(immediate joiner) mern/full stack developers

agentic ai engineer

ai / ml engineer

ai engineer

ai engineers

automation engineer

ai ml engineer

Accenture in India

<div>
 
 Project Role :
 
 AI / ML Engineer
 
 
 
 Project Role Description :
 
 Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
 
 
 
 Must have skills :
 
 Machine Learning (ML)
 
 
 
 Good to have skills :
 
 NA
 
 
 
 Minimum 3 Year(s) Of Experience Is Required
 
 
 
 
 Educational Qualification :
 
 15 years full time education
 
 
 Role Summary
 
 
 We are seeking a hands-on AI Native Engineer who can design, build, and deploy end-to-end agentic and LLM-powered systems. This includes constructing RAG pipelines, working with vector databases, building autonomous or semi-autonomous agents, integrating tools and skills, and developing evaluation frameworks for high-quality AI behaviour. You will prototype rapidly, experiment with models, and evolve solutions from PoC to production while working closely with cross-functional teams.
 
 
 AI Powered Tech Talent
 
 
 Key Responsibilities
 
 
 Agentic &amp; LLM System Development
 
 
 Build agentic AI systems, including agent orchestration, planning loops, tool calling, and memory modules.
 
 
 Implement LLM toolchains, custom prompts, templates, evaluators, and multi-step reasoning workflows.
 
 
 Develop autonomous/semi-autonomous agents for retrieval, summarization, decision support, or workflow automation.
 
 
 RAG Pipelines &amp; Vector Intelligence
 
 
 Design and implement RAG pipelines end-to-end: ingestion, chunking, embeddings, indexing, vector search, hybrid retrieval, and grounding.
 
 
 Integrate vector databases such as pgvector, Pinecone, Weaviate, or Milvus.
 
 
 Optimize retrieval quality, latency, and factual accuracy using rerankers, retrieval evaluators, and freshness pipelines.
 
 
 Model Integration &amp; AI Ops
 
 
 Integrate enterprise-grade AI APIs, foundation models, and transformer models into scalable systems.
 
 
 Implement robust evaluation frameworks including offline and online evals, regression tests, content safety checks, and red-team scenarios.
 
 
 Build monitoring for model drift, agent failure modes, hallucination detection, and end-to-end system health.
 
 
 Full-Stack &amp; Cloud Alignment
 
 
 Deploy services using Python/Node/Java microservices, serverless functions, or containerized workloads.
 
 
 Integrate event streams, API gateways, and cloud-native patterns across Azure/AWS/GCP.
 
 
 Build CI/CD pipelines for AI services with safe rollouts, versioning, and feature flags for model updates.
 
 
 Prototyping &amp; Rapid Iteration
 
 
 Rapidly experiment with models, embeddings, architectures, and agentic patterns.
 
 
 Translate business requirements into AI-native technical architectures and communicate trade-offs via demos and deep-dives.
 
 
 Document designs, experiments, and evaluation results for reproducibility and knowledge sharing.
 
 
 Professional &amp; Technical Skills
 
 
 Must-Have (AI Native Core)
 
 
 Hands-on experience with LLMs, agent frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, AutoGen), and vector DBs.
 
 
 Strong Python skills for building agents, RAG services, data pipelines, and evaluation harnesses.
 
 
 Deep understanding of transformer models, embeddings, prompt engineering, and model fine-tuning workflows.
 
 
 Experience deploying AI systems to production with monitoring, error handling, retries, and fallback strategies.
 
 
 Good to Have
 
 
 Experience with cloud AI platforms (Azure OpenAI, Bedrock, Vertex AI).
 
 
 Knowledge of multimodal models, reinforcement learning, or advanced reasoning agents.
 
 
 Familiarity with evaluation frameworks (pytest, JUnit) and custom eval harnesses.
 
 
 Additional Information
 
 
 Minimum 3 years of experience in ML/AI engineering (AI-native experience preferred).
 
 
 Location: Bengaluru.
 
