3,253 Natural Language Processing jobs in India

About Company:

It is a global MNC Service based.

Experience: 3 to 6Years

Location: Bangalore

Notice Period: Immediate to 45 Days

Mode: work from office(WFO)

Skills: Natural language processing(NLP) with Python / Java (Scripting), Machine Learning(AIML)

Roles and Responsibilities:

Scripting/Programming : Skilled in Shell and Python / Java for automation and tool development. Familiarity with NLP libraries like NLTK or spaCy or Tensor flow

Data Analysis: Strong analytical skills to clean, preprocess, and analyze large datasets

Good understanding of Machine Learning & Deep Learning

Additional Skills:

Kubernetes: Strong experience in deploying and scaling applications, managing secrets, and troubleshooting within Kubernetes environments. K8s networking, CNI, VLAN and CNS

Google Cloud : Familiarity with Google Cloud Build, Cloud Deploy,Cloud Functions, Secret Manager, GCS-storage

Virtualization & Containerization : Understanding of virtualization concepts and experience with containerization technologies, including KubeVirt. Proficient in building and deploying containers

CI/CD, DevOps : Experienced in automating build processes, module testing, static code analysis, integration testing, application packaging, vulnerability scanning, and release management.

Configuration Management: Proficient with tools such as Terraform and Ansible for infrastructure as code.

Configuration Management: Proficient with tools such as Terraform and Ansible for infrastructure as code.

About Company:

It is a global MNC Service based.

Experience: 3 to 6Years

Location: Bangalore

Notice Period: Immediate to 45 Days

Mode: work from office(WFO)

Skills: Natural language processing(NLP) with Python / Java (Scripting), Machine Learning(AIML)

Roles and Responsibilities:

Scripting/Programming : Skilled in Shell and Python / Java for automation and tool development. Familiarity with NLP libraries like NLTK or spaCy or Tensor flow

Data Analysis: Strong analytical skills to clean, preprocess, and analyze large datasets

Good understanding of Machine Learning & Deep Learning

Additional Skills:

Kubernetes: Strong experience in deploying and scaling applications, managing secrets, and troubleshooting within Kubernetes environments. K8s networking, CNI, VLAN and CNS

Google Cloud : Familiarity with Google Cloud Build, Cloud Deploy,Cloud Functions, Secret Manager, GCS-storage

Virtualization & Containerization : Understanding of virtualization concepts and experience with containerization technologies, including KubeVirt. Proficient in building and deploying containers

CI/CD, DevOps : Experienced in automating build processes, module testing, static code analysis, integration testing, application packaging, vulnerability scanning, and release management.

Configuration Management: Proficient with tools such as Terraform and Ansible for infrastructure as code.

Configuration Management: Proficient with tools such as Terraform and Ansible for infrastructure as code.

Job Summary

Synechron is seeking a highly skilled Sr. NLP Developer and Project Leader to spearhead the development, migration, and management of natural language processing (NLP) projects utilizing the Natural programming language and related NLP frameworks. The successful candidate will have extensive experience in building enterprise-level NLP applications, leading technical teams, and migrating legacy systems toward modern, AI-enabled NLP solutions. In this role, you will drive innovation, ensure seamless system integration, and optimize performance for scalable deployment.

Purpose:
To design, develop, and guide enterprise NLP solutions and migrations that enhance automation, intelligence, and operational efficiency across business functions within a modern technology environment.

Value:
This role accelerates the organization’s adoption of NLP and AI technologies, improves system integration, and supports digital transformation by modernizing legacy systems and enabling intelligent automation.

Software Requirements

Required Skills:

Proven experience developing NLP applications using the Natural programming language in enterprise settings.

Strong understanding of NLP techniques and frameworks such as NLTK, SpaCy, Stanford NLP, and transformer models (e.g., BERT, GPT).

Proficiency in programming languages including Java, Python, or similar for NLP tasks and system integration.

Experience leading projects for legacy application migration to NLP-capable platforms.

Solid understanding of machine learning principles, especially as they relate to NLP.

Expertise in designing, developing, and deploying NLP solutions with cloud platforms such as AWS, Azure, or Google Cloud.

Ability to guide technical teams on best practices, coding standards, and NLP methods.

Strong skills in system integration using APIs, databases, and enterprise data sources.

Preferred Skills:

Certifications in AI, NLP, or related fields.

Experience deploying NLP solutions on cloud environments for scalability.

