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ai ml intern machine learning generative ai

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)

Infosys

<div>
 <ul>
 <li>
 Primary skills:Domain-&gt;Turbomachinery-&gt;Steam Turbine-&gt;Rotor
 
 
 </li>
 </ul>
 Key Responsibilities Design, develop, and deploy machine learning and AI models Build and maintain data pipelines for training and inference Work on supervised and unsupervised learning algorithms Implement NLP, Computer Vision, or Deep Learning solutions Optimize models for performance, scalability, and accuracy Collaborate with data engineers, analysts, and product teams Deploy models using cloud platforms (AWS/Azure/GCP) Monitor model performance and perform continuous improvements Conduct data preprocessing, feature engineering, and model evaluation Document models, processes, and experiments Required Skills &amp; Qualifications Technical Skills Strong proficiency in Python Experience with Machine Learning libraries: Scikit-learn TensorFlow / PyTorch Knowledge of data manipulation tools (Pandas, NumPy) Experience with ML algorithms (regression, classification, clustering) Familiarity with Deep Learning frameworks Knowledge of NLP or Computer Vision techniques Experience in model deployment (APIs, microservices) Strong understanding of statistics and probability
 
 
 Preferred Skills (Nice-to-Have) Experience with Generative AI / LLMs (GPT, LangChain, Hugging Face) Knowledge of MLOps tools (MLflow, Kubeflow, Airflow) Experience with Docker and Kubernetes Familiarity with Big Data tools (Spark, PySpark) Experience with REST APIs and microservices architecture Knowledge of cloud AI services (AWS SageMaker, Azure ML, GCP AI) Understanding of vector databases and embeddings (FAISS, Pinecone) Exposure to CI/CD pipelines and DevOps practices
</div>

AI Engineers

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
Not the right fit? Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!</div>

MLOps 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

Hitachi Energy

<div>Location:
Chennai, Tamil Nadu, India
Job ID:
R0124753
Date Posted:
2026-07-01
Company Name:
HITACHI ENERGY TECHNOLOGY SERVICES PRIVATE LIMITED
Profession (Job Category):
Engineering &amp; Science
Job Schedule:
Full time
Remote:
No
Job Description:
Your Responsibilities:
<ul><li>Display technical expertise in data analytics focusing on a team of diversified technical competencies.
</li><li>Build and maintain accurate and scalable data pipeline and infrastructure such as SQL Warehouse, Data Lakes, etc. using Cloud platforms (e.g.: MS Azure, Databricks).
</li><li>Proactively work with business stakeholders to understand data lineage, definitions, and methods of data extraction.
</li><li>Write production-grade SQL and PySpark code to create data architecture.
</li><li>Consolidate SQL databases from multiple sources, data cleaning, and manipulation in preparation for analytics and machine learning.
</li><li>Use data visualization tools such as Power BI to create professional quality dashboards and reports.
</li><li>Write good quality documentation for data processing for different projects to ensure reproducibility.
</li><li>Living Hitachi Energy&rsquo;s core values safety and integrity, which means taking responsibility for your own actions while caring for your colleagues and the business.
</li></ul>Your Background:
<ul><li>BE / B.Tech in Computer Science, Data Science, or related discipline and at least 5 years of related working experience.
</li><li>5 years of data engineering experience, with understanding lake house architecture, data integration framework, ETL/ELT pipeline, orchestration/monitoring, star schema data modeling.
</li><li>5 years of experience with Python/PySpark and SQL(Proficient in PySpark, Python, and Spark SQL)
<ul><li>2-3 years of hands-on data engineering experience using Databricks as the main tool (meaning &gt;60% of their time is using Databricks instead of just occasionally).
</li><li>2-3 years of hands-on experience with different Databricks components (DLT, workflow, Unity catalog, SQL warehouse, CI/CD) in addition to using notebooks.
</li></ul></li><li>Experience in Microsoft Power BI.
</li></ul>Additional Insights:
<ul><li>Basic understanding of Machine Learning algorithms.
</li><li>Enhanced Data Processing : AI/ML can automate and improve data processing tasks, making them more efficient and accurate.
</li><li>Predictive Analytics : Integrating AI/ML can help in building predictive models that can forecast trends and outcomes, providing valuable insights for decision-making.
</li><li>Personalization : AI/ML can be used to create personalized experiences for users by analyzing their behavior and preferences.
</li><li>Automation : AI/ML can automate repetitive tasks, freeing up time for more complex and creative work.
</li><li>Ability to quickly grasp concepts from a field that is not one's core competency; A fast learning generalist capable of solving problems independently and resourceful in a matrixed corporate environment.
</li><li>Proficiency in both spoken &amp; written English language is required.
</li></ul><h2 class="jobSectionHeader">Qualified individuals with a disability may request a reasonable accommodation if you are unable or limited in your ability to use or access the Hitachi Energy career site as a result of your disability. You may request reasonable accommodations by completing a general inquiry form on our website. Please include your contact information and specific details about your required accommodation to support you during the job application process.
</h2><h2 class="jobSectionHeader">This is solely for job seekers with disabilities requiring accessibility assistance or an accommodation in the job application process. Messages left for other purposes will not receive a response.</h2></div>

Data Engineer

Sitero LLC

<div>Sitero is seeking a Senior AI Developer to design, build, and deploy next-generation AI-driven applications. You will bridge the gap between advanced machine learning models and scalable, production-ready enterprise solutions leveraging modern cloud AI platforms. 
Key Responsibilities
<ul>
<li>Application Architecture: Design robust, scalable architectures for AI-powered applications natively on the cloud.</li>
<li>Model Orchestration: Deploy and manage foundation models using AWS Bedrock and orchestrate complex prompt workflows.</li>
<li>API Development: Build and maintain secure, high-performance APIs and microservices using Python, Java, or Node.js.</li>
<li>Data Integration: Implement Retrieval-Augmented Generation (RAG) pipelines to connect internal corporate data with language models.</li>
<li>System Optimization: Optimize application latency, token throughput, and overall compute costs for AI inference.</li>
<li>Collaboration &amp; Mentorship: Partner with product teams to build AI agents and mentor junior engineers on engineering best practices.
</li></ul>Required Skills &amp; Qualifications
<ul>
<li>Education: Bachelor&rsquo;s or master&rsquo;s degree in computer science, Engineering, or a related field.</li>
<li>AI &amp; Cloud Platforms: Deep hands-on experience with AWS Bedrock, including model evaluation and agent setup.</li>
<li>AI Ecosystem: Experience with orchestration frameworks like LangChain, LlamaIndex, or the Hugging Face ecosystem.</li>
<li>Core Development: Strong software engineering proficiency in Python, Java, or Node.js.</li>
<li>Data Systems: Experience working with Vector Databases (e.g., Pinecone, Amazon OpenSearch, Milvus) and SQL/NoSQL systems.</li>
<li>Software Engineering: Solid understanding of CI/CD pipelines, Docker, Kubernetes, and Git workflows.
</li></ul>Preferred Qualifications
<ul>
<li>Experience with AWS Certified Generative AI Developer credentials or building production-grade enterprise agents.</li>
<li>Familiarity with advanced prompt optimization, guardrails, and model fine-tuning techniques.</li>
<li>5-8 years experience</li></ul></div>

Senior AI Developer

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

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