 
 Education: 15 years full-time education., 15 years full time education
</div>

AI / ML Engineer

Fractal Analytics

<div>It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.<div><div>
Job Description</div></div><div><div><div><div><div><div><div><div><div><h1 class="jobSectionHeader">
EL3 &ndash; Databricks MLOps Engineer (Contract)</h1>
Domain: Claims Payment Integrity | M&amp;R, C&amp;S, E&amp;I Claims (preferred) 
Actuarial &amp; Forecasting Analytics Exposure is an Added Advantage 
Tech Stack: Databricks, Spark, Python, Scala, Azure, GitHub Actions, Terraform 
AI/LLM Capabilities: Embedding Models, LLM Integration, LangChain Agentic Frameworks<h2 class="jobSectionHeader">
Role Summary</h2>
The EL3 Databricks MLOps Engineer is a senior hands-on role responsible for enabling end-to-end machine learning lifecycle automation on Databricks. This includes building and maintaining the CI/CD infrastructure, environment configuration, packaging and deploying ML models, supporting reproducible experiments, and ensuring scalable job orchestration for AI/ML workloads, including LLM-based applications.
The role partners closely with Data Scientists, AI/ML Engineers, platform teams, and business stakeholders within Claims Payment Integrity to ensure robust, reliable, and automated ML delivery.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Enable and automate the end-to-end ML lifecycle on Databricks (environment setup, model workflow automation, job scheduling, monitoring hooks).</li><li>
Build frameworks, templates, and utilities that make ML development and experimentation reproducible and scalable.</li><li>
Implement CI/CD pipelines using Git, GitHub Actions, Jenkins, Azure DevOps, or similar tools.</li><li>
Package, version, and deploy ML models into Databricks-managed execution environments.</li><li>
Set up automated workflows for training, retraining, evaluation, and scheduled job execution.</li><li>
Support creation and integration of machine learning models including classification, forecasting, anomaly detection, NLP, and PI models.</li><li>
Enable LLM/GenAI-driven solutions by integrating:<ul><li>
Embedding model generation</li><li>
RAG architectures</li><li>
Vector databases</li><li>
LangChain agentic workflows</li></ul></li><li>
Optimize resource usage, runtime configurations, and code execution patterns for ML workloads.</li><li>
Collaborate with Data Scientists to translate experimental notebooks into production-ready pipelines.</li><li>
Implement platform-level controls for environment consistency, dependency management, access control, and model versioning.</li><li>
Support troubleshooting, debugging, and performance improvements for ML workloads.</li><li>
Document standards, templates, guidelines, and best practices for MLOps teams.</li><li>
Work cross-functionally with product, engineering, and analytics teams across PI.</li></ul><h2 class="jobSectionHeader">
Required Qualifications</h2><ul><li>
Bachelor&rsquo;s/Master&rsquo;s degree in Computer Science, Engineering, or related field</li><li>
6&ndash;9 years of relevant experience in ML Engineering, MLOps, or platform engineering</li><li>
Strong hands-on experience with Databricks, Spark (batch/streaming), Python, Scala</li><li>
Experience enabling ML lifecycle tools such as MLflow (tracking, packaging, model registration)</li><li>
Strong CI/CD experience using Git, GitHub Actions, Jenkins, or Azure DevOps</li><li>
Experience deploying AI/ML models into cloud environments (Azure preferred)</li><li>
Ability to create and integrate embedding models, semantic vectors, and LLM-driven components</li><li>
Experience with LangChain for agentic workflows and integration of tools/functions</li><li>
Strong problem-solving, debugging, and collaboration skills</li></ul><h2 class="jobSectionHeader">
Preferred Qualifications</h2><ul><li>
Experience with Azure OpenAI or OpenAI-compatible LLM APIs</li><li>
Familiarity with healthcare claims workflows, PI, FWA, provider billing, or pricing</li><li>
Experience in Agile/Scrum environments</li><li>
Strong understanding of software engineering best practices, packaging, dependency management</li></ul><h2 class="jobSectionHeader">
Good-to-Have Data Knowledge</h2><ul><li>
Call Center datasets (member &amp; provider interactions)</li><li>
Provider RCM datasets (billing, coding, authorizations)</li><li>
EHR/clinical datasets for cross-domain validation</li></ul></div></div></div></div></div></div></div></div></div>
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!<h3 class="jobSectionHeader">
Hiring Related Queries</h3>
India: HiringsupportIndia@fractal.ai
Outside India: HiringsupportROW@fractal.ai
This inbox does not process resume submissions. All applications must be made through posted job openings
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MLOps Engineer

