76 Autoencoders Jobs

About Us At NexusLink Services, we are passionate about building intelligent, scalable solutions that drive real-world impact. As we expand our AI/ML capabilities, were looking for a Generative AI-focused Data Scientist to join our innovative and rapidly growing team. Role Overview We are seeking an experienced Data Scientist with deep expertise in Generative AI to design and implement cutting-edge models that solve real business problems. You will work with LLMs, GANs, RAG frameworks, and transformer-based architectures to build production-ready solutions across industries. Key Responsibilities Design, develop, and fine-tune Generative AI models (LLMs, GANs, Diffusion models, etc. Work on RAG (Retrieval-Augmented Generation) and transformer-based architectures. Customize and fine-tune LLMs for domain-specific use cases. Build and manage robust ML pipelines for training, evaluation, and deployment. Collaborate with engineering teams to integrate models into real-world applications. Stay updated with the latest GenAI research, tools, and trends. Analyze model outputs, monitor performance, and ensure responsible AI use. Required Skills Strong Python skills with experience in ML/DL libraries: TensorFlow, PyTorch, HuggingFace Transformers. Deep understanding of LLMs, GANs, RAG, Autoencoders, etc. Experience with LoRA, PEFT, or similar fine-tuning techniques. Familiarity with Vector Databases (FAISS, Pinecone) and embeddings. Expertise in data preprocessing, synthetic data generation. Solid knowledge of NLP, prompt engineering, and language model safety. Hands-on experience with model deployment, APIs, and cloud platforms (AWS/GCP/Azure). Nice To Have Experience with Chatbots, Conversational AI, or AI Assistants. Familiarity with LangChain, LLMOps, or serverless model deployment. Background in MLOps, Docker/Kubernetes, and CI/CD pipelines. Exposure to OpenAI, Anthropic, Google Gemini, or Meta LLaMA. (ref:hirist.tech)

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for contributing to the development and deployment of machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms as a part of a larger team. Contributes to translating application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Contributes to developing ways to use machine learning to solve problems and discover new products, working on a portion of the problem and collaborating with more senior researchers as needed. Works with moderate guidance in own area of knowledge. Job Description Core Responsibilities About the Role: We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate events, and proactively surface operational insights across our large-scale streaming infrastructure. You’ll work at the intersection of machine learning, observability, and IT operations, collaborating closely with Platform Engineers, SREs, Incident Managers, Operators and Developers to integrate smart detection and decision logic directly into our operational workflows. This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve the reliability of streaming infrastructure that powers millions of users globally. What You’ll Do Design and tune machine learning models for event correlation, anomaly detection, alert scoring, and root cause inference Engineer features to enrich alerts using service relationships, business context, change history, and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and logs Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations, automate workflows, and ensure production readiness Contribute to the development of self-healing automation, diagnostics, and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A/B testing, offline validation, and live performance monitoring of ML models Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers, and leadership Participate in incident postmortems, providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML + rule-based systems to support dynamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs, POVs, and exploration of emerging AI/ML tools and strategies Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field 3+ years of experience building and deploying ML solutions in production environments 2+ years working with AIOps, observability, or real-time operations data Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) Experience working with SQL, time-series query languages (e.g., PromQL), and data transformation in pandas or Spark Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g., sentence-transformers, vector DBs) Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM), autoencoders, clustering (e.g., HDBSCAN), and anomaly detection Experience managing structured + unstructured data, and building features from logs, alerts, metrics, and traces Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC, AUC, calibration Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series (InfluxDB, Prometheus) databases Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git, Confluence, JIRA, & collaborative agile environments Nice To Have Experience building or contributing to the AIOps platform (e.g., Moogsoft, BigPanda, Datadog, Aisera, Dynatrace, BMC etc.) Experience working in streaming media, OTT platforms, or large-scale consumer services Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event- based alerting tools Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log summarization, retrieval-augmented generation) Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based search for observability data Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like SHAP or LIME) Experience with containerized model deployment using Docker or Kubernetes Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing Contributions to open-source ML or DevOps communities, or participation in AIOps research/benchmarking efforts Certifications in cloud architecture, ML engineering, or data science specialization Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 2-5 Years