Familiarity with data management, data engineering, and large-scale data processing.

Overall Responsibilities

Lead the end-to-end development of NLP applications, including design, development, testing, and deployment.

Manage migration projects from legacy systems to NLP-enabled platforms, ensuring minimal disruption and maximal adoption.

Provide technical leadership, mentorship, and guidance to project teams on NLP best practices, system architecture, and coding standards.

Collaborate with stakeholders to gather requirements, design solutions, and deliver innovative NLP-driven automation.

Integrate NLP solutions with existing enterprise systems, databases, and APIs to ensure seamless operations.

Monitor, troubleshoot, and optimize NLP applications for performance, accuracy, and scalability.

Document system architecture, analytics insights, and migration strategies comprehensively.

Stay current with evolving NLP, AI, and machine learning trends, evaluating new tools and techniques to enhance project outcomes.

Strategic Objectives:

Modernize legacy applications with NLP insights, enabling automation and intelligent decision-making.

Drive technical innovation through NLP and AI best practices aligned with enterprise goals.

Deliver scalable, secure, and high-performance NLP solutions that add measurable business value.

Performance Outcomes:

Successful migration of legacy systems with minimal operational impact and clear documentation.

High accuracy and efficiency of deployed NLP applications.

Consistent project delivery within scope, budget, and timeline expectations.

Technical Skills (By Category)

Programming Languages:

Essential: Natural language processing-specific scripts using Java, Python, or similar languages.

Preferred: Familiarity with scripting languages such as R or Perl for NLP tasks.

Frameworks & Libraries:

Essential: NLP frameworks including NLTK, SpaCy, Stanford NLP, Hugging Face transformers.

Preferred: Experience with deep learning frameworks like TensorFlow or PyTorch for NLP model training and fine-tuning.

Databases & Data Management:

Experience working with large datasets, knowledge of NoSQL databases (e.g., MongoDB, Cassandra), and structured data sources for NLP.

Cloud Technologies:

Hands-on experience deploying NLP models and applications on cloud platforms such as AWS, Azure, or Google Cloud.

System Integration & APIs:

Proficiency in integrating NLP applications with existing enterprise systems, APIs, and data pipelines.

Development Tools & Methodologies:

GIT, Jenkins, Docker, Kubernetes for code management, deployment, and automation.

Agile/Scrum methodologies for project delivery.

Security & Data Privacy:

Knowledge of data security, access controls, and privacy considerations relevant to NLP applications.

Experience Requirements

5+ years of hands-on experience developing NLP applications and solutions.

Proven experience leading NLP projects, including migration or modernization of legacy systems.

Demonstrated expertise in deploying NLP solutions at scale, preferably in enterprise or financial environments.

Prior leadership experience managing multidisciplinary teams for project execution.

Day-to-Day Activities

Design, develop, and deliver NLP applications aligned with business needs.

Lead migration efforts, transforming legacy systems into NLP-driven platforms.

Conduct technical reviews, code audits, and optimize NLP pipelines for performance and accuracy.

Collaborate with business and technical teams to develop requirements and translate them into scalable solutions.

Research emerging NLP technologies and incorporate relevant innovations into projects.

Monitor live NLP applications, troubleshoot issues, and implement improvements.

Document processes, architecture decisions, and model performance metrics.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or related fields.

Certifications in AI, NLP, or cloud deployment are a plus.

Proven track record of developing and managing NLP solutions in enterprise settings.

Professional Competencies

Strong analytical and troubleshooting skills.

Excellent communication skills for technical and non-technical audiences.

Strategic thinking to align NLP solutions with business goals.

Leadership ability to guide teams and mentor junior staff.

Adaptability to rapidly evolving AI and NLP technologies.

Time management skills to deliver on multiple projects effectively.

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Minimum qualifications:
+ Bachelor's degree or equivalent practical experience.
+ 5 years of experience with software development in one or more programming languages.
+ 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
+ 3 years of experience with Natural Language Processing (NLP) concepts, algorithms, and experience in designing NLP solutions.
+ 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
+ Master's degree or PhD in Computer Science or related technical field.
+ 5 years of experience with data structures/algorithms.
+ 1 year of experience in a technical leadership role.
+ Experience developing accessible technologies.
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We're made up of multiple teams, building Google's Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
+ Write and test product or system development code.
+ Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)
+ Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
+ Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
+ Design and implement NLP solutions, leverage ML infrastructure, and contribute to model optimization and data processing.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:

