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machine learning intern

Kuku FM

<div>
 
 About The Role
 
 
 
 As a Machine Learning Engineer II in Recommendation, you will be instrumental in advancing our recommendation algorithms and content embeddings, directly driving the growth and success of our Video and Audio Stories Platform.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Recommendation Systems: Design and develop large-scale recommendation systems serving millions of users, with a strong focus on personalization, scalability, and efficiency.
 </li>
 <li>
 ML Execution: Drive the ML execution, specifically around feed ranking and recall oriented candidate generation systems.
 </li>
 <li>
 Technical Ownership: Provide guidance in ML model formulation, experimentation, and deployment. Take end-to-end ownership of ML systems, including key user satisfaction metrics.
 </li>
 <li>
 Architecture &amp; Strategy: Contribute to the architectural strategy and design of complex ML systems that meet the needs of users, and content stakeholders.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Model Training &amp; Serving: Hands-on experience training and serving large-scale ML models using frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Production Experience: Proven track record of productionising machine learning models, including designing and managing end-to-end ML systems and data pipelines.
 </li>
 <li>
 Recommendation Expertise: Direct experience in building and applying large-scale (million+ users) machine learning solutions for feed ranking and personalized recommendations.
 </li>
 <li>
 Research Awareness: Stay up-to-date with the latest advancements in recommender systems, data engineering, and applied machine learning.
 </li>
 <li>
 Education &amp; Experience: Bachelor&rsquo;s or Master&rsquo;s in Computer Science, Machine Learning, Statistics, or a related engineering field, with 2-4 years of relevant experience.
 
 
 </li>
 </ul>
 
 About KUKU
 
 
 
 Founded in 2018, KUKU is India&rsquo;s leading storytelling platform, offering a vast digital library of audio stories, short courses, and microdramas. KUKU aims to be India&rsquo;s largest cultural exporter of stories, culture and history to the world with a firm belief in &ldquo;Create In India, Create For The World&rdquo;.
 
 
 We deliver immersive entertainment and education through our OTT platforms: Kuku FM, Guru, Kuku TV, and more. With a mission to provide high-quality, personalized stories across genres from entertainment across multiple formats and languages, KUKU continues to push boundaries and redefine India&rsquo;s entertainment industry.
 
 
 🌐 Website: www.kukufm.com
 
 
 📱 Android App: Google Play
 
 
 📱 iOS App: App Store
 
 
 🔗 LinkedIn: KUKU
 
 
 📢 Ready to make an impact? Apply now!
 
 
 Skills: production experience,research awareness,model training &amp; serving,recommendation expertise
</div>

Machine Learning Engineer II

LinkedIn

<div>
 
 Company Description
 
 
 
 LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.
 
 
 
 Job Description
 
 
 
 We are looking for an Staff Machine Learning Engineer to play a pivotal role as a technical leader within the LSS AI team. This role goes beyond building models- you will set the technical direction, own the AI roadmap, and lead initiatives that push the boundaries of what's possible in enterprise AI. You will combine deep research expertise with the ability to build production-grade ML systems at scale, partnering across engineering, product, and research to deliver transformative AI solutions.
 
 
 At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Lead the design, development, and deployment of state-of-the-art ML systems across search, recommendations, generative AI, reinforcement learning, and LLMs for Sales Navigator.
 </li>
 <li>
 Define and drive the technical roadmap and architecture for end-to-end AI systems within LSS, ensuring scalability, reliability, and innovation.
 </li>
 <li>
 Research, fine-tune, and adapt large language models (LLMs) and build agentic AI systems that enable reasoning, planning, and decision-making for sales professionals.
 </li>
 <li>
 Partner with product, design, and other engineering teams to align AI solutions with business strategy and maximize impact.
 </li>
 <li>
 Drive cross-functional collaborations with horizontal AI and platform teams to leverage foundational tools and scale adoption of innovations across LinkedIn.
 </li>
 <li>
 Mentor and guide engineers, fostering a culture of craftsmanship, innovation, and technical excellence.
 </li>
 <li>
 Represent LinkedIn in external venues (papers, conferences, workshops) by showcasing advances in applied AI research and engineering.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Basic Qualifications
 