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for developing and deploying machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms. Translates application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Develops novel ways to use machine learning to solve problems and discover new products. Has in-depth experience, knowledge and skills in own discipline. Usually determines own work priorities. Acts as resource for colleagues with less experience. Job Description About the Role: We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate events, and proactively surface operational insights across our large-scale streaming infrastructure. You’ll work at the intersection of machine learning, observability, and IT operations, collaborating closely with Platform Engineers, SREs, Incident Managers, Operators and Developers to integrate smart detection and decision logic directly into our operational workflows. This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve the reliability of streaming infrastructure that powers millions of users globally. What You’ll Do Design and tune machine learning models for event correlation, anomaly detection, alert scoring, and root cause inference Engineer features to enrich alerts using service relationships, business context, change history, and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and logs Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations, automate workflows, and ensure production readiness Contribute to the development of self-healing automation, diagnostics, and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A/B testing, offline validation, and live performance monitoring of ML models Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers and leadership Participate in incident postmortems, providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML + rule-based systems to supportnamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs, POVs, and explorationemerging AI/ML tools and strategies Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field 5+ years of experience building and deploying ML solutions in production environments 2+ years working with AIOps, observability, or real-time operations data Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) Experience working with SQL, time-series query languages (e.g., PromQL), and data transformation in pandas or Spark Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g., sentence-transformers, vector DBs) Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM), autoencoders, clustering (e.g., HDBSCAN), and anomaly detection Experience managing structured + unstructured data, and building features from logs, alerts, metrics, and traces Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC, AUC, calibration Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series (InfluxDB, Prometheus) databases Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git, Confluence, JIRA, & collaborative agile environments Nice To Have Experience building or contributing to the AIOps platform (e.g., Moogsoft, BigPanda, Datadog, Aisera, Dynatrace, BMC etc.) Experience working in streaming media, OTT platforms, or large-scale consumer services Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event- based alerting tools Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log summarization, retrieval-augmented generation) Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based search for observability data Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like SHAP or LIME) Experience with containerized model deployment using Docker or Kubernetes Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing Contributions to open-source ML or DevOps communities, or participation in AIOps research/benchmarking efforts. Certifications in cloud architecture, ML engineering, or data science specializations, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations and reports. Contributes to the company by creating patents, Application Programming Interfaces (APIs). Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 5-7 Years

Job Description: We're seeking a skilled and motivated ML/AI Engineer to join our team and drive end-to-end AI development for cutting-edge healthcare prediction models. As part of our AI delivery team you will be working on designing, developing, and deploying ML models to solve complex business challenges. Key Responsibilities: Design, develop, and deploy scalable machine learning models and AI solutions. Collaborate with engineers and product managers to understand business requirements and translate them into technical solutions. Analyse and preprocess large datasets for training and testing ML models. Experiment with different ML algorithms and techniques to improve model performance. Skills & Qualifications: Experience: B.Tech with 2-5 years of relevant experience in Machine Learning, AI, or Data Science roles. OR M.Tech, M. Statistics with 2-4 years of relevant experiencein Machine Learning, AI, or Data Science roles. Education: Bachelor's/master's degree in computer science or Statistics or any other relevant engineering / AI course from a Tier 1 or Tier 2 college. Technical Skills: Proficiency in programming languages such asPython & R Strong knowledge of classicalmachine learning algorithms with hands on experience in the following: Supervised (Classification model, regressions models) Unsupervised, (Clustering Algorithms, Autoencoders) Ensemble Models (Stacking, Bagging, Boosting techniques, Random Forest, XGBoost) Experience in data preprocessing, feature engineering, and handling large-scale datasets. Model evaluation techniques like accuracy, precision, recall, F1 score, AUC-ROC for classification, and MAE, MSE, RMSE, R-squared for regression. Explainable AI (XAI) techniques include methods like SHAP values, LIME, feature importance from decision trees, and partial dependence plots. Experience withML frameworkslikeTensorFlow, PyTorch, Scikit-learn,orKeras. Building & deploying Model APIs using framework like Flask, Fast API, Django, TensorFlow Serving etc. Knowledge ofcloud platformslike Azure (preferred), AWS, GCP and experience deploying models in such environments -> changed the wording, added points. Nice to Have: Object Oriented Programming. Familiarity withNLP, ortime seriesanalysis. -> Moving this into Nice to have, not bare min Exposure todeep learningmodels (RNN, LSTM) and working with GPUs.

About Us At NexusLink Services, we are passionate about building intelligent, scalable solutions that drive real-world impact. As we expand our AI/ML capabilities, we’re looking for a Generative AI-focused Data Scientist to join our innovative and rapidly growing team. Role Overview We are seeking an experienced Data Scientist with 4-6 years of hands-on experience and deep expertise in Generative AI to design and implement cutting-edge models that address real business challenges. You will work with LLMs, GANs, RAG frameworks , and transformer-based architectures to build scalable, production-ready solutions across industries. Key Responsibilities Design, develop, and fine-tune Generative AI models (LLMs, GANs, Diffusion models, etc.) Work on RAG (Retrieval-Augmented Generation) and transformer-based architectures Customize and fine-tune LLMs for domain-specific use cases Build and manage robust ML pipelines for training, evaluation, and deployment Collaborate with engineering teams to integrate models into real-world applications Stay updated with the latest GenAI research, tools, and trends Analyze model outputs, monitor performance, and ensure responsible AI use Required Skills 4-6 years of experience in data science or machine learning roles Strong Python skills with experience in ML/DL libraries: TensorFlow, PyTorch, HuggingFace Transformers Deep understanding of LLMs, GANs, RAG, Autoencoders, etc. Experience with LoRA, PEFT, or similar fine-tuning techniques Familiarity with Vector Databases (FAISS, Pinecone) and embeddings Expertise in data preprocessing, synthetic data generation Solid knowledge of NLP, prompt engineering, and language model safety Hands-on experience with model deployment, APIs, and cloud platforms (AWS/GCP/Azure) Nice to Have Experience with Chatbots, Conversational AI, or AI Assistants Familiarity with LangChain, LLMOps, or serverless model deployment Background in MLOps, Docker/Kubernetes, and CI/CD pipelines Exposure to OpenAI, Anthropic, Google Gemini, or Meta LLaMA