**Hungry, Humble, Honest, with Heart.**
**The Opportunity**
We are reimagining observability at Nutanix with **Panacea.ai** , our next-gen AI-driven log and metrics analyzer. In version 1.0, we leveraged regex-based filters to surface anomalies. Now, we're building **Panacea.ai** -powered by **AI/ML, ModernBERT, and LLMs** -to deliver intelligent, context-rich anomaly detection, automated root cause analysis (Auto-RCA), and continuous learning from user feedback.As a **Staff Engineer (MTS-6)** , you will **own the architecture and AI/ML systems that power both log and metrics analysis** , enabling automated diagnostics and reducing triage time for QA failures, regression runs, and customer issues. You'll also help define and drive the central AI charter at Nutanix, building reusable components, model infrastructure, and scalable ML services.
**About the Team**
The **Panacea** team has a passionate set of engineers across India and US office. We move fast, collaborate closely, and care deeply about quality and ownership. Our mission is to deliver **AI/ML-powered developer productivity tools** that solve real engineering and support pain points at scale.
Why Join Us
+ Build **AI-first observability tools** that redefine how engineers triage and troubleshoot.
+ Own systems that reduce hours of manual work in **engineering and SRE workflows** .
+ Collaborate with a **tight-knit team of high-ownership engineers** who are passionate about impact and innovation.
+ Hybrid work model that supports flexibility and deep focus.
+ Help shape the **central AI charter** at Nutanix and influence future AI products across the company.
**Your Role**
+ **AI-Powered Observability Platform** : Own the vision, architecture, and delivery of Panacea's ML-based log and metrics analyzer that reduces triage time and improves engineering efficiency.
+ **AI/ML-powered Log Analyzer Tool** : Use deep learning (e.g., **ModernBERT** ) to represent log messages, detect anomalies, group patterns, and surface actionable insights to users.
+ **Metrics Anomaly Detection Engine** : Build robust ML models to detect anomalies in time-series metrics like **CPU, memory, disk I/O, network traffic, service health** , and more-automatically identifying performance degradation or system regressions across distributed environments.
+ **Auto-RCA Engine** : Combine log and metrics signals with graph-based correlation and LLM-powered summarization to automatically diagnose the root cause of system failures.
+ **Feedback Loop & Continuous Learning** : Build infrastructure for incorporating user feedback to continuously retrain and improve anomaly detection systems.
+ **LLM Integration** : Integrate LLMs for user queries, problem summarization, anomaly explanation, and contextual recommendations.
+ **Central AI Charter** : Contribute to Nutanix's foundational AI platform by defining shared tooling, datasets, governance, and reusable ML components across products.
Responsibilities
+ Architect and scale ML pipelines for **real-time and batch-based anomaly detection** in both logs and time-series metrics.
+ Build and fine-tune **ModernBERT** and other transformer-based models for log understanding, anomaly classification, and summarization.
+ Develop unsupervised and semi-supervised ML models for **detecting anomalies in system metrics** (CPU, memory, network throughput, latency, etc.).
+ Implement correlation models to connect anomalies across logs and metrics to form a cohesive RCA narrative.
+ Own the entire ML lifecycle: data ingestion, feature extraction, model training, evaluation, deployment, and monitoring.
+ Build explainable AI systems that increase adoption and trust within engineering, QA, and support teams.
+ Collaborate with cross-functional stakeholders (SRE, QA, Dev) to deeply understand pain points and translate them into intelligent tooling.
+ Drive technical excellence through code and design reviews, mentoring, and setting engineering best practices.
**What You Will Bring**
+ **Educational Background** : B.Tech/M.Tech in Computer Science, Machine Learning, AI, or related fields.
+ **Experience** : 12+ years of engineering experience , including designing , developing and deploying AI/ML systems at scale.
+ **ML Expertise** :
+ Strong in time-series anomaly detection, statistical modeling, supervised/unsupervised learning.
+ Experience building ML models for **metrics data** (CPU, memory, IOPS, network, etc.) using models like Isolation Forest, Prophet, LSTM, or deep autoencoders.
+ Expertise in NLP using **ModernBERT, BERT, or** log classification, clustering, and summarization.
+ Experience with LLMs for downstream tasks like summarization, root cause reasoning, or intelligent Q&A.
+ **Engineering Skills** : Strong Python background, hands-on with ML libraries (PyTorch, TensorFlow, Scikit-learn), time-series frameworks, and MLOps tools. Familiar with data pipelines and serving models.
+ **Observability Knowledge** : Hands-on with logs, metrics, traces, and popular monitoring tools (e.g., Prometheus, Grafana, ELK).
+ **Leadership** : Ability to independently drive projects from requirements to delivery, mentor junior engineers, and deliver business impact.
**Work Arrangement**
Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. For most roles, that will mean coming into an office a minimum of 2 - 3 days per week, however certain roles and/or teams may require more frequent in-office presence. Additional team-specific guidance and norms will be provided by your manager.
We're an Equal Opportunity Employer Nutanix is an Equal Employment Opportunity and (in the U.S.) an Affirmative Action employer. Qualified applicants are considered for employment opportunities without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, protected veteran status, disability status or any other category protected by applicable law. We hire and promote individuals solely on the basis of qualifications for the job to be filled. We strive to foster an inclusive working environment that enables all our Nutants to be themselves and to do great work in a safe and welcoming environment, free of unlawful discrimination, intimidation or harassment. As part of this commitment, we will ensure that persons with disabilities are provided reasonable accommodations. If you need a reasonable accommodation, please let us know by contacting