 
 <ul>
 <li>
 MS/PhD degree in Computer Science or related technical discipline, or equivalent practical experience.
 </li>
 <li>
 8+ years of experience in machine learning, artificial intelligence, or related fields.
 </li>
 <li>
 5+ years in an architect or technical leadership role driving large-scale AI initiatives.
 </li>
 <li>
 Hands-on experience with end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and optimization.
 </li>
 <li>
 Expertise in at least one of: LLMs, generative AI, search/recommendations, reinforcement learning, or large-scale deep learning.
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 10+ years of experience building and scaling machine learning systems in production.
 </li>
 <li>
 Proven experience in pre-training and fine-tuning LLMs, including domain-specific adaptations.
 </li>
 <li>
 Strong software engineering skills (Python, Java, C++, or similar), with the ability to design robust, scalable systems.
 </li>
 <li>
 Track record of influencing product and technical strategy through AI/ML innovation.
 </li>
 <li>
 Publications, patents, or open-source contributions in machine learning, NLP, or related areas.
 
 
 
 </li>
 </ul>
 Suggested Skills
 
 
 <ul>
 <li>
 Machine Learning
 </li>
 <li>
 Large Language Models
 </li>
 <li>
 Generative AI
 </li>
 <li>
 Search &amp; Recommendations
 </li>
 <li>
 Reinforcement Learning
 </li>
 <li>
 Technical Leadership
 </li>
 <li>
 Cross-Functional Collaboration
 
 
 
 </li>
 </ul>
 You Will Benefit from Our Culture
 
 
 We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
 
 
 
 Additional Information
 
 
 
 
 India Disability Policy
 
 
 
 LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
 
 
 
 Global Data Privacy Notice for Job Candidates
 
 
 
 Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
 
 
</div>

Staff Software Engineer, Machine Learning

<div>
 
 Company Description
 
 
 
 LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.
 
 
 
 Job Description
 
 
 
 Join the LSS-AI team and help create meaningful impact by connecting sellers and buyers to mutual growth opportunities! LinkedIn Sales Solutions (LSS) is one of the fastest-growing multi-billion dollar verticals at LinkedIn, and the LSS-AI team is at the forefront of building the next generation of AI-centric Sales Navigator platform. This platform enables tens of millions of companies to connect with their future customers, driving significant economic value. As a member of the LSS-AI team, you will work on cutting-edge projects, including building Agentic and GenAI-powered search and recommendation systems, tuning and applying domain-specific LLMs, and collaborating with our partner vendors like OpenAI. You will have the opportunity to work with passionate AI engineers, as well as our brilliant cross-functional partner teams in Engineering, Product Management, and Design. Together, we are creating immense economic value for our customers using the largest global professional economic graph.
 
 
 As part of a new and fast growing team of top-notch scientists and engineers, you will experience all the excitement and dynamism of a startup along with the scale and technology of a world-class enterprise.
 
 
 At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop advanced embedding models (text, graph, structured data) to capture semantic meaning of companies, people, and signals for retrieval and ranking.
 </li>
 <li>
 Design and train ranking models that optimize search relevance, entity discovery, and lead recommendations across millions of entities.
 </li>
 <li>
 Build large-scale classification models to automatically tag industries, technologies, buyer intent, and other business signals.
 </li>
 <li>
 Deploy and monitor production ML pipelines for embedding generation, model inference, and continuous retraining with real-world feedback loops.
 </li>
 <li>
 Develop state-of-the-art supervised and semi-supervised models that scale to hundreds of millions of companies, professionals, and business signals.
 </li>
 <li>
 Own end-to-end model development and deployment of embeddings, retrieval, ranking, and classification models in large-scale production environments.
 </li>
 <li>
 Mentor junior ML engineers in applying advanced machine learning techniques to core problems such as entity resolution, lead scoring, and search relevance.
 </li>
 <li>
 Represent LinkedIn in academic and industry circles by showcasing our innovation, data products and scientific expertise in bringing game-changing data products to market
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Basic Qualifications
 