As a skilled Data Scientist specializing in Generative AI, you will be responsible for designing, developing, and deploying state-of-the-art AI models to tackle real-world business challenges. Your role will involve working with Large Language Models (LLMs), Generative Adversarial Networks (GANs), Retrieval-Augmented Generation (RAG) frameworks, and transformer architectures to create production-ready solutions. Your key responsibilities will include: - Designing, developing, and fine-tuning advanced Generative AI models such as LLMs, GANs, and Diffusion models. - Implementing and enhancing RAG and transformer-based architectures to enable contextual understanding and document intelligence. - Customizing and optimizing LLMs for specific domain applications. - Building, maintaining, and optimizing ML pipelines and infrastructure for model training, evaluation, and deployment. - Collaborating with engineering teams to integrate AI models into user-facing applications. - Staying updated with the latest trends and research in Generative AI, open-source frameworks, and tools. - Analyzing model outputs for quality and performance, ensuring adherence to ethical AI practices. To excel in this role, you should possess the following skills: - Strong proficiency in Python and deep learning frameworks like TensorFlow, PyTorch, and HuggingFace Transformers. - Deep understanding of GenAI architectures such as LLMs, RAG, GANs, and Autoencoders. - Experience in fine-tuning models using techniques like LoRA, PEFT, or equivalents. - Knowledge of vector databases like FAISS, Pinecone, and embedding generation methods. - Experience in handling datasets, preprocessing, and synthetic data generation. - Solid grasp of NLP concepts, prompt engineering, and safe AI practices. - Hands-on experience in API development, model deployment, and cloud platforms such as AWS, GCP, and Azure. By leveraging your expertise in Generative AI and staying abreast of industry advancements, you will play a crucial role in developing cutting-edge solutions to address complex business problems.,

Job Description We are seeking a skilled AI Developer with 24 years of experience to join our dynamic team. The ideal candidate will have hands-on experience in training models over images and text, with a strong focus on Generative AI (GenAI) technologies. You will collaborate with cross-functional teams to develop and deploy AI solutions that drive innovation and enhance our product Responsibilities : Design, develop, and fine-tune AI models for image and text data, utilising Generative AI techniques such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer models. Implement, train, and optimise deep learning models for Natural Language Processing (NLP), Computer Vision (CV), and multimodal AI tasks. Manage the end-to-end lifecycle of AI projects, including data collection, pre-processing, model training, evaluation, and deployment. Collaborate with data scientists, software engineers, and product managers to integrate AI solutions into existing systems and products. Stay abreast of the latest advancements in AI research and apply innovative techniques to solve complex problems. Ensure ethical AI development practices, prioritising fairness, transparency, and privacy in all AI Skills and Qualifications : Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 2 - 4 years of hands-on experience in developing AI solutions, with a focus on Generative AI models. Proficiency in programming languages such as Python and experience with AI frameworks like TensorFlow, PyTorch, or Keras. Strong understanding of deep learning algorithms, particularly in generative models like GANs, VAEs, and transformer architectures. Experience in pre-processing and augmenting large datasets for training AI models. Familiarity with cloud platforms (AWS, GCP, Azure) for model training and deployment. Excellent problem-solving skills and the ability to work collaboratively in a team Skills : Experience with Natural Language Processing (NLP) techniques and frameworks. Knowledge of MLOps practices and tools for continuous integration and deployment of AI models. Familiarity with ethical AI practices, including strategies for mitigating bias and ensuring responsible AI usage. (ref:hirist.tech)

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Description Summary: What you need to know about the role- Data scientists are highly motivated team players with strong analytical skills who specialize in creating, driving and executing initiatives to mitigate fraud on PayPal’s platform and improve the experience for PayPal’s hundreds of millions of customers, while guaranteeing compliance with regulations. Meet our team Data scientists in the Fraud Risk team are problem solvers suited to approach varied challenges in complex big data environments. Our core goals are to enable seamless and delightful experiences to our customers, while preventing threat actors from accessing customers’ financial instruments and personal information. As part of our day-to-day job, we are collaborating with a wide variety of partners: product owners, data scientists, security experts, legal consults, and engineers, to bring our data science insights to life, impacting the experience and security of millions of customers around the globe. Job Description: Your way to impact Data scientists deeply understand PayPal’s business objectives, as their impact on PayPal’s top and bottom lines is immense. As a data scientist, you will develop key AIML capabilities, tools, and insights with the aim of adapting PayPal’s advanced proprietary fraud prevention and experience mechanisms and enabling growth. Your day to day Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets. What Do You Need To Bring- Strong proficiency in Python for data analysis, machine learning, and automation. Solid understanding of supervised and unsupervised AI/machine learning methods (e.g., XGBoost, LightGBM, Random Forest, clustering, isolation forests, autoencoders, neural networks, transformer-based architectures). Experience in payment fraud, AML, KYC, or broader risk modeling within fintech or financial institutions. Experience developing and deploying ML models in production using frameworks such as scikit-learn, TensorFlow, PyTorch, or similar. Hands-on experience with LLMs (e.g., OpenAI, LLaMA, Claude, Mistral), including use of prompt engineering, retrieval-augmented generation (RAG), and agentic AI to support internal automation and risk workflows. Ability to work cross-functionally with engineering, product, compliance, and operations teams. Proven track record of translating complex ML insights into business actions or policy decisions. BS/BA degree with 5+ years of related professional experience or master’s degree with 4+ years of related experience. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply. REQ ID R0127046