The Opportunity

We are reimagining observability at Nutanix with , our next-gen AI-driven log and metrics analyzer. In version 1.0, we leveraged regex-based filters to surface anomalies. Now, we’re building —powered by AI/ML, ModernBERT, and LLMs —to deliver intelligent, context-rich anomaly detection, automated root cause analysis (Auto-RCA), and continuous learning from user a Staff Engineer (MTS-6) , you will own the architecture and AI/ML systems that power both log and metrics analysis , enabling automated diagnostics and reducing triage time for QA failures, regression runs, and customer issues. You’ll also help define and drive the central AI charter at Nutanix, building reusable components, model infrastructure, and scalable ML services.

About the Team

The Panacea team has a passionate set of engineers across India and US office. We move fast, collaborate closely, and care deeply about quality and ownership. Our mission is to deliver AI/ML-powered developer productivity tools that solve real engineering and support pain points at scale.

Why Join Us
 

Build AI-first observability tools that redefine how engineers triage and troubleshoot.

Own systems that reduce hours of manual work in engineering and SRE workflows .

Collaborate with a tight-knit team of high-ownership engineers who are passionate about impact and innovation.

Hybrid work model that supports flexibility and deep focus.

Help shape the central AI charter at Nutanix and influence future AI products across the company.

Your Role

AI-Powered Observability Platform : Own the vision, architecture, and delivery of Panacea’s ML-based log and metrics analyzer that reduces triage time and improves engineering efficiency.

AI/ML-powered Log Analyzer Tool : Use deep learning (., ModernBERT ) to represent log messages, detect anomalies, group patterns, and surface actionable insights to users.

Metrics Anomaly Detection Engine : Build robust ML models to detect anomalies in time-series metrics like CPU, memory, disk I/O, network traffic, service health , and more—automatically identifying performance degradation or system regressions across distributed environments.

Auto-RCA Engine : Combine log and metrics signals with graph-based correlation and LLM-powered summarization to automatically diagnose the root cause of system failures.

Feedback Loop & Continuous Learning : Build infrastructure for incorporating user feedback to continuously retrain and improve anomaly detection systems.

LLM Integration : Integrate LLMs for user queries, problem summarization, anomaly explanation, and contextual recommendations.

Central AI Charter : Contribute to Nutanix’s foundational AI platform by defining shared tooling, datasets, governance, and reusable ML components across products.

Responsibilities
 

Architect and scale ML pipelines for real-time and batch-based anomaly detection in both logs and time-series metrics.

Build and fine-tune ModernBERT and other transformer-based models for log understanding, anomaly classification, and summarization.

Develop unsupervised and semi-supervised ML models for detecting anomalies in system metrics (CPU, memory, network throughput, latency, .

Implement correlation models to connect anomalies across logs and metrics to form a cohesive RCA narrative.

Own the entire ML lifecycle: data ingestion, feature extraction, model training, evaluation, deployment, and monitoring.

Build explainable AI systems that increase adoption and trust within engineering, QA, and support teams.

Collaborate with cross-functional stakeholders (SRE, QA, Dev) to deeply understand pain points and translate them into intelligent tooling.

Drive technical excellence through code and design reviews, mentoring, and setting engineering best practices.

What You Will Bring

Educational Background : / in Computer Science, Machine Learning, AI, or related fields.