 
 <ul>
 <li>
 Bachelor's degree or related practical experience
 </li>
 <li>
 2+ years of experience in at least one of the following areas: Recommendation systems, Machine Learning, Statistical modeling/inference, Data mining, Graph/geometric deep learning, Large Language Models, Generative AI, Distributed Training.
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Master's degree in computer science, statistics, engineering, mathematics, or similar quantitative discipline.
 </li>
 <li>
 3+ years of hands-on experience working on Recommendation systems, Machine Learning, Statistical modeling/inference, Data mining, Graph/geometric deep learning, Large Language Models, Generative AI, Distributed Training.
 </li>
 <li>
 Understanding of standard programming and software engineering practices
 </li>
 <li>
 Proven track record of publishing at academic and industry venues
 </li>
 <li>
 Ability and eagerness to program
 
 
 
 </li>
 </ul>
 Suggested Skills
 
 
 <ul>
 <li>
 Machine Learning
 </li>
 <li>
 Generative-AI
 </li>
 <li>
 Large Language Models
 
 
 
 </li>
 </ul>
 You will Benefit from our Culture
 
 
 We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
 
 
 
 Additional Information
 
 
 
 
 India Disability Policy
 
 
 
 LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
 
 
 
 Global Data Privacy Notice for Job Candidates
 
 
 
 Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
 
 
</div>

Software Engineer, Machine Learning

<div>
 LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world&rsquo;s workforce in ways no other company can. We&rsquo;re much more than a digital resume -- we transform lives through innovative products and technology.
 
 
 Every day, millions of posts, videos, and articles course through the LinkedIn feed, generating tens of thousands of comments every hour &mdash; and tens of millions more shares and likes.
 
 
 Join the LSS-AI team and help create meaningful impact by connecting sellers and buyers to mutual growth opportunities! LinkedIn Sales Solutions (LSS) is one of the fastest-growing multi-billion dollar verticals at LinkedIn, and the LSS-AI team is at the forefront of building the next generation of AI-centric Sales Navigator platform. This platform enables tens of millions of companies to connect with their future customers, driving significant economic value. As a member of the LSS-AI team, you will work on cutting-edge projects, including building Agentic and GenAI-powered search and recommendation systems, tuning and applying domain-specific LLMs, and collaborating with our partner vendors like OpenAI. You will have the opportunity to work with passionate AI engineers, as well as our brilliant cross-functional partner teams in Engineering, Product Management, and Design. Together, we are creating immense economic value for our customers using the largest global professional economic graph.
 
 
 As part of a new and fast growing team of top-notch scientists and engineers, you will experience all the excitement and dynamism of a startup along with the scale and technology of a world-class enterprise.
 
 
 At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
 
 
 Responsibilities:
 
 - Develop advanced embedding models (text, graph, structured data) to capture semantic meaning of companies, people, and signals for retrieval and ranking.
 
 - Design and train ranking models that optimize search relevance, entity discovery, and lead recommendations across millions of entities.
 
 - Build large-scale classification models to automatically tag industries, technologies, buyer intent, and other business signals.
 
 - Deploy and monitor production ML pipelines for embedding generation, model inference, and continuous retraining with real-world feedback loops.
 
 - Develop state-of-the-art supervised and semi-supervised models that scale to hundreds of millions of companies, professionals, and business signals.
 
 - Own end-to-end model development and deployment of embeddings, retrieval, ranking, and classification models in large-scale production environments.
 
 - Mentor junior ML engineers in applying advanced machine learning techniques to core problems such as entity resolution, lead scoring, and search relevance.
 
