1,323 AI Architecture jobs in India
Member of Technical Staff - AI/ML [ Natural Language Processing, Transformers, Gen AI, LLM, Neura...
Posted 2 days ago
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**The Opportunity**
At Nutanix, we're redefining intelligent observability with Panacea.ai - an AI/ML-powered platform that automatically detects, explains and correlates anomalies across logs and metrics.
In version 1.0, we used regex-based filters along with historical data to identify anomalies. In version 2.0, we advanced to **AI/ML** and capabilities that deliver deeper, context-rich anomaly detection and are working on building an **enterprise-grade automated RCA (Root Cause Analysis) engine** - powered by an **agentic platform** that integrates **MCP servers** as tools, and a conversational interface that enables users to query, explore and discuss issues as naturally as a chat.
We're seeking a passionate and driven Engineer to work on this mission-critical initiative. This is a hands-on, high-impact role where you will work on this AI/ML innovation, and shape Nutanix's central AI charter. You'll be at the forefront of building enterprise-scale, AI-first observability solutions.
**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
+ Work along with **high-impact team** delivering AI-first observability tools that directly improve engineering velocity and product quality.
+ Tackle **challenging technical and product problems** at scale and speed.
+ Shape the **foundational AI platform and practices** across Nutanix.
+ Enjoy the **flexibility of hybrid work** , with a culture that values deep work, collaboration, and ownership.
+ Be part of a **startup-style team** backed by the scale, reach, and stability of a global cloud leader.
**Your Role**
+ **Auto RCA Engine:** Deliver an AI-driven engine that correlates logs and metrics across distributed services, automatically surfacing explanations for incidents. This includes an **agentic platform** that integrates **MCP servers** as tools, alongside a **chat-like conversational interface** that enables engineers to query issues, run diagnostics, and collaborate on RCA in natural language. Here, LLMs will power interactive diagnostics and human-like discussions around problem-solving.
+ **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. This includes leveraging LLMs for anomaly explanation, RCA summaries, and contextual recommendations to engineers and support teams.
+ **Knowledge Base Creation:** Build a robust **company-wide knowledge base** that consolidates product, observability, and system data into structured formats. This knowledge base will serve as a foundation for LLMs, enhancing their ability to reason, answer queries, and provide deeper insights into system anomalies.
+ **Metrics Anomaly Detection:** Development of models that detect anomalies in **CPU, memory, disk I/O, network traffic, and service health** , enabling proactive identification of performance regressions. LLMs will assist in summarizing anomalies and providing contextual recommendations for remediation.
+ **Feedback Loop & Continuous Learning:** Build infrastructure that captures user interactions and feedback, using LLMs and ML pipelines to retrain and improve anomaly detection and RCA accuracy over time.
+ **Central AI Charter:** Collaborate with product and support teams to define foundational AI infrastructure, shared ML components, governance practices, and standards that scale across Nutanix's product ecosystem.
Responsibilities
+ Apply expertise in **LangGraph, LangChain, agentic AI architectures, and multi-agent orchestration** to build intelligent, scalable workflows.
+ Design and develop **conversational AI systems** (chatbots, copilots, or support assistants) for incident triage and RCA.
+ Implement correlation models to connect anomalies across logs and metrics, forming a cohesive **RCA narrative** .
+ **End-to-end 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.
**What You Will Bring**
+ **Educational Background** : B.Tech/M.Tech in Computer Science, Machine Learning, AI, or a related field.
+ **Experience** : 6+ years in software engineering, with a track record of designing, developing, and deploying AI/ML systems at scale,
+ **AI/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.
+ Experience with LLMs for downstream tasks like summarization, root cause reasoning, or intelligent Q&A.
+ Preferred experience in designing and deploying agentic workflows.
+ **Engineering Skills:** Strong Python programming skills with proficiency in ML libraries (PyTorch, TensorFlow, Scikit-learn), time-series frameworks, and MLOps tools. Experience building and operating robust data pipelines and serving models at scale.Observability Knowledge: Familiarity with logs, metrics, and traces, along with monitoring tools such as Prometheus, Grafana, and ELK
**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 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
Deep Learning Engineer
Posted 5 days ago
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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.