About Aezion Aezion is one of the premiere custom software providers in United States. and we live by the adage that our word is our bond. Our Promise is to get it right or make it right. We accomplish this by investing the effort to exceed client expectations from start to finish - architecting, designing, developing, hosting, deploying, maintaining, and supporting our clients throughout the project lifecycle. We believe that work is ministry – an expression of our values. Our goal is to honor our commitments to clients and the life energies of Aezion employees through results that transform clients into lifelong partners. Position Description Job Title: AI/ML Architct Job Summary: We are looking for an innovative AI/ML Engineer to join our team and work on cutting-edge machine learning and artificial intelligence projects. The ideal candidate will have experience in building, deploying, and optimizing AI/ML models, along with a strong foundation in data science, programming, and algorithms. You will help drive the development of intelligent systems that leverage machine learning to solve real-world problems and improve business outcomes. Key Responsibilities: Data Preparation and Analysis: Ability to understand large datasets, preprocess them, and extract features Data Preprocessing Techniques: Knowledge of normalization, feature encoding, and handling missing values Data Cleaning: Identifying and rectifying errors, outliers, and missing values within datasets Design, develop, and implement machine learning & Deep Learning (FNN, CNN, RNN) models, with a focus on LLMs, generative AI, and fraud detection systems. Deploy and maintain ML models in AWS or any other cloud environments. Optimize model performance and scalability. Collaborate with cross-functional teams to integrate AI solutions into existing applications. Develop and maintain APIs (RESTful) for AI model integration. Implement MLOps best practices to streamline the ML lifecycle. Stay up-to-date with the latest advancements in AI/ML and incorporate new techniques into our workflow. Develop and implement fraud detection models to identify and prevent fraudulent activities. Evaluate model performance using appropriate metrics and techniques, ensuring high accuracy and reliability. Experience with Machine Learning Libraries and Frameworks: Familiarity with tools like TensorFlow, PyTorch, and scikit-learn, Keras GenAI Developer Job Description We are seeking a talented Generative AI Developer to join our innovative team. The ideal candidate will have a strong background in AI and machine learning, with a focus on generative models and large language models (LLMs). You will work closely with cross-functional teams to conceptualize, design, test, and deploy AI projects that drive innovation and provide value in the rapidly evolving field of artificial intelligence. Join us and be part of a dynamic team that is shaping the future of AI. Advanced Programming Knowledge: Mastery in programming languages like Python and expertise in AI-specific libraries such as TensorFlow, PyTorch, and Keras. Proficiency in implementing and manipulating complex algorithms essential for generative AI development. Generative Models Expertise: In-depth experience with Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Ability to design, train, and optimize these models for generating high-quality and creative content. Natural Language Processing (NLP): Strong background in text generation techniques, including text parsing, sentiment analysis, and the use of transformers like GPT models for advanced text-based applications. Vector Databases: Hands-on experience with vector databases such as Pinecone, PgVector, and Qdrant for efficient retrieval and similarity search. Embedding, Retrieval-Augmented Generation (RAG), and Indexing: Expertise in creating embeddings, implementing RAG workflows, and indexing vector databases to improve search, retrieval, and contextual generation. LangChain and LangGraph: Expertise in building advanced workflows and applications using LangChain for LLM-based solutions and LangGraph for structured workflows with conditional logic. FastAPI and Microservices: Proficiency in building scalable, RESTful FastAPI applications and microservices architectures for deploying AI solutions. LangSmith and LangFuse: Experience using LangSmith for debugging and evaluation of LLM chains, and LangFuse for logging and analytics in LLM applications. Cloud Computing and Deployment: Expertise in deploying and managing AI applications on cloud platforms such as AWS, Google Cloud, and Microsoft Azure. Familiarity with Docker for containerization and Kubernetes for scaling and orchestration.