 - Represent LinkedIn in academic and industry circles by showcasing our innovation, data products and scientific expertise in bringing game-changing data products to market
 
 
 Basic Qualifications:
 
 - Bachelor&rsquo;s degree or related practical experience
 
 - 2+ years of experience in at least one of the following areas: Recommendation systems, Machine Learning, Statistical modeling/inference, Data mining, Graph/geometric deep learning, Large Language Models, Generative AI, Distributed Training.
 
 
 
 Preferred Qualifications:
 
 - Master&rsquo;s degree in computer science, statistics, engineering, mathematics, or similar quantitative discipline.
 
 - 3+ years of hands-on experience working on Recommendation systems, Machine Learning, Statistical modeling/inference, Data mining, Graph/geometric deep learning, Large Language Models, Generative AI, Distributed Training.
 
 - Understanding of standard programming and software engineering practices
 
 - Proven track record of publishing at academic and industry venues
 
 - Ability and eagerness to program
 
 
 Suggested Skills:
 
 - Machine Learning
 
 - Generative-AI
 
 - Large Language Models
 
 
 You will Benefit from our Culture:
 
 We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
 
 
 
 India Disability Policy
 
 LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
 
 
 Global Data Privacy Notice for Job Candidates
 
 This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal
</div>

Media.net

<div>
 
 
 SDE II &ndash; Machine Learning
 
 
 
 Location: Bangalore
 
 
 Experience: 3&ndash;6 years
 
 
 
 
 
 
 About Media.net
 
 
 
 Media.net is a global leader in ad tech, powering billions of ad impressions across web and mobile formats. Our proprietary contextual advertising and machine learning technologies serve major global publishers and advertisers.
 
 
 We focus on building intelligent systems that solve complex optimization and targeting problems at scale. If you thrive in a fast-paced, data-driven environment and are excited to work on products that impact millions of users daily, Media.net is the place for you.
 
 
 
 
 
 
 Role Overview
 
 
 
 As an SDE II &ndash; Machine Learning, you will be a core contributor in designing, building, and scaling ML-driven systems that power our real-time ad platforms. You'll be responsible for full-stack ML development&mdash;from data engineering and model development to scalable deployment&mdash;working closely with product, data science, and engineering teams.
 
 
 
 
 
 
 What You'll Do
 
 
 
 &middot; Build and deploy machine learning models for ranking, bid optimization, and click-through rate prediction.
 
 
 &middot; Design scalable and fault-tolerant data pipelines and services that serve real-time and batch ML workloads.
 
 
 &middot; Work with large volumes of structured and unstructured data to extract meaningful patterns.
 
 
 &middot; Collaborate with data scientists to convert prototypes into production-ready systems.
 
 
 &middot; Build systems to intelligently target ads and content by combining contextual and behavioral signals.
 
 
 &middot; Use LLM learning to improve ad relevance, page understanding, and user targeting.
 
 
 &middot; Continuously experiment and optimize models based on user feedback and system performance.
 
 
 
 
 
 
 Some Interesting Challenges You'll Solve
 
 
 
 &middot; Predicting CTRs and revenue across millions of unique URLs and topics in real-time.
 
 
 &middot; Solving cold-start problems with sparse data using explore-exploit frameworks.
 
 
 &middot; Matching contextual and behavioral data for enhanced user targeting.
 
 
 &middot; Designing real-time bidding systems that optimize for revenue and win rate.
 
 
 &middot; Leveraging LLMs/NLP to extract intent and context from web content.
 
 
 
 
 
 
 Tech Stack You'll Work With
 
 
 
 &middot; Languages: Python, Java, Node.js
 
 
 &middot; ML/Big Data: Apache Spark, Hadoop, TensorFlow/PyTorch, Kafka
 
 
 &middot; Databases: SQL, MongoDB, Redis, Elasticsearch
 
 
 &middot; Cloud: GCP or similar
 
 
 
 
 
 
 What We're Looking For
 
 
 
 &middot; 3&ndash;6 years of hands-on experience in software development and ML engineering.
 
 
 &middot; Strong programming and debugging skills, preferably in Python and Java.
 
 
 &middot; Experience building and deploying ML models in production environments.
 