Experience : 12+ years of engineering experience , including designing , developing and deploying AI/ML systems at scale.

ML Expertise :Strong in time-series anomaly detection, statistical modeling, supervised/unsupervised learning.Experience building ML models for metrics data (CPU, memory, IOPS, network, using models like Isolation Forest, Prophet, LSTM, or deep autoencoders.Expertise in NLP using ModernBERT, BERT, or log classification, clustering, and summarization.Experience with LLMs for downstream tasks like summarization, root cause reasoning, or intelligent Q&A.

Engineering Skills : Strong Python background, hands-on with ML libraries (PyTorch, TensorFlow, Scikit-learn), time-series frameworks, and MLOps tools. Familiar with data pipelines and serving models.

Observability Knowledge : Hands-on with logs, metrics, traces, and popular monitoring tools (., Prometheus, Grafana, ELK).

Leadership : Ability to independently drive projects from requirements to delivery, mentor junior engineers, and deliver business impact.

Work Arrangement

Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. For most roles, that will mean coming into an office a minimum of 2 - 3 days per week, however certain roles and/or teams may require more frequent in-office presence. Additional team-specific guidance and norms will be provided by your manager.

--

Greetings from TCS!

Job Title: AI Developer

Required Skillset: LangChain Python, Azure Low Code

Location: Chennai

Experience Range: 4-6 years

Job Description

Must-Have**

1. 5+ years of professional experience (not necessarily in AI)
2. Proven experience in AI development using pro-code and/or low-code platforms.
3. Proficiency with AI frameworks like LangChain
4. Experience with Azure AI Services and other low-code platforms.

Good To Have:

1. Familiarity with front-end technologies (JavaScript, HTML, CSS) is a plus.
2. Understanding of RESTful APIs and microservices architecture.

Responsibility of / Expectations from the Role:

1. AI Development: Design and implement AI solutions using pro-code frameworks (e.g., LangChain) and low-code Azure Services.
2. Collaboration: Work closely with Python back-end developers to integrate AI functionalities and with front-end developers to ensure optimal user experience.
3. Integration: Develop APIs and interfaces that enable smooth communication between AI components and other system parts.
4. Flexibility: Adapt to various project requirements and switch between pro-code and low-code development as needed.
5. Innovation: Stay updated with the latest AI trends and technologies to bring innovative solutions to the team.

Soft Skills:

1. Excellent communication skills to effectively interface with cross-functional teams.
2. Strong problem-solving abilities and attention to detail.
3. Ability to work independently and collaboratively in a team environment.

Qualifications: Bachelor’s degree in computer science, Engineering, or a related field is preferred but not required.

Thanks & Regards,

Ria Aarthi A.

Job Title: AI Developer – Recruitment Process Automation

Location: Remote

Experience: 2–4 years

Job Type: Full-Time | Remote

About Us:

At Elegant Enterprise-Wide Solutions, we’re transforming how staffing works by embracing smart automation. We're hiring an AI Developer to build intelligent tools that streamline and automate our core staffing operations.

Responsibilities:

• Design and implement AI/ML solutions to automate recruitment and staffing workflows.
• Collaborate with operations and HR teams to understand use cases and pain points.
• Build and train models for resume parsing, candidate matching, and document generation.
• Create and refine effective prompts to drive accurate outputs from generative AI tools (e.g., ChatGPT, Claude).
• Ensure integration of AI tools with internal systems like CRMs, ATS, and proposal platforms.
• Continuously improve the accuracy, speed, and reliability of all automation solutions.

Requirements:

• 2–4 years of experience in AI/ML development or automation projects.
• Strong Python skills with hands-on knowledge of libraries such as Scikit-learn, spaCy, or NLTK.
• Experience with natural language processing (NLP) and resume parsing.
• Ability to craft effective AI prompts for automating content-based tasks.
• Familiarity with recruitment workflows, HR tech tools, or staffing platforms.

Summary: Hiring an AI Developer to build, train, and deploy ML/DL models for production-ready AI solutions.
Responsibilities:

• Develop and deploy ML/DL models .
• Handle data preprocessing and feature engineering .
• Integrate models with production systems.
• Research and apply new AI techniques.

Requirements:

• 3–5 years in AI/ML development .
• Strong Python , TensorFlow/PyTorch, scikit-learn.
• Experience in model training, tuning, and evaluation.
• Knowledge of data pipelines and cloud ML deployment.
• Git version control skills.