Senior Assistant Vice President EXL/SAVP/1403930 Digital SolutionsNoida Posted On 27 Jun 2025 End Date 11 Aug 2025 Required Experience 5 - 10 Years Basic Section Number Of Positions 1 Band D2 Band Name Senior Assistant Vice President Cost Code G090154 Campus/Non Campus NON CAMPUS Employment Type Permanent Requisition Type New Max CTC 6000000.0000 - 6500000.0000 Complexity Level Not Applicable Work Type Hybrid – Working Partly From Home And Partly From Office Organisational Group EXL Digital Sub Group Digital Solutions Organization Digital Solutions LOB Product Practice Market SBU GenAI R&D Country India City Noida Center Noida - Centre 59 Skills Skill NLP AI PYTHON Minimum Qualification B.TECH/B.E Certification No data available Job Description Job Summary As part of the EXL Digital AI Innovation team, you will work as a R&D in the Innovation unit supporting all EXL Business Units. You will be exposed to hundreds of different enterprise GenAI business use cases and help our clients create value architecting GenAI applications and solutions. This role involves working on cutting-edge Generative AI technologies to drive significant revenue growth, operational efficiencies, and enhanced customer experiences for our Fortune 1000 enterprise clients across various industries in insurance, healthcare, banking & financial services, media, and retail. You will work with a team of talented data scientists, AI researchers, software engineers, ML engineers, project managers and delivery managers helping them in deploying advanced AI technologies. You’ll design AI systems & architectures at scale, improve AI Governance and responsible, LLM selection(GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) & fine-tuning PEFT LoRa/QLoRa adapters, RAG, LLM Prompt Engineering, Agentic AI, AutoGen, AI Autonomous Agents, Multimodal LLMs and LLM orchestration architectures for enterprise data at scale in Python. Key Responsibilities Experience of architecting AI systems to solve complex business problems. Build advanced RAG pipelines, text chunking, and retrieval, LLM Prompt Engineering, using Vector Databases. Implement right LLM selection based on use cases and client criteria (GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) while managing trifecta of accuracy, cost, and latency/scale. Develop, fine-tune, context tune and implement state-of-the-art NLP models including Large Language Models like GPT, Llama3.1, Claude, BLOOM, Flan-T5, Falcon etc. fine-tuning PEFT LoRa/QLoRa adapters design AI systems & architectures, while considering good Responsible AI standards and AI Governance. Build Agentic AI, AutoGen, Muti-agents use cases, AI Autonomous Agents and LLM orchestration architectures for enterprise data at scale in Python. Hands on experience with complementary technologies around LLMs like embedders, vector databases (chroma, weaviate etc.), orchestration tools like Langchain, LlamaIndex etc. Conduct research and experimentation to improve existing models and propose novel approaches. Collaborate with cross-functional teams to integrate generative AI solutions into real-world applications. Stay up-to-date with the latest advancements in deep learning and generative models and apply them to enhance our AI capabilities. Document research findings, prepare technical reports, and contribute to whitepaper/scientific publications. Provide deep leadership and coaching in the project delivery lifecycle. Focus on shared learning, continuous improvement, and drive adoption of best practices. Qualifications Education and Experience: Masters of Science or PhD in computer science, data science, statistics, Natural Language Processing 2-3 years of experience in GenAI and Large Language Models. Hands-on experience with current deep learning frameworks (e.g., PyTorch, TensorFlow) as evidenced by released code (e.g., GitHub repositories – version control awareness). Solid understanding of optimization techniques for training deep neural networks, regularization methods, and hyperparameter/fine tuning. Experience in Generative AI Models and LLMs, finetuning LLMs, prompt engineering and experience with LLM orchestration frameworks like Langchain, LlamaIndex, RAGAS, etc. Strong software engineering skills for rapid and accurate development of AI models and systems. Understanding of Agentic AI, Autonomous Agents, AI Agents, AutoGen, Crew.ai, Langchain, and workflow steps design. NVIDIA Blueprints. Google AI Agents. Provide business-oriented solution with ability to communicate effectively, both verbally and in writing, with technical and non-technical stakeholders. Experience working in a collaborative environment, contributing to multidisciplinary teams and projects. Proven ability to solve complex problems, think creatively, and adapt to evolving research trends. Skills and Competencies: 5 years of experience in AI, NLP including transformer architecture and LLMs, Computer Vision and related technologies Excellent communication and problem-solving skills. Working with cross-functional teams across different stakeholders. Ability to explain GenAI to non-technical audiences across many different industries. Ability to do GenAI Architecture solutioning for existing clients and potential clients. People leadership skills. Candidate is also hands on developer while people managing Data Scientists, ML Engineers etc. Experience in ML Engineering and MLOps, MLFlow Strong understanding of statistical and machine learning concepts Experience with deep learning frameworks such as TensorFlow and PyTorch Familiarity with key concepts and techniques used in generative models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and flow-based models. Strong programming skills in languages such as Python, along with experience working with popular deep learning frameworks like PyTorch and TensorFlow. Understanding of Graph Database and/or Vector Database along with knowledge of cloud services (e.g., AWS, Azure, GCP). Experience with deploying AI models in production environments. Familiarity with domain-specific applications of generative AI Leveraged both Azure and AWS for model inferencing. For finetuning, he has worked more on AWS SageMaker. Has used different retrieval, reranking, and generation techniques based on the use case complexity and the metrics required. Has played multiple roles in the past, such as an individual contributor, a solution architect, a mentor, a trainer, and a people manager. He also participates in RFI, RFP, thought leadership, and business development activities. Workflow Workflow Type Digital Solution Center