Cloud Solution Architecture - Data & AI
Posted 2 days ago
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The Global Customer Success (GCS) organization, an organization within CE&S, is leading the effort to enable customer success on the Microsoft Cloud by harnessing leading, AI-powered capabilities and human expertise to deliver innovation solutions that accelerate business value, drive operational excellence and nurture long term loyalty.
Are you looking for a role where you can interact directly with large enterprise customers to improve their Azure Data and SQL related technologies? If so, we are looking for you!
We are seeking a Cloud Solution Architect in the CSA Global Delivery organization with deep expertise in Azure Data and SQL. As a key technical resource for the customer, you will be primarily focused on delivering proactive services such as education workshops, delivering assessments, and providing tailored guidance. Troubleshooting skills are essential as this role will include working with Microsoft Support to expedite incident resolution.
The CSA Global Delivery team is a centralized group consisting of both full-time employees (FTEs) and Vendor CSAs dedicated to enhancing the customer's experience with Microsoft as they transition to hybrid/public cloud solutions.
Microsoft's mission is to empower every person and every organization on the planet to achieve more.
This role is flexible in that you can work up to 50% from home.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
**Responsibilities**
You will be planning and delivering proactive and reactive support including onsite presence as needed
· You will Identify and manage customer goals and SfMC opportunities to improve the quality, consumption, and health of the customer's solution.
· You will drive and participate in proactive delivery management: spot performance issues, analyze problems, and drive activities focused on stabilizing and optimizing your customer's solution.
· You will work with internal Microsoft support teams, account teams, product engineering and service engineering teams and other stakeholders to ensure a streamlined and efficient customer support experience.
· You will apply and share lessons learned for continuous process and delivery improvement for the customer and peers.
· You will engage in meetings with your customers and account teams to review Support for Mission Critical services, customer support issues, and articulate your Customer Success Plans.
· You will share and gain knowledge through technical communities.
Technical Leadership
· Demonstrate the capability to act as CSA Pod Lead with ability to drive planning and delivery of Pod team by engaging CSAM and ATU, manage customer relationship by conducting monthly engagement reviews and assuring quality and be accountable for capacity planning, hiring, skilling and utilization of Pod members.
· Proactively develops technical and professional learning and development plan in alignment with and support from their manager. Role models effective technical readiness. Acts as a mentor and role model to less experienced colleagues to educate them on technical and non-technical concepts. Participates in development opportunities (e.g., Ready, Build, Ignite).
· Shares ideas, insights, and strategic technical input with technical teams, internal communities across the field, and the larger virtual team across Microsoft using a thorough knowledge of specific Microsoft products and their context in the competitive landscape. Participates in external technical community events (e.g., conferences, seminars, technical meetups, Webcasts, blogs, hackathons) and shares learnings with the internal team.
· Generates new ideas for changes and improvements to existing intellectual property (IP), technologies, and processes for designated customers/partners. Drives opportunities for IP reuse, best practice sharing, and consumption acceleration. Proactively identifies gaps through delivery and communicating those gaps to others (e.g., Leadership, managed intellectual property (MIP), Design, and Governance). Applies subject matter expertise to develop new IP that fills identified gaps
Important key criteria:
- Should have potential to scale as CSA Pod Lead with ability to lead planning and delivery of vendor Pod team by engaging account team
- Manage customer relationship by conducting monthly engagement reviews and assuring quality and be accountable for capacity planning, hiring, skilling and utilization of Pod members.
Additional details
**Qualifications**
Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND 4+ years experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting OR equivalent experience.
- 10+ years of Data & AI related experience with at least three of the following technologies: SQL Server 2012 or later on-premises, SQL Server 2012 or later running on Azure VMs, Azure SQL Database, Azure SQL Managed Instance, Azure SQL Hyper-Scale, SQL AAG Clusters, Azure Integration Services
- Strong knowledge of SQL Server Internals
- Practical experience designing / building large OLTP DB systems
- Knowledge of other SQL technologies on Azure (PostgreSQL, MySQL, MariaDB)
- Data & AI Certifications in Microsoft and competing Cloud Technologies.
- Outstanding customer service skills with excellent oral and written communication skills as well as experience providing training to peers or customers.
- Strong interpersonal and leadership skills while working with diverse audiences including highly technical IT professionals, engineers, developers, and architects as well as executives and management professionals in both customer and Microsoft teams.
