: Ability to translate business requirements into technical NLP solutions for real-world logistics challenges.
Requirements
Education
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.
Requirements
Hugging Face Azure Machine Learning spaCy Azure Kubernetes Service
Data Scientist / NLP /engineer
Posted today
Job Viewed
Job Description
• BI tools for data visualization like Tableau
• Experience extracting insights from large data sets using advanced Python
• experience working with complex unstructured and semi-structured data,
NLP Python, engineer
Posted today
Job Viewed
Job Description
• Experience in developing predictive, prescriptive, optimization, and forecasting models, including the use of contemporary techniques such as support vector machines, neural networks, and gradient boosting
• Experience translating high-level project requirements into technical tasks
• Experience with big data and cloud platforms (AWS) and toolset.
• Ability to engineer and create complex research datasets by manipulating typically large volume transactional data
Senior Engineer-NLP
Posted today
Job Viewed
Job Description
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Senior AI Engineer - NLP
Posted today
Job Viewed
Job Description
Key Responsibilities:
- Designing, developing, and implementing state-of-the-art NLP models and algorithms for various applications.
- Building and optimizing machine learning pipelines for text data processing, feature extraction, and model training.
- Utilizing frameworks like TensorFlow, PyTorch, and Hugging Face Transformers to develop advanced NLP solutions.
- Collaborating with product managers and data scientists to define project requirements and deliver impactful AI features.
- Deploying NLP models into production environments and monitoring their performance.
- Conducting research on new NLP techniques and technologies to identify opportunities for innovation.
- Ensuring the quality, scalability, and efficiency of AI solutions.
- Writing clean, maintainable, and well-documented code.
- Troubleshooting and debugging AI models and applications.
- Staying updated with the latest advancements in the NLP field and contributing to the team's knowledge base.
Required Qualifications:
- Master's or Ph.D. degree in Computer Science, Artificial Intelligence, or a related field.
- 5+ years of experience in AI/ML engineering, with a specialization in NLP.
- Proficiency in Python and experience with NLP libraries (e.g., NLTK, spaCy, scikit-learn).
- Hands-on experience with deep learning frameworks (TensorFlow, PyTorch) and transformer architectures.
- Strong understanding of NLP concepts such as word embeddings, sequence-to-sequence models, attention mechanisms, and language generation.
- Experience with deploying ML models in production environments.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
- Familiarity with cloud platforms (AWS, Azure, GCP) is a plus.
Lead Software Engineer - NLP
Posted today
Job Viewed
Job Description
About the role
You will have a vital role in developing complex solutions and deploying transformative data products. You will work in a team responsible for building Analytical insights, recommendation engines and boutique algorithms. You will identify new areas to apply data science to improve business performance. As a digital marketplace with millions of reviews and insights from our clients, there are limitless opportunities to apply your skills in data science. You will cover a broad and evolving set of responsibilities as you build data science capabilities at RCD – versatility, adaptability, and self-sufficiency will be critical to success. As a member of the Gartner family, you will have access to industry-leading research on analytics and data science solutions to help you deliver more engaging and relevant content for software buyers and improve the volume and quality of buyer leads for software sellers.
What will you do:
Research & Development
Research, design, and implement advanced machine learning (ML) and data algorithms, with a focus on analyzing text data and extracting actionable insights.
Stay current with the latest advancements in large language models (LLMs), generative AI (GenAI), and related technology trends to ensure the adoption of cutting-edge techniques.
ML Models Development & Optimization
Build and deploy ML models that facilitate effective matching of buyers to relevant content, enhancing the buyer’s journey.
Fine-tune pre-trained language models for specific business use cases, optimizing for accuracy, performance, and domain relevance.
End-to-End Solution Delivery
Lead the end-to-end development lifecycle of ML solutions, from rapid prototyping to full-scale productization.
Ensure seamless integration of ML solutions into existing systems and workflows, maintaining high standards of reliability and scalability.
Collaboration & Stakeholder Engagement
Work closely with Engineering and Product Management teams to align on and execute the data science roadmap.
Gather and analyze requirements from stakeholders, ensuring solutions are tailored to business needs and deliver measurable value.
Data Infrastructure & Solution Design
Play a hands-on role in the design and implementation of robust data warehousing solutions to support scalable analytics and ML initiatives.
Ensure data quality, integrity, and security throughout the data lifecycle.
Agile Delivery & Continuous Improvement
Participate in Agile Scrum ceremonies and processes, driving the iterative delivery of high-quality ML solutions.
Lead efforts in testing, validation, and post-rollout continuous improvement to maximize business impact and solution effectiveness.
What you’ll need
Bachelor’s degree in computer science, Information Systems, or a related field, or equivalent hands-on experience in software development.
6-8 years of professional experience in machine learning models , with hands-on experience working with AWS cloud services and Cassandra databases.
Proficiency in Python and a solid understanding of Object-Oriented Programming (OOP) principles
Familiarity with AWS ML tools and best practices for deploying and managing scalable machine learning solutions in the cloud.
Who you are:
A strong, passionate, empathetic engineer, who can work is able to work collaboratively with senior leadership, peers, and project team to deliver solutions on time, within budget, keeping the morale high
Proficiency in project tracking tools like Jira for effective project management and delivery tracking.
Strong ability to interpret and manage client expectations , proactively identifying and resolving issues that could impact project delivery.
Excellent interpersonal skills with a proven ability to work effectively within a matrixed and distributed team environment.
Demonstrated problem-solving skills and the ability to work both independently and collaboratively in a fast-paced setting.
Exceptional organizational and analytical skills , with keen attention to detail and the ability to maintain a strategic, big-picture perspective.
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At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world.
Our mission relies on expert analysis and bold ideas to deliver actionable, objective insight, helping enterprise leaders and their teams succeed with their mission-critical priorities.
Since our founding in 1979, we’ve grown to more than 21,000 associates globally who support ~14,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That’s why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here.
What makes Gartner a great place to work?
Our sustained success creates limitless opportunities for you to grow professionally and flourish personally. We have a vast, virtually untapped market potential ahead of us, providing you with an exciting trajectory long into the future. How far you go is driven by your passion and performance.
We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients.
Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations.
We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work.
What do we offer?
Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers.
In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring.
Ready to grow your career with Gartner? Join us.
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Machine Learning Engineer (NLP)
Posted 317 days ago
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Job Description
Machine Learning Engineer (NLP)
- Develop and deploy information extraction models for entity, relationship, and attribute extraction. - Utilize neural networks (LSTMs, GRUs, Siamese) and pre-trained models (BERT, T5, Transformers). - Fine-tune and optimize existing models for improved accuracy and efficiency. - Leverage knowledge graphs for enhancing information extraction and inference capabilities. - Integrate neuro-symbolic AI techniques for reasoning and knowledge representation. - Contribute to the creation and maintenance of knowledge graphs from unstructured text data. - Explore applications of knowledge graphs in question-answering and decision-making systems. - Collaborate with the team to integrate solutions into larger systems. - Potentially contribute to sentiment analysis, text generation, and translation projects. - Strong Python skills and experience with TensorFlow (or similar) and knowledge graph technologies required. - Be able to evaluate and transform latest, untested academic methods into production workflows. - Self-driven, highly motivated and ability to work both independently and within a team. - Operate optimally in fast pace development environment with dynamic changes, tight deadlines and limited resources.