Job Summary As part of the EXL Digital AI Innovation team, you will work as a R&D in the Innovation unit supporting all EXL Business Units. You will be exposed to hundreds of different enterprise GenAI business use cases and help our clients create value architecting GenAI applications and solutions. This role involves working on cutting-edge Generative AI technologies to drive significant revenue growth, operational efficiencies, and enhanced customer experiences for our Fortune 1000 enterprise clients across various industries in insurance, healthcare, banking & financial services, media, and retail. You will work with a team of talented data scientists, AI researchers, software engineers, ML engineers, project managers and delivery managers helping them in deploying advanced AI technologies. You’ll design AI systems & architectures at scale, improve AI Governance and responsible, LLM selection(GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) & fine-tuning PEFT LoRa/QLoRa adapters, RAG, LLM Prompt Engineering, Agentic AI, AutoGen, AI Autonomous Agents, Multimodal LLMs and LLM orchestration architectures for enterprise data at scale in Python. Key Responsibilities Experience of architecting AI systems to solve complex business problems. Build advanced RAG pipelines, text chunking, and retrieval, LLM Prompt Engineering, using Vector Databases. Implement right LLM selection based on use cases and client criteria (GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) while managing trifecta of accuracy, cost, and latency/scale. Develop, fine-tune, context tune and implement state-of-the-art NLP models including Large Language Models like GPT, Llama3.1, Claude, BLOOM, Flan-T5, Falcon etc. fine-tuning PEFT LoRa/QLoRa adapters design AI systems & architectures, while considering good Responsible AI standards and AI Governance. Build Agentic AI, AutoGen, Muti-agents use cases, AI Autonomous Agents and LLM orchestration architectures for enterprise data at scale in Python. Hands on experience with complementary technologies around LLMs like embedders, vector databases (chroma, weaviate etc.), orchestration tools like Langchain, LlamaIndex etc. Conduct research and experimentation to improve existing models and propose novel approaches. Collaborate with cross-functional teams to integrate generative AI solutions into real-world applications. Stay up-to-date with the latest advancements in deep learning and generative models and apply them to enhance our AI capabilities. Document research findings, prepare technical reports, and contribute to whitepaper/scientific publications. Provide deep leadership and coaching in the project delivery lifecycle. Focus on shared learning, continuous improvement, and drive adoption of best practices. Qualifications Education and Experience: Masters of Science or PhD in computer science, data science, statistics, Natural Language Processing 2-3 years of experience in GenAI and Large Language Models. Hands-on experience with current deep learning frameworks (e.g., PyTorch, TensorFlow) as evidenced by released code (e.g., GitHub repositories – version control awareness). Solid understanding of optimization techniques for training deep neural networks, regularization methods, and hyperparameter/fine tuning. Experience in Generative AI Models and LLMs, finetuning LLMs, prompt engineering and experience with LLM orchestration frameworks like Langchain, LlamaIndex, RAGAS, etc. Strong software engineering skills for rapid and accurate development of AI models and systems. Understanding of Agentic AI, Autonomous Agents, AI Agents, AutoGen, Crew.ai, Langchain, and workflow steps design. NVIDIA Blueprints. Google AI Agents. Provide business-oriented solution with ability to communicate effectively, both verbally and in writing, with technical and non-technical stakeholders. Experience working in a collaborative environment, contributing to multidisciplinary teams and projects. Proven ability to solve complex problems, think creatively, and adapt to evolving research trends. Skills And Competencies 5 years of experience in AI, NLP including transformer architecture and LLMs, Computer Vision and related technologies Excellent communication and problem-solving skills. Working with cross-functional teams across different stakeholders. Ability to explain GenAI to non-technical audiences across many different industries. Ability to do GenAI Architecture solutioning for existing clients and potential clients. People leadership skills. Candidate is also hands on developer while people managing Data Scientists, ML Engineers etc. Experience in ML Engineering and MLOps, MLFlow Strong understanding of statistical and machine learning concepts Experience with deep learning frameworks such as TensorFlow and PyTorch Familiarity with key concepts and techniques used in generative models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and flow-based models. Strong programming skills in languages such as Python, along with experience working with popular deep learning frameworks like PyTorch and TensorFlow. Understanding of Graph Database and/or Vector Database along with knowledge of cloud services (e.g., AWS, Azure, GCP). Experience with deploying AI models in production environments. Familiarity with domain-specific applications of generative AI Leveraged both Azure and AWS for model inferencing. For finetuning, he has worked more on AWS SageMaker. Has used different retrieval, reranking, and generation techniques based on the use case complexity and the metrics required. Has played multiple roles in the past, such as an individual contributor, a solution architect, a mentor, a trainer, and a people manager. He also participates in RFI, RFP, thought leadership, and business development activities.

