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Valuebound

<div>
 Role Overview
 
 
 As a Data Scientist, you will play a key role in improving and optimising the models that drive real-time speech AI. You&rsquo;ll work on analysing, processing, and modelling data to make our systems smarter.
 
 
 
 Specifically, You&rsquo;ll
 
 
 
 <ul>
 <li>
 Develop and fine-tune Speech to Speech machine learning models
 </li>
 <li>
 Experiment with data-driven solutions to enhance AI performance.
 </li>
 <li>
 Work on feature engineering and dataset preparation to train robust models.
 </li>
 <li>
 Collaborate with the team to evaluate and deploy models into production.
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 Strong problem-solving skills, paired with a passion for learning.
 </li>
 <li>
 1-3 years of experience in Data Science and related fields.
 </li>
 <li>
 Experience with speech processing or NLP.
 </li>
 <li>
 Proficiency in Python and familiarity with data science libraries.
 </li>
 <li>
 Understanding of machine learning frameworks (e.g., TensorFlow, PyTorch).
 </li>
 <li>
 Familiarity with working on datasets and data preprocessing techniques.
 
 
 </li>
 </ul>
 Skills:- speech and Natural Language Processing (NLP)
</div>

Data Scientist

Dell Technologies

<div>
 
 Data Science Consultant
 
 
 
 Dell Content Engineering and Translation (CET) teams exist within a very complex ecosystem of departments and business units around the world that together enable Dell's commitment to excellence. As Dell expands its offerings and updates its infrastructure, CET is increasingly at the center of many fast-paced, exciting projects which require vision and technical acumen to achieve, as well as expertise at navigating administrative and political complexity.
 
 
 Join us as a
 
 Senior Data Scientist
 
 on our
 
 DevOps
 
 team in
 
 Bangalore
 
 to do the best work of your career and make a profound social impact.
 
 
 
 What You&rsquo;ll Achieve
 
 
 
 The Senior Data Scientist will join Dell&rsquo;s Content Engineering &amp; Translation (CET) organization, driving innovation at the intersection of knowledge graphs and Generative AI. This role focuses on graph-based modelling and reasoning as well as GenAI, LLMs, and agentic workflows, delivering intelligent, explainable, and scalable solutions for Dell&rsquo;s global content ecosystem. You will combine strong theoretical foundations in data science and machine learning with hands-on expertise in graph technologies, LLM integration, and multi-modal workflows.
 
 
 
 You will:
 
 
 
 <ul>
 <li>
 Collect and analyze linguistic data; implement core NLP techniques like tokenization, NER, and sentiment analysis for MT/NLG pipelines.
 </li>
 <li>
 Design reproducible experiments, establish annotation protocols, and evaluate models using metrics like BLEU, COMET, and ROUGE.
 </li>
 <li>
 Build and enrich knowledge graphs; design ontologies and schemas; optimize queries using SPARQL and Cypher.
 </li>
 <li>
 Develop GraphRAG pipelines, train graph/text embeddings, and integrate agentic frameworks (e.g., LangGraph) for multi-hop reasoning and query translation.
 </li>
 <li>
 Work with MLOps teams to deploy models with CI/CD; monitor GenAI solutions for quality and performance; communicate results to stakeholders.
 
 
 </li>
 </ul>
 
 Take the first step towards your dream career
 
 
 
 Every Dell Technologies team member brings something unique to the table. Here&rsquo;s what we are looking for with this role:
 
 
 
 Essential Requirements
 
 
 
 <ul>
 <li>
 Strong Python skills with hands-on experience in ML frameworks (PyTorch, TensorFlow) and data processing libraries.
 </li>
 <li>
 Deep understanding of NLP techniques (e.g., summarization, paraphrasing, NER, sentiment analysis) and evaluation metrics (BLEU, COMET, ROUGE, METEOR).
 </li>
 <li>
 Familiarity with LLM frameworks (LangGraph, LlamaIndex), RAG design patterns, and multi-agent orchestration with human-in-the-loop processes.
 </li>
 <li>
 Skilled in graph ML, embeddings, and semantic modeling; experienced in building GraphRAG pipelines and applying graph algorithms.
 </li>
 <li>
 Excellent communication and presentation skills; ability to document and explain complex solutions clearly.
 