EPAM Systems

<div>EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
We are seeking an experienced Lead/Sr MLOps Engineer with deep expertise in Domino Data Lab to manage and optimize machine learning operations across the entire ML lifecycle. In this role, you will support platform reliability, drive infrastructure automation and ensure seamless deployment and monitoring of machine learning solutions in production environments.
Responsibilities<ul><li>
Manage and optimize the Domino Data Lab platform across the machine learning lifecycle</li><li>
Oversee MLOps processes to support efficient model development and operations</li><li>
Maintenance of Kubernetes clusters and Docker containers for scalable workloads</li><li>
Implementation of CI/CD pipelines using Jenkins, GitLab and GitHub</li><li>
Administration of Linux environments to ensure system stability</li><li>
Provide platform support at L2/L3 levels for end users and stakeholders</li><li>
Monitoring and troubleshooting of platform issues to minimize downtime</li><li>
Collaboration with data science teams to streamline machine learning workflows</li><li>
Deployment and management of solutions across AWS, Azure and GCP</li></ul>
Requirements<ul><li>
5+ years of experience in MLOps or machine learning lifecycle management</li><li>
Knowledge of Domino Data Lab platform</li><li>
Expertise in Kubernetes and Docker</li><li>
Proficiency in Python and R</li><li>
Skills in CI/CD tools including Jenkins, GitLab and GitHub</li><li>
Familiarity with AWS, Azure and GCP</li><li>
Competency in Linux administration</li><li>
Capability to perform monitoring and troubleshooting</li><li>
Background in platform support at L2/L3 levels</li></ul>
Nice to have<ul><li>
Background in AI/ML engineering</li><li>
Skills in model deployment and monitoring</li><li>
Familiarity with data science platform support</li><li>
Proficiency in infrastructure automation using Terraform and Ansible</li></ul>
We offer<ul><li>
Opportunity to work on technical challenges that may impact across geographies</li><li>
Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications</li><li>
Opportunity to share your ideas on international platforms</li><li>
Sponsored Tech Talks &amp; Hackathons</li><li>
Unlimited access to LinkedIn learning solutions</li><li>
Possibility to relocate to any EPAM office for short and long-term projects</li><li>
Focused individual development</li><li>
Benefit package:<ul><li>
Health benefits</li><li>
Retirement benefits</li><li>
Paid time off</li><li>
Flexible benefits</li></ul></li><li>
Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)</li></ul></div>

Lead/Sr MLOps Engineer - Domino Data Lab

ARCITECH

<div><div><div><div><div><h6 class="jobSectionHeader">Arcitech AI <div>Turbhe, Maharashtra, India</div></h6></div><div><ul><div>
On-site</div><div>
Full-time</div><div><div>
2-5 Years experience required</div></div><div><div><div>
₹</div><div>
300000 - 420000 Per Year</div></div></div></ul></div><div><div>
Posted 1 day ago</div></div></div></div><div></div><div><h5 class="jobSectionHeader">
About Company</h5><div>
Arcitech AI, located in Navi Mumbai's bustling Vashi, is a trailblazer in software and IT, specializing in software development, AI, mobile apps, and integrative solutions. Committed to excellence and innovation, Arcitech AI offers incredible growth opportunities for team members. Enjoy unique perks like weekends off and a provident fund. Our vibrant culture is friendly and cooperative, fostering a dynamic work environment that inspires creativity and forward-thinking. Join us to shape the future of technology.</div>
Unit No. 15, Ground Floor, E Wing, Phase - I, Akshar Business Park, Sector - 25, Vashi- 400703.</div></div><div></div><div><div><div>
About the Role

As a Manual QA Tester you are the last line of defense for quality before anything reaches a client or a live user.

You will work on our highest-stakes products &mdash; systems that handle payments, children&rsquo;s education data, recorded customer conversations, and healthcare information &mdash; where a missed defect has real consequences.