Data Scientist — Quantitative Machine Learning Location Hyderabad (preferred) — hybrid friendly. Exceptional remote candidates within India will be considered. About InvestorAi InvestorAi is an AI-first fintech that transforms vast, noisy market data into real-time, alpha-generating insights for global investors. Our proprietary “spatial-ordering” pipelines, genetic-algorithm search, and deep-learning mixture-of-experts have delivered a 45 % CAGR while remaining lean and profitable. With new capital and an ambitious roadmap, we’re scaling research and production deployment of models that trade live capital every day. Our Al algorithms have been trained and developed by our expert tam at Bridgeweave Labs using 14 years of stock market data. We perform over 35 million computations using sophisticated AI techniques like Computer Vision, Convolutional Neural Networks, Genetic Algorithms etc. to produce the best possible investment ideas. We have over 2 years of track record of producing exceptional results and outlier win rates for our investors. Why this role matters Model ownership, end-to-end: You’ll design, train, validate, and deploy production-grade models that directly drive portfolio decisions and P&L. Cutting-edge R&D: Work on entropy-based initializers, hybrid CNN/Transformer architectures, and Optuna-driven hyper-parameter searches—ideas that rarely escape academia. Massive impact: A single improvement in signal quality or latency can unlock millions in incremental alpha. Key Responsibilities Area What You’ll Own Research & Signal Discovery Ideate and prototype novel features from tick-level, fundamental, and alternative data; explore quantum-inspired ordering, autoencoders, time-series augmentations. Model Development Build, iterate, and benchmark CNNs, Transformers, GNNs, and Mixture-of-Experts using TensorFlow/PyTorch ; run large-scale Optuna sweeps on our GPU cluster. Deployment & MLOps Package models as Docker images, publish to our Kubernetes-based inference platform, and write CI/CD tests to ensure reproducible builds and seamless rollbacks. Performance Monitoring Create dashboards for live AUC-ROC, precision-recall, drawdown, beta, and slippage; set alert thresholds and conduct post-mortems when KPIs drift. Cross-functional Collaboration Partner with quant researchers, portfolio managers, and full-stack engineers to push models from Jupyter notebooks into live trading strategies. Documentation & Knowledge Sharing Draft technical memos, run code-reviews, and mentor junior analysts on best practices in robust ML for finance. Must-Have Qualifications 3 – 6 years building and shipping ML models in production (preferably finance, ad-tech, or other latency-sensitive domains). Expert-level Python plus strong grasp of TensorFlow or PyTorch ; comfortable profiling GPU memory and optimizing kernels. Proven experience with model deployment (Docker, Kubernetes, CI/CD, feature stores, model registries). Solid understanding of statistics, probability, and time-series analysis; able to articulate bias-variance trade-offs and back-test pitfalls. Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; a Master’s degree is preferred. Hands-on with SQL and at least one distributed data tool (Spark, Dask, or Ray). Clear, concise communicator—capable of translating technical findings into investor-friendly language. Nice-to-Have Extras Familiarity with trading venues, order-book dynamics, and transaction-cost analysis. Contributions to open-source ML libraries or finance-related GitHub projects. Experience with Optuna, genetic algorithms, or Bayesian optimization frameworks. Knowledge of Von Neumann entropy, quantum-inspired computing, or information-theoretic model selection. Comfort working in a start-up-style, high-ownership culture (you build it, you run it) What We Offer Work with best brains in Data Science and cutting edge modelling to solve complex finance problems Competitive salary + performance bonus tied to desk P&L. ESOP after probation. Comprehensive health insurance (self & family). Annual professional-development budget (courses, conferences, journals). 18 days paid vacation + flexible wellness leave.  How to Apply 1.Email Smriti5991@gmail.com with subject line “Data Scientist — Your Name”. 2.Attach your CV (≤ 2 pages) and link to a GitHub repo or notebook showcasing a project you took all the way to deployment . 3.Short-listed candidates complete a programming test (feature engineering, model training, deployment script) followed by two technical interviews and a culture chat with the founders. We hire for curiosity, rigor, and ownership. If you’re excited by the idea of shipping ML that lives (and profits) in the wild, we’d love to meet you.

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Description Summary: What you need to know about the role- Data scientists are highly motivated team players with strong analytical skills who specialize in creating, driving and executing initiatives to mitigate fraud on PayPal’s platform and improve the experience for PayPal’s hundreds of millions of customers, while guaranteeing compliance with regulations. Meet our team Data scientists in the Fraud Risk team are problem solvers suited to approach varied challenges in complex big data environments. Our core goals are to enable seamless and delightful experiences to our customers, while preventing threat actors from accessing customers’ financial instruments and personal information. As part of our day-to-day job, we are collaborating with a wide variety of partners: product owners, data scientists, security experts, legal consults, and engineers, to bring our data science insights to life, impacting the experience and security of millions of customers around the globe. Job Description: Your way to impact Data scientists deeply understand PayPal’s business objectives, as their impact on PayPal’s top and bottom lines is immense. As a data scientist, you will develop key AIML capabilities, tools, and insights with the aim of adapting PayPal’s advanced proprietary fraud prevention and experience mechanisms and enabling growth. Your day to day Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets. What Do You Need To Bring- Strong proficiency in Python for data analysis, machine learning, and automation. Solid understanding of supervised and unsupervised AI/machine learning methods (e.g., XGBoost, LightGBM, Random Forest, clustering, isolation forests, autoencoders, neural networks, transformer-based architectures). Experience in payment fraud, AML, KYC, or broader risk modeling within fintech or financial institutions. Experience developing and deploying ML models in production using frameworks such as scikit-learn, TensorFlow, PyTorch, or similar. Hands-on experience with LLMs (e.g., OpenAI, LLaMA, Claude, Mistral), including use of prompt engineering, retrieval-augmented generation (RAG), and agentic AI to support internal automation and risk workflows. Ability to work cross-functionally with engineering, product, compliance, and operations teams. Proven track record of translating complex ML insights into business actions or policy decisions. BS/BA degree with 5+ years of related professional experience or master’s degree with 4+ years of related experience. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply. REQ ID R0127046