 
 &middot; Solid understanding of ML algorithms (e.g., decision trees, gradient boosting, deep learning).
 
 
 &middot; Hands-on experience with large-scale data processing tools (e.g., Spark, Hadoop).
 
 
 &middot; Ability to design low-latency, high-throughput systems.
 
 
 &middot; Strong problem-solving and analytical skills.
 
 
 
 
 
 
 Bonus Points
 
 
 
 &middot; Prior experience with ad tech, recommender systems, or real-time bidding.
 
 
 &middot; Publications or contributions to ML research or open-source projects.
 
 
 &middot; Experience with NLP, LLMs, or Information Retrieval.
 
 
 &middot; Exposure to auction theory or game-theoretic modeling.
 
 
 
 
 
 
 Why Join Us?
 
 
 
 &middot; Work on high-impact problems that power ad delivery at scale.
 
 
 &middot; Flexible work hours, modern office spaces, and supportive teams.
 
 
 &middot; Full-stack ownership and end-to-end involvement in projects.
 
 
 &middot; Culture that values innovation, autonomy, and deep tech.
 
 
 
</div>

Software Development Engineer II (Machine Learning)

PhonePe

<div>
 
 About PhonePe Limited:
 
 
 
 Headquartered in India, its flagship product, the PhonePe digital payments app, was launched in Aug 2016. As of April 2025, PhonePe has over 60 Crore (600 Million) registered users and a digital payments acceptance network spread across over 4 Crore (40+ million) merchants. PhonePe also processes over 33 Crore (330+ Million) transactions daily with an Annualized Total Payment Value (TPV) of over INR 150 lakh crore.
 
 
 PhonePe&rsquo;s portfolio of businesses includes the distribution of financial products (Insurance, Lending, and Wealth) as well as new consumer tech businesses (Pincode - hyperlocal e-commerce and Indus AppStore Localized App Store for the Android ecosystem) in India, which are aligned with the company&rsquo;s vision to offer every Indian an equal opportunity to accelerate their progress by unlocking the flow of money and access to services.
 
 
 
 Culture:
 
 
 
 At PhonePe, we go the extra mile to make sure you can bring your best self to work, Everyday!. And that starts with creating the right environment for you. We empower people and trust them to do the right thing. Here, you own your work from start to finish, right from day one. PhonePe-rs solve complex problems and execute quickly; often building frameworks from scratch. If you&rsquo;re excited by the idea of building platforms that touch millions, ideating with some of the best minds in the country and executing on your dreams with purpose and speed, join us!
 
 
 
 Job Description:
 
 
 
 We are looking for an experienced Data Scientist with 6+ years of experience to join our team and drive impactful data-driven solutions. The ideal candidate will possess deep expertise in machine learning, statistical modeling, and big data processing, along with a proven ability to work with cross-functional teams and effectively communicate insights to stakeholders. This role requires a strategic mindset, strong leadership, and the ability to translate complex data problems into actionable business insights.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Lead and drive the development of advanced machine learning models to solve high-impact business challenges.
 </li>
 <li>
 Collaborate with stakeholders (business leaders, product managers, engineering teams) to identify opportunities where data science can add business value.
 </li>
 <li>
 Embed yourself with business to understand the strategy and propose data solutions to accelerate outcomes.
 </li>
 <li>
 Design and implement scalable data pipelines and real-time analytics solutions.
 </li>
 <li>
 Guide and mentor data scientists, fostering a culture of innovation and best practices.
 </li>
 <li>
 Conduct deep-dive analyses to extract meaningful insights from complex and large datasets.
 </li>
 <li>
 Ensure machine learning models are explainable, reproducible, and aligned with business objectives.
 </li>
 <li>
 Present findings and recommendations to key stakeholders in a clear and actionable manner.
 </li>
 <li>
 Work closely with engineering teams to deploy ML models into production environments at scale.
 </li>
 <li>
 Own end-to-end model lifecycle management, including data preprocessing, feature engineering, model training, validation, and monitoring.
 