This is a craft role:

We care about how well you test (your coverage, your edge-case thinking, the clarity of your bug reports) far more than how many cases you can rush through. This is a manual testing role. Automation is not required, though an interest in growing toward it over time is welcome. What You Will Test You will test complex, data-sensitive products and client projects, including:
<ul><li>An education platform with student and teacher flows, course purchases, multi-currency payments, tax/GST calculations, ratings, and strict separation of one user&rsquo;s data from another&rsquo;s &mdash; including data belonging to younger users, where correctness and privacy matter most.</li></ul>
<ul><li>A customer-conversation analytics platform involving recorded calls, dashboards, and sentiment/quality data, where accuracy and access control are critical.</li></ul>
<ul><li>A healthcare interpreting platform where data handling and reliability carry real-world impact.</li></ul>
<ul><li>Complex client projects with intricate business logic and integrations that demand careful, methodical testing. Because of this, your day-to-day testing goes well beyond happy-path clicking &mdash; it includes payment and transaction edge cases (failed payments, refunds, currency conversion, minimum- amount limits), role and permission boundaries, data-accuracy checks across dashboards and reports, validation and error handling, and regression across releases.</li></ul>

Key Responsibilities
<ul><li>Test case design and execution. Prepare clear test case scenarios before sign-off testing begins, covering positive flows, negative scenarios, edge cases, role/permission checks, validation, regression impact, and cross-browser/device variations where relevant.</li></ul>
<ul><li>Find issues before users do. Test assigned features, fixes, and regression areas thoroughly. Catching a bug internally is a win; a bug that reaches a client or user is a miss.</li></ul>
<ul><li>High-quality defect reporting. Log every issue with clear reproduction steps, expected vs. actual behavior, environment details, and evidence (screenshots, recordings, console logs) &mdash; so a developer can reproduce it without you explaining it verbally.</li></ul>
<ul><li>Accurate classification and retesting. Classify bugs by severity (Critical / High / Medium / Low), retest fixes, and update records with outcomes.</li></ul>
<ul><li>Release sign-off discipline. Never mark something fully tested without documented, executed test cases. Block release when material bugs are open or testing is incomplete.</li></ul>
<ul><li>Tooling discipline. Maintain accurate, current records in our project and issue-tracking systems (we use Zoho Projects and Zoho Desk) and log working hours via our time- tracking tool.</li></ul>
<ul><li>Continuous improvement. Surface recurring defect patterns, suggest process and tooling improvements, and contribute to the wider QA practice.</li></ul>

Quality Independence &mdash; An Important Part of This Role READ THIS BEFORE APPLYING Our testers operate independently from delivery pressure.

Quality decisions are made on the merits of what is actually working.

If you are ever pressured to sign off on something that is not ready, you are expected to block the release and escalate &mdash; not give in.

Quality and sign-off matters report to the Senior QA Engineer who leads testing, not to the delivery team.

We are looking for someone with the integrity and backbone to hold that line.

Required Qualifications
<ul><li>2+ years of manual testing on web or software applications, with at least 1 year owning testing for a product or module end to end (not only executing someone else&rsquo;s test scripts).</li></ul>
<ul><li>Strong test design. Demonstrable ability to write thorough test cases covering positive, negative, edge, and regression scenarios &mdash; not just the happy path.</li></ul>
<ul><li>Defect reporting track record. Clear, reproducible bug reports with proper evidence.</li></ul>
<ul><li>Integrity and independence. Willingness to log every issue honestly, block a release that is not ready, and escalate when pressured.</li></ul>
<ul><li>Tooling familiarity. Comfortable with a defect/issue tracking system (Zoho, Jira, or similar) and standard QA workflows.</li></ul>
<ul><li>Testing fundamentals. Solid grasp of the QA lifecycle, test case management, severity/priority classification, and regression testing.</li></ul>
<ul><li>Attention to detail and communication. Methodical and thorough, able to describe issues clearly in writing and coordinate with developers and project managers.</li></ul>

Preferred (Not Required)
<ul><li>Experience testing applications involving payments, multi-currency, or sensitive/regulated user data.</li></ul>
<ul><li>Exposure to API testing (e.g., Postman) at a basic level.</li></ul>
<ul><li>ISTQB Foundation or similar QA certification.</li></ul>
<ul><li>Interest in growing toward test automation over time.</li></ul></div></div></div></div>

QA Tester

Cisco

<div>
 
 
 Job Description
 
 
 
 You will be a member of a software engineering team that develops tools and integrations for a portfolio of cloud infrastructure services supporting Cisco&rsquo;s critical business operations.
 