Experience: 5+ years Location: S.G. Highway, Ahmedabad Send CV: hr@isummation.com Job Description: We are seeking a skilled AI Developer with 2–4 years of experience to join our dynamic team. The ideal candidate will have hands-on experience in training models over images and text, with a strong focus on Generative AI (GenAI) technologies. You will collaborate with cross-functional teams to develop and deploy AI solutions that drive innovation and enhance our product offerings. Key Responsibilities: Design, develop, and fine-tune AI models for image and text data, utilising Generative AI techniques such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer models. Implement, train, and optimise deep learning models for Natural Language Processing (NLP), Computer Vision (CV), and multimodal AI tasks. Manage the end-to-end lifecycle of AI projects, including data collection, pre-processing, model training, evaluation, and deployment. Collaborate with data scientists, software engineers, and product managers to integrate AI solutions into existing systems and products. Stay abreast of the latest advancements in AI research and apply innovative techniques to solve complex problems. Ensure ethical AI development practices, prioritising fairness, transparency, and privacy in all AI solutions. Required Skills and Qualifications : Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 2–4 years of hands-on experience in developing AI solutions, with a focus on Generative AI models. Proficiency in programming languages such as Python and experience with AI frameworks like TensorFlow, PyTorch, or Keras. Strong understanding of deep learning algorithms, particularly in generative models like GANs, VAEs, and transformer architectures. Experience in pre-processing and augmenting large datasets for training AI models. Familiarity with cloud platforms (AWS, GCP, Azure) for model training and deployment. Excellent problem-solving skills and the ability to work collaboratively in a team environment. Preferred Skill s: Experience with Natural Language Processing (NLP) techniques and frameworks . Knowledge of MLOps practices and tools for continuous integration and deployment of AI models . Familiarity with ethical AI practices, including strategies for mitigating bias and ensuring responsible AI usag e.

Data science internship at Sekuen LLC About Sekuen https://www.sekuen.com/blog Sekuen is an AI agency located in Dubai, offering AI solutions in several industries like regulation tech, biotech, adtech etc Some of our recent products include: Building AI agents that monitor changes in regulations for green ESG building regulations in Germany. Building a 700 classes (IAB taxonomy) video classifier with 98% accuracy. Building AI agents for live monitoring in FDA regulations in order to help meds formulation passing the new regulations exams Location Dubai, UAE Remote available Duration 3-4 months At the end of which the company proceeds to a student evaluation protocol. This position could open the door to full time later depending on the availability and at the discretion of the company executives. Starting Within 4 weeks Immediate preferable Compensation Select Internship Allowances available Language English Arabic (optional) Working hours Full time, 40 hours per week Monday-Friday 11 am to 8 pm GST (Dubai time) What will you learn? Working with Sekuen LLC, you will get exposed to most of the following hot topics in data science Matrix multiplication, matrix inversion, Eigendecomposition, SVD SVM, Logistic regression, KNN, K-means Decision trees, Random Forests, XGBOOST Autoencoders, Transformers, attention FFT, Laplace transform GAN, generative and agentic AI NN, RNN, CNN, Reinforcement learning NLP, text cleanups, LLM generators, recommenders, publications classification Social media video marketing Prerequisites Should be able to present some previous/current ML/AI projects Full time availability for the full duration Proven excellence and distinction in maths and data science applications Python, Colab are prerequisites NLP, CNN, Bitbucket/Git and version control are a plus Scientific background is desirable (Phys, Chem, Bio, Med, Pharma) Nail your interview Basic intro to NLP https://www.youtube.com/playlist?list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S Basics of machine learning algorithms https://www.youtube.com/@SerranoAcademy Basics of mathematics https://www.youtube.com/@3blue1brown Advanced machine learning for control https://www.youtube.com/@Eigensteve/ Desired but not mandatory Certified Agentic AI Professional (GSDC) AAIA (Advanced in AI Audit, ISACA) Certified AI Transformation Leader (CAITL) Artificial Intelligence Governance Professional (AIGP, IAPP) Salesforce AI Associate Cloud certifications (AWS/GCP/Azure) Professional Data Science/AI certificates Know your interviewer https://www.linkedin.com/in/samirzein/ How to apply? Write a 3-4 paragraphs email to career@sekuen.com Explain why you are the best fit for the above and attach a 1 page CV , listing mostly projects related to ML/DL you performed in the past, and your curriculum in math Subject/title of your message “Sekuen data science internship 2025”

About KnowBe4 KnowBe4, the provider of the world's largest security awareness training and simulated phishing platform, is used by tens of thousands of organizations around the globe. KnowBe4 enables organizations to manage the ongoing problem of social engineering by helping them train employees to make smarter security decisions, every day. Fortune has ranked us as a best place to work for women, for millennials, and in technology for four years in a row! We have been certified as a "Great Place To Work" in 8 countries, plus we've earned numerous other prestigious awards, including Glassdoor's Best Places To Work. Our team values radical transparency, extreme ownership, and continuous professional development in a welcoming workplace that encourages all employees to be themselves. Whether working remotely or in-person, we strive to make every day fun and engaging; from team lunches to trivia competitions to local outings, there is always something exciting happening at KnowBe4. Please submit your resume in English. Are you a forward-thinking data scientist, poised to lead with innovation? At KnowBe4, you'll be able to shape a career as distinctive as your expertise, supported by our global reach, inclusive ethos, and cutting-edge technology. As a Data Scientist, you'll be at the forefront of crafting impactful, data-driven solutions, collaborating with talented teams in a dynamic, fast-paced environment. Join us in creating an extraordinary path for your professional growth and making a meaningful impact in the working world. Data scientists design data modeling processes, create algorithms and predictive models to be used by software engineers for developing new and exciting products for KnowBe4’s customers, alongside other engineers in a fast-paced, agile development environment. Responsibilities Research, design, and implement Machine Learning, Deep Learning algorithms to solve complex problems Communicate