 
 </li>
 </ul>
 
 Required Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's or Master&rsquo;s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field (Ph.D. preferred but not mandatory).
 </li>
 <li>
 6+ years of experience in data science, machine learning, or applied statistics. Experience in financial services, fintech, e-commerce, or similar data-driven industries.
 </li>
 <li>
 Strong expertise in Python, SQL with proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
 </li>
 <li>
 Solid understanding of big data technologies (Spark, PySpark, Hadoop, or similar).
 </li>
 <li>
 Hands-on experience in model deployment using cloud platforms (AWS, GCP, Azure) and ML Ops frameworks (MLflow, Kubeflow, etc.).
 </li>
 <li>
 Expertise in statistical modeling, predictive analytics.
 </li>
 <li>
 Experience working with real-time and batch-processing systems.
 </li>
 <li>
 Demonstrated ability to translate business problems into data science solutions.
 </li>
 <li>
 Excellent problem-solving, critical-thinking, and analytical skills.
 </li>
 <li>
 Strong communication and stakeholder management skills, with the ability to explain technical concepts to non-technical audiences.
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 Experience in financial services, fintech, e-commerce, or similar data-driven industries.
 
 
 </li>
 </ul>
 
 PhonePe Full Time Employee Benefits (Not applicable for Intern or Contract Roles)
 
 
 
 <ul>
 <li>
 Insurance Benefits - Medical Insurance, Critical Illness Insurance, Accidental Insurance, Life Insurance
 </li>
 <li>
 Wellness Program - Employee Assistance Program, Onsite Medical Center, Emergency Support System
 </li>
 <li>
 Parental Support - Maternity Benefit, Paternity Benefit Program, Adoption Assistance Program, Day-care Support Program
 </li>
 <li>
 Mobility Benefits - Relocation benefits, Transfer Support Policy, Travel Policy
 </li>
 <li>
 Retirement Benefits - Employee PF Contribution, Flexible PF Contribution, Gratuity, NPS, Leave Encashment
 </li>
 <li>
 Other Benefits - Higher Education Assistance, Car Lease, Salary Advance Policy
 
 
 </li>
 </ul>
 
 
 Our inclusive culture promotes individual expression, creativity, innovation, and achievement and in turn helps us better understand and serve our customers. We see ourselves as a place for intellectual curiosity, ideas and debates, where diverse perspectives lead to deeper understanding and better quality results. PhonePe is an equal opportunity employer and is committed to treating all its employees and job applicants equally; regardless of gender, sexual preference, religion, race, color or disability. If you have a disability or special need that requires assistance or reasonable accommodation, during the application and hiring process, including support for the interview or onboarding process,
 
 
 
 
 please fill out this form.
 
 
 
 
 
 
 Read more about PhonePe
 
 
 
 
 on our blog
 
 
 
 
 .
 
 
 
 
 
 Life at PhonePe
 
 
 
 
 PhonePe in the news
 
</div>

Data Scientist (6 to 8 Years)

Kaplan

<div>
 
 
 Job Description
 
 
 
 For more than 80 years, Kaplan has been a trailblazer in education and professional advancement. We are a global company at the intersection of education and technology, focused on collaboration, innovation, and creativity to deliver a best in class educational experience and make Kaplan a great place to work.
 
 
 Our offices in India opened in Bengaluru in 2018. Since then, our team has fueled growth and innovation across the organization, impacting students worldwide. We are eager to grow and expand with skilled professionals like you who use their talent to build solutions, enable effective learning, and improve students&rsquo; lives.
 
 
 The future of education is here and we are eager to work alongside those who want to make a positive impact and inspire change in the world around them.
 
 
 As a Data Scientist at Kaplan, you will play a pivotal role in driving data-informed decisions and developing cutting-edge solutions that enhance our educational products and services. You will leverage your expertise in machine learning, statistical modeling, and data analysis to extract meaningful insights from complex educational datasets. You will collaborate with product managers, engineers, and educators to identify opportunities for innovation and develop data-driven solutions that directly impact student learning and teacher effectiveness.
 