 
 As a Software (AI / Private Cloud / Virtualization) Engineer with extensive experience in enterprise-level private cloud and AI-driven automation setups, you will join a dynamic and agile team of engineers focused on developing platform automation, operational tooling, and intelligent systems for large-scale infrastructure environments.
 
 
 
 
 
 
 
 
 
 Responsibilities:
 
 
 
 As a
 
 Software Engineer with the Cloud Infrastructure Platform Team
 
 , you will:
 
 
 &bull; Participate in architect and design scalable solutions supporting Infrastructure and AI Platform Services for enterprise private cloud environments.
 
 
 &bull; Design, develop, and maintain automation frameworks for managing large-scale OpenStack-based private cloud infrastructure.
 
 
 &bull; Develop and deliver software/tools required for building and improving the functionality, reliability, availability, and manageability of applications/services and cloud platforms using a DevOps model.
 
 
 &bull; Ensure the quality, performance, robustness, and scalability of the services you implement.
 
 
 &bull; Drive AIOps initiatives across infrastructure platforms by collaborating with multi-functional teams including SRE and Software Engineers to operationalize and optimize AI/LLM-based automation solutions.
 
 
 &bull; Develop infrastructure automation tools and frameworks using Python along with automation tools such as Ansible and CI/CD pipelines.
 
 
 &bull; Build AI-powered assistants, RAG-based systems, or agentic automation solutions to help automate operational workflows across the private cloud platform.
 
 
 &bull; Collaborate with platform and SRE teams to identify automation opportunities and develop plug-and-play AI solutions for platform operations.
 
 
 &bull; Assist in implementing AIOps practices such as intelligent monitoring, log analysis, alert correlation, and automated remediation workflows.
 
 
 &bull; Automate the development, testing, and deployment processes through CI/CD pipelines using Git, GitHub Actions,CI, Jenkins, Helm, or similar tools.
 
 
 &bull; Develop microservices and REST APIs supporting infrastructure automation and operational tooling.
 
 
 &bull; Work with containerized environments and orchestration platforms such as Kubernetes and Docker.
 
 
 &bull; Ensure platform reliability, scalability, and performance through strong engineering practices, observability, and automation.
 
 
 &bull; Conduct code reviews, establish engineering best practices, and mentor junior engineers.
 
 
 &bull; Stay updated on emerging technologies in AI/ML, cloud infrastructure, and automation to influence platform enhancements.
 
 
 &bull; Apply global knowledge of IT infrastructure to develop standard solutions that can be leveraged across multiple areas.
 
 
 &bull; Evaluate new and emerging technologies and determine their applicability to the platform engineering group.
 
 
 &bull; Generate ideas and technical strategies and present them to peers and stakeholders for feedback.
 
 
 
 
 
 
 
 
 
 Minimum Qualifications / Requirement:
 
 
 
 &bull; Experience: 5+ years of software engineering experience, including exposure to AI/ML or AI-driven automation initiatives.
 
 
 &bull; Hands-on experience operating or automating OpenStack-based private cloud environments.
 
 
 &bull; Strong programming skills in Python.
 
 
 &bull; Experience with infrastructure automation tools such as Ansible.
 
 
 &bull; Experience working with Kubernetes for cluster management, container orchestration, and platform services.
 
 
 &bull; Experience with Docker containerization and microservices-based architectures.
 
 
 &bull; Experience developing AI or LLM-powered operational assistants, chatbots, or internal developer tools.
 
 
 &bull; Experience implementing RAG (Retrieval-Augmented Generation) pipelines to query operational documentation, runbooks, and infrastructure data.
 
 
 &bull; Experience building CI/CD pipelines for infrastructure or platform services using tools such as GitHub Actions, GitLab CI, Jenkins, or similar.
 
 
 &bull; Familiarity with monitoring, logging, and observability platforms used in large-scale distributed systems.
 
 
 &bull; Experience working with databases such as MySQL, MongoDB, or similar systems.
 
 
 &bull; Experience working with messaging systems such as Kafka or similar event-streaming platforms.
 
 
 &bull; Interest in applying AI and machine learning techniques to platform operations, automation, and AIOps initiatives.
 
 
 &bull; Strong debugging and problem-solving skills in complex distributed systems.
 
 
 &bull; Experience mentoring engineers and contributing to architectural or technical decision-making.
 
 
 
 
 
 
 
 
 Why Cisco?
 