 
 </li>
 </ul>
 
 Desirable Requirements
 
 
 
 <ul>
 <li>
 Experience with Agile development methodology (e.g., Scrum)
 </li>
 <li>
 Experience - 12 to 15 yrs
 
 
 </li>
 </ul>
 
 Who We Are
 
 
 
 We believe that each of us has the power to make an impact. That&rsquo;s why we put our team members at the center of everything we do. If you&rsquo;re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we&rsquo;re looking for you.
 
 
 Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.
 
 
 
 Application closing date: 30 October 2025
 
 
 
 Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here.
 
 
 
 Job ID:
 
 R276236
</div>

Consultant, Data Science

<div>
 At EY, you&rsquo;ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we&rsquo;re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.
 
 
 
 EY GDS &ndash; Data and Analytics (D&amp;A) &ndash; Senior &ndash; Senior Data Scientist
 
 
 
 Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.
 
 
 
 Responsibilities:
 
 
 
 
 Your technical responsibilities:
 
 
 
 <ul>
 <li>
 Contribute to the design and implementation of state-of-the-art AI solutions.
 </li>
 <li>
 Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
 </li>
 <li>
 Collaborate with stakeholders to identify business opportunities and define AI project goals.
 </li>
 <li>
 Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
 </li>
 <li>
 Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
 </li>
 <li>
 Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
 </li>
 <li>
 Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
 </li>
 <li>
 Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
 </li>
 <li>
 Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
 </li>
 <li>
 Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
 </li>
 <li>
 Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
 </li>
 <li>
 Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
 </li>
 <li>
 Ensure compliance with data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.
 
 
 </li>
 </ul>
 
 Requirements:
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
 </li>
 <li>
 Minimum 3-7 years of experience in Data Science and Machine Learning.
 </li>
 <li>
 In-depth knowledge of machine learning, deep learning, and generative AI techniques.
 </li>
 <li>
 Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
 </li>
 <li>
 Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
 </li>
 <li>
 Familiarity with computer vision techniques for image recognition, object detection, or image generation.
 </li>
 <li>
 Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
 </li>
 <li>
 Expertise in data engineering, including data curation, cleaning, and preprocessing.
 </li>
 <li>
 Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
 </li>
 <li>
 Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
 </li>
 <li>
 Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
 </li>
 <li>
 Understanding of data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Track record of driving innovation and staying updated with the latest AI research and advancements.
 
 
 </li>
 </ul>
 
 Good to Have Skills:
 
 
 
 <ul>
 <li>
 Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
 </li>
 <li>
 Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
 </li>
 <li>
 Implement CI/CD pipelines for streamlined model deployment and scaling processes.
 </li>
 <li>
 Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
 </li>
 <li>
 Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation.
 </li>
 <li>
 Implement monitoring and logging tools to ensure AI model performance and reliability.
 </li>
 <li>
 Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
 </li>
 <li>
 Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.
 
 
 </li>
 </ul>
 
 EY | Building a better working world
 
 
 
 EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
 
 
 Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
 
 
 Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
</div>

EY - GDS Consulting - AI And DATA -Gen AI - Senior

Nanonets

<div>
 
 
 Nanonets has a vision to help computers see the world starting with reading and understanding documents. Machine Learning (ML) is no longer a futuristic concept&mdash;it's a present-day powerhouse transforming the business landscape. Nanonets is at the forefront of this transformation, offering innovative ML solutions designed to make document related processes faster than ever before.
 