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 
 Develop and deploy advanced machine learning models:
 
 Design, implement, and evaluate machine learning models for tasks such as personalized learning recommendations, student performance prediction, content optimization, and educational resource analysis.
 </li>
 <li>
 Hands on experience in preparation of
 
 evaluation datasets
 
 and defining
 
 evaluation metrics
 
 for model training experiments.
 </li>
 <li>
 
 Conduct in-depth data analysis:
 
 Explore and analyze large datasets from various sources (e.g., student learning platforms, assessment data, user behavior logs) to identify trends, patterns, and insights that inform product development and educational strategies.
 </li>
 <li>
 
 Design and execute experiments:
 
 Develop and implement A/B testing and other experimental designs to evaluate the effectiveness of educational interventions and product features.
 </li>
 <li>
 
 Communicate insights and recommendations:
 
 Effectively communicate complex data insights and recommendations to both technical and non-technical audiences through visualizations, presentations, and reports.
 </li>
 <li>
 
 Collaborate with cross-functional teams:
 
 Work closely with product managers, engineers, educators, and researchers to define project goals, develop data-driven solutions, and ensure successful implementation.
 </li>
 <li>
 
 Stay up-to-date with the latest advancements:
 
 Continuously research and evaluate new machine learning techniques, tools, and best practices relevant to the education technology domain.
 </li>
 <li>
 
 Contribute to the development of data infrastructure:
 
 Work with data engineers to ensure data quality, accessibility, and scalability.
 </li>
 <li>
 Work on building products and features that use Generative AI
 </li>
 <li>
 Hybrid Schedule: 3 days remote / 2 days in office
 </li>
 </ul>
 
 
 
 
 
 
 Minimum Requirements:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s/Master's in Computer Science, Statistics, Mathematics, or a related field.
 </li>
 <li>
 3+ years of experience as a Data Scientist, with a proven track record of developing and deploying machine learning models in a production environment.
 </li>
 <li>
 Strong proficiency in programming languages such as Python (with libraries like scikit-learn, TensorFlow, PyTorch, pandas, NumPy) and LLMs ( ChatGPT, Gemini, Llama, Claude) etc.
 </li>
 <li>
 Strong Proficiency in Transformer Architecture, Multimodality, RAG Pipelines and Prompt Engineering.
 </li>
 <li>
 Experience with statistical modeling, data mining, and machine learning algorithms.
 </li>
 <li>
 Experience in SQL and working with relational databases.
 </li>
 <li>
 Experience working with cloud platforms (e.g., AWS, GCP, Azure).
 </li>
 <li>
 Excellent communication and presentation skills, with the ability to translate complex technical concepts into clear and concise language.
 </li>
 <li>
 Strong problem-solving and analytical skills.
 </li>
 <li>
 Experience with MLOps workflow with tools such as Weights and Biases, MLFLow etc
 </li>
 <li>
 Experience in integrating model monitoring in production
 </li>
 <li>
 Passion for education and a desire to make a positive impact on student learning.
 </li>
 <li>
 Experience with educational data and learning analytics is a plus.
 </li>
 <li>
 Experience with Natural Language Processing and CNN Models is a plus.
 </li>
 </ul>
 
 
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Publications in peer-reviewed journals or conferences related to machine learning or education technology.
 </li>
 <li>
 Experience working with large-scale educational datasets.
 </li>
 <li>
 Experience with recommender systems.
 </li>
 <li>
 Experience with time series analysis.
 </li>
 </ul>
 
 
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Data Scientist

Explore 187+ Machine learning intern in Mangaluru this September. Find roles across top companies and apply now to boost your career.

187 machine learning intern jobs IN Mangaluru

Machine Learning Engineer II

Staff Software Engineer, Machine Learning

Software Engineer, Machine Learning

Software Engineer, Machine Learning

Software Development Engineer II (Machine Learning)

Data Scientist (6 to 8 Years)

Data Scientist