 
 At Cisco, we&rsquo;re revolutionizing how data and infrastructure connect and protect organizations in the AI era &ndash; and beyond. We&rsquo;ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
 
 
 Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you&rsquo;ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
 
 
 We are Cisco, and our power starts with you
 
</div>

Software Engineer (AI)

Intelligent Minds Trust

Senior Robotics Engineer | IoT | Embedded SystemsLocation: Sector 67, Noida Experience: 3&ndash;6 Years Job Type: Full-Time (Work from Office)About the RolePM Publishers Pvt. Ltd. is looking for a passionate Senior Robotics Engineer to design and develop innovative Robotics, IoT, and STEM products for the education sector. If you have hands-on experience with embedded systems and enjoy building practical learning solutions, we'd love to hear from you.Key Responsibilities<ul><li>Design and develop Robotics, IoT, and Embedded System projects.</li><li>Develop STEM kits and educational robotics products.</li><li>Set up Robotics &amp; STEM Labs for schools.</li><li>Work with Arduino, ESP32, Raspberry Pi, and Python.</li><li>Conduct technical workshops and support product demonstrations.</li><li>Mentor junior engineers and contribute to product innovation.</li></ul>Required Skills<ul><li>3+ years of experience in Robotics, IoT, or Embedded Systems.</li><li>Strong knowledge of Python and Embedded C/C++.</li><li>Hands-on experience with Arduino, ESP32, Raspberry Pi, sensors, and electronic circuits.</li><li>Knowledge of IoT protocols (Wi-Fi, Bluetooth, MQTT, HTTP).</li><li>Excellent problem-solving and communication skills.</li></ul>Preferred SkillsExperience with ROS, OpenCV, AI/ML, CAD, or 3D Printing will be an added advantage.QualificationBachelor's/Master's degree in Robotics, Electronics, Electrical Engineering, Mechatronics, Computer Science, or a related field.Why Join Us?<ul><li>Work on innovative Robotics &amp; STEM products.</li><li>Career growth and leadership opportunities.</li><li>Collaborative and innovation-driven work environment.</li></ul>Apply now and be a part of shaping the future of STEM education!Pay: ₹50,000.00 - ₹60,000.00 per monthWork Location: In person

Senior Robotics Engineer | IoT | Embedded Systems

Better Analytics Private Limited

We are looking for a motivated AI/ML Intern to join our team and work on real-world machine learning and generative AI projects. This internship offers hands-on experience in building, training, and deploying AI models while collaborating with experienced engineers and product teams.Key Responsibilities<ul><li>Assist in developing and implementing machine learning models.</li><li>Work with structured and unstructured datasets for data preprocessing and analysis.</li><li>Build and evaluate predictive models using Python and popular ML libraries.</li><li>Develop AI-powered applications using Large Language Models (LLMs) and prompt engineering.</li><li>Experiment with Retrieval-Augmented Generation (RAG) and vector databases.</li><li>Support model deployment, testing, and performance optimization.</li><li>Research emerging AI technologies and contribute innovative ideas.</li><li>Document experiments, findings, and technical implementations.</li></ul>Required Skills<ul><li>Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.</li><li>Strong programming skills in Python.</li><li>Basic understanding of machine learning concepts and algorithms.</li><li>Familiarity with libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.</li><li>Knowledge of SQL and data analysis.</li><li>Understanding of Generative AI, LLMs, or prompt engineering is a plus.</li><li>Strong analytical and problem-solving skills.</li><li>Good communication and teamwork abilities.</li></ul>Preferred Qualifications<ul><li>Experience with LangChain, LlamaIndex, or similar AI frameworks.</li><li>Familiarity with APIs, REST services, or FastAPI.</li><li>Knowledge of Git and version control.</li><li>Experience with cloud platforms (AWS, Azure, or GCP) is a plus.</li><li>Personal, academic, or open-source AI/ML projects are highly valued.</li></ul>Internship Details<ul><li>Employment Type: Internship</li><li>Duration: 3&ndash;6 months</li><li>Work Mode: On-site</li></ul>Pay: ₹15,000.00 - ₹20,000.00 per monthWork Location: In person

AI/ML Intern (Machine Learning & Generative AI)

Explore 68+ Ai ml engineer in India this July. Find roles across top companies and apply now to boost your career.