 
 
 
 
 
 From automating data extraction processes to enhancing reconciliation, our solutions are designed to revolutionize workflows, optimize operations, and unlock untapped potential for our clients. Our client footprint spans across brands such as Toyota, Boston Scientific, Bill.com and Entergy to name a few enabling businesses across a myriad of industries to unlock the potential of their visual and textual data.
 
 
 
 
 
 Here's a quick 1-minute
 
 intro video
 
 .
 
 
 
 
 
 We recently announced a series B round of $29 million in funding by Accel and are backed by the likes of existing investors including Elevation Capital &amp; YCombinator. This infusion of capital underscores our commitment to driving innovation and expanding our reach in delivering cutting-edge AI solutions to businesses worldwide.
 
 
 
 
 
 
 Read about the release here:
 
 
 
 
 https://www.forbes.com/sites/davidprosser/2024/03/12/why-enterprises-are-learning-to-love-nanonets-automation/?sh=6d79ec8f3ca1
 
 
 
 
 https://techcrunch.com/2024/03/12/nanonets-funding-accel-india/amp/
 
 
 
 
 
 
 We&rsquo;re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.
 
 
 
 
 
 
 About the role
 
 
 
 The role can be summed up as building and deploying cutting edge generalised deep learning architectures that can solve complex business problems like converting unstructured data into structured format without hand-tuning features/models. You are expected to build state of the art models that are best in the world for solving these problems, continuously experimenting and incorporating new advancements in the field into these architectures.
 
 
 
 
 
 
 What we&rsquo;re looking for
 
 
 <ul>
 <li>
 Strong Machine Learning concepts.
 </li>
 <li>
 Strong command in low-level operations involved in building architectures like Transformers, Efficientnet, ViT, Faster-rcnn, etc., and experience in implementing those in pytorch/jax/tensorflow.
 </li>
 <li>
 1-3 years of experience with the latest semi-supervised, unsupervised and few shot architectures in Deep Learning methods in NLP/CV domain.
 </li>
 <li>
 Strong command in probability and statistics.
 </li>
 <li>
 Strong programming skills.
 </li>
 <li>
 Have previously shipped something of significance, either implemented some paper or made significant changes in an existing architecture etc.
 </li>
 </ul>
 
 
 
 
 
 Ideal candidate should have the following skillset
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Tensorflow
 </li>
 <li>
 Experience building and deploying systems
 </li>
 <li>
 Experience with Theano/Torch/Caffe/Keras all useful
 </li>
 <li>
 Experience Data warehousing/storage/management would be a plus
 </li>
 <li>
 Experience writing production software would be a plus
 </li>
 <li>
 The ideal candidate should have developed their own DL architectures apart from using open source architectures.
 </li>
 <li>
 Ideal candidate would have extensive experience with computer vision applications.
 </li>
 </ul>
 
 
 
 
 
 Interesting Projects Other DL Engineers Have Completed
 
 
 <ul>
 <li>
 
 Setting New Standards:
 
 Through our
 
 Automation Benchmark
 
 , we are defining how AI systems are measured on grounding, reliability, and performance.
 </li>
 <li>
 
 Proven Adoption:
 
 Our
 
 Nanonets-OCR-S
 
 model on Hugging Face has already
 
 ~225,000 downloads
 
 , validating its global impact and utility.
 </li>
 <li>
 
 Global Recognition:
 
 Our research and open-source contributions are recognized by leading voices in AI (
 
 example
 
 ).
 </li>
 <li>
 
 Enterprise-Ready AI:
 
 Our models don&rsquo;t just output predictions - they provide
 
 grounded answers with confidence scores
 
 to enable trustworthy decision-making.
 </li>
 <li>
 
 Agentic OCR Systems:
 
 Unlike traditional OCR, our models are
 
 agentic
 
 - capable of reasoning about inputs, adapting to task context, and chaining multiple steps to deliver structured, actionable data.
 </li>
 <li>
 
 VLM + LLM Innovation:
 