- Experience leading and driving projects as well as motivating others.
- Self-motivated, resourceful, and able to handle multiple responsibilities as a Microsoft Cloud Solution Architect
- Ability to develop strong strategic customer relationships that gain the trust and respect of customers.
- Ability to handle critical technical issues and work in difficult support situations.
- Ability to handle difficult or sensitive situations with customers.
Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations ( .
Senior Deep Learning Architect
Posted 22 days ago
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Responsibilities:
- 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.
AI Research Scientist - Machine Learning & Deep Learning
Posted 13 days ago
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Key Responsibilities:
- Conduct advanced research in machine learning, deep learning, and other AI domains.
- Develop, implement, and evaluate novel AI algorithms and models.
- Design and execute experiments to test hypotheses and validate research findings.
- Analyze large datasets to extract insights and train AI models.
- Collaborate with cross-functional teams to integrate AI solutions into products.
- Publish research findings in top-tier academic conferences and journals.
- Stay abreast of the latest advancements in AI and related fields.
- Contribute to the development of intellectual property and patents.
- Mentor junior researchers and interns.
- Present research progress and results to internal and external stakeholders.
Qualifications:
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
- 5+ years of research experience in AI/ML, with a strong publication record.
- Deep understanding of machine learning algorithms, deep learning architectures, and statistical modeling.
- Proficiency in programming languages such as Python.
- Hands-on experience with AI/ML frameworks like TensorFlow, PyTorch, or Keras.
- Experience with data manipulation and analysis tools.
- Strong analytical, problem-solving, and critical thinking skills.
- Excellent communication and presentation skills.
- Ability to work both independently and collaboratively in a research environment.
- Experience with cloud platforms (AWS, GCP, Azure) for AI development is a plus.
Lead Machine Learning Engineer - Deep Learning Frameworks
Posted 19 days ago
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Responsibilities:
- Lead the design, development, and implementation of scalable machine learning systems and pipelines.
- Architect and optimize deep learning models using frameworks such as TensorFlow, PyTorch, or JAX.
- Develop and deploy production-ready ML solutions, ensuring reliability, performance, and scalability.
- Collaborate with research scientists to translate novel algorithms and experimental findings into robust engineering implementations.
- Mentor and guide a team of ML engineers, fostering best practices in coding, testing, and deployment.
- Define and implement MLOps strategies for model versioning, monitoring, and continuous integration/deployment.
- Conduct thorough code reviews and provide constructive feedback to team members.
- Optimize model performance for efficiency and effectiveness across various hardware platforms.
- Stay abreast of the latest advancements in machine learning, deep learning, and AI research.
- Contribute to the strategic technical direction of the ML engineering team and the broader organization.
- Troubleshoot and resolve complex technical issues in production ML systems.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Minimum of 7 years of experience in machine learning engineering, with a strong focus on deep learning.
- Proven experience in leading ML projects from research to production.
- Deep expertise in Python and proficiency with core ML libraries (e.g., scikit-learn, pandas, NumPy).
- Extensive hands-on experience with deep learning frameworks like TensorFlow, PyTorch, or Keras.
- Strong understanding of MLOps principles and tools (e.g., Docker, Kubernetes, CI/CD, MLflow).
- Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
- Excellent problem-solving, analytical, and algorithmic thinking skills.
- Exceptional leadership, communication, and collaboration abilities, critical for a remote-first environment.
- Experience with large-scale data processing and distributed systems.
Senior Machine Learning Engineer - Deep Learning Specialist
Posted 22 days ago
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AI Research Scientist - Deep Learning
Posted 1 day ago
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The ideal candidate will possess a strong academic background in Artificial Intelligence, Machine Learning, or a closely related field, with a proven ability to conduct independent research and publish findings. Expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras is essential. You will work on projects involving areas like computer vision, natural language processing, reinforcement learning, or generative models. Responsibilities include designing experiments, collecting and analyzing data, building and training deep learning models, evaluating their performance, and translating research findings into practical applications. Collaboration with other researchers and engineers will be key to pushing the boundaries of what's possible in AI.
Key responsibilities include:
- 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.
AI Research Scientist - Deep Learning
Posted 6 days ago
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AI Research Scientist - Deep Learning
Posted 6 days ago
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