 From text to vision-language, we are solving alignment, hallucination reduction, and cross-modal understanding at scale -
 
 leveraging the latest techniques like RLHF, PEFT, and advanced fine-tuning
 
 to push what&rsquo;s possible.
 </li>
 </ul>
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Understand specific customer requirements, develop and apply SOTA GenAI solutions to their workflows
 </li>
 <li>
 Develop and fine-tune OCR and Vision Language Models (text detection, recognition, entity extraction, layout understanding).
 </li>
 <li>
 Build and maintain data pipelines for documents, including cleaning, augmentation, and annotation.
 </li>
 <li>
 Implement and evaluate document parsing solutions for invoices, receipts, IDs, contracts, forms, etc.
 </li>
 <li>
 Work with LLMs/VLMs to enhance document understanding and enable intelligent reasoning over documents.
 </li>
 <li>
 Collaborate with senior engineers to deploy models in production with scalable APIs and workflows.
 </li>
 <li>
 Track and improve accuracy, robustness, and latency using proper evaluation metrics
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 
 Must-Have:
 
 
 <ul>
 <li>
 1&ndash;3 years of experience in Machine Learning / AI Engineering/ Deep Learning
 </li>
 <li>
 Strong programming skills in Python and familiarity with PyTorch or TensorFlow.
 </li>
 <li>
 Experience with data preprocessing, training, and evaluation for vision or NLP tasks.
 </li>
 <li>
 Experience working with LLMs or multimodal models (Hugging Face transformers, Nanonets-OCR-S, Qwen-VL, LLaMa).
 </li>
 <li>
 Knowledge of REST APIs, Docker, Git, Kubernetes and basic cloud deployment (AWS/GCP/Azure).
 </li>
 <li>
 Good understanding of ML fundamentals (supervised learning, evaluation metrics, error analysis)
 </li>
 <li>
 Basic understanding of agentic AI workflows (document reasoning, confidence scoring, grounding).
 </li>
 <li>
 Have previously shipped something of significance, either implemented some paper or made significant changes in an existing architecture etc.
 </li>
 <li>
 Strong problem-solving and analytical skills
 </li>
 </ul>
</div>

Junior Deep Learning Engineer

<div>
 
 Introduction
 
 
 
 In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology
 
 
 
 Your Role And Responsibilities
 
 
 
 An AI Data Scientist at IBM is not just a job title &ndash; it&rsquo;s a mindset. You&rsquo;ll leverage the watsonx,AWS Sagemaker,Azure Open AI platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients.
 
 
 We are seeking an experienced and innovative AI Data Scientist to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. You will work closely with customers, product managers, and development teams to understand business requirements and design custom AI solutions that address complex challenges. Experience with tools like Github Copilot, Amazon Code Whisperer etc. is desirable.
 
 
 Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive.
 
 
 
 Day-to-Day Duties
 
 
 
 <ul>
 <li>
 Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations.
 </li>
 <li>
 Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC
 </li>
 <li>
 Documentation and Knowledge Sharing: Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members.
 </li>
 <li>
 Industry Trends and Innovation: Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation
 
 
 </li>
 </ul>
 
 Preferred Education
 
 
 
 Master's Degree
 
 
 
 Required Technical And Professional Expertise
 
 
 
 <ul>
 <li>
 Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus.
 </li>
 <li>
 Experience and working knowledge in COBOL &amp; JAVA would be preferred
 </li>
 <li>
 Having experience in Code generation, code matching &amp; code translation leveraging LLM capabilities would be a Big plus (e.g. Amazon Code Whisperer, Github Copilot etc.)
 </li>
 <li>
 Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI.
 </li>
 <li>
 Growth mindset: Demonstrate a growth mindset to understand clients' business processes and challenges.
 </li>
 <li>
 Experience in python and pyspark will be added advantage
 
 
 </li>
 </ul>
 
 Preferred Technical And Professional Experience
 
 
 
 <ul>
 <li>
 Experience: Proven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms.
 </li>
 <li>
 Strong track record in scientific publications or open-source communities
 </li>
 <li>
 Experience in full AI project lifecycle, from research and prototyping to deployment in production environments
 </li>
 </ul>
</div>

Data Scientist-Artificial Intelligence

LeadSquared

<div>
 
 Role: SEO Executive
 
 
 
 
 Department: Marketing
 
 
 
 
 Reporting To: Associate Director Marketing
 
 
 
 
 Location: Bangalore
 
 
 
 
 Job Purpose
 
 
 
 We are looking for a data-driven and innovative SEO Specialist to help scale organic growth and lead generation for LeadSquared, a fast-growing comprehensive SaaS CRM company.
 
 
 The ideal candidate should have hands-on experience in SEO for SaaS businesses, an understanding of SEO strategies (LLMs, content optimization, and technical SEO optimizations), and a passion for leveraging data to improve search visibility and conversions.
 
 
 This role will involve executing on-page, off-page, and technical SEO strategies while working closely with content, performance marketing, and web development teams.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Execute data-driven SEO strategies to improve organic rankings, traffic, and lead generation for LeadSquared&rsquo;s website.
 </li>
 <li>
 Conduct in-depth keyword research and identify content opportunities based on search intent and B2B SaaS industry trends.
 </li>
 <li>
 Optimize website architecture, metadata, internal linking, and structured data markup to improve crawlability and search visibility.
 </li>
 <li>
 Implement AI-powered SEO techniques, such as content optimization using NLP models (ChatGPT, Jasper, SurferSEO) and automated keyword clustering.
 </li>
 <li>
 Monitor Core Web Vitals and collaborate with developers to improve site speed, mobile-friendliness, and UX optimizations.
 </li>
 <li>
 Conduct technical SEO audits, fixing issues related to crawl errors, indexing, schema markup, and JavaScript SEO.
 </li>
 <li>
 Track SEO performance metrics (organic traffic, rankings, conversions, backlinks) and generate actionable insights using GA4, Search Console, Ahrefs, and SEMrush.
 </li>
 <li>
 Assist in content optimization, entity-based SEO, and topic cluster strategies to improve authority in B2B SaaS search results.
 </li>
 <li>
 Support link-building campaigns by identifying relevant industry sites, guest posting opportunities, and partnerships.
 </li>
 <li>
 Conduct competitor analysis to benchmark against top-ranking SaaS competitors and recommend growth opportunities.
 </li>
 <li>
 Stay updated on Google&rsquo;s algorithm updates, AI advancements in search, and emerging SEO trends.
 
 
 </li>
 </ul>
 
 Skills &amp; Experience Required
 
 
 
 <ul>
 <li>
 1-3 years of hands-on SEO experience from B2B SaaS or tech industries.
 </li>
 <li>
 Strong knowledge of on-page, off-page, and technical SEO best practices.
 </li>
 <li>
 Experience with AI-powered SEO tools (ChatGPT, Jasper, Clearscope, SurferSEO, Etc).
 </li>
 <li>
 Hands-on experience with Google Analytics (GA4), Search Console, Ahrefs, SEMrush, Screaming Frog.
 </li>
 <li>
 Familiarity with content optimization, keyword research, and NLP-driven SEO strategies.
 </li>
 <li>
 Understanding of HTML, CSS, JavaScript SEO, and technical site architecture.
 </li>
 <li>
 Ability to interpret SEO data, track performance, and provide insights for optimization.
 </li>
 <li>
 Experience in B2B keyword strategy, topic clustering, and buyer-journey-based SEO.
 </li>
 <li>
 Strong analytical mindset and the ability to test and implement SEO experiments.
 </li>
 <li>
 Excellent communication and teamwork skills, with the ability to collaborate with content, development, and marketing teams.
 </li>
 </ul>
</div>

SEO Executive

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

Explore 79+ Nlp engineer in Mangaluru this October. Find roles across top companies and apply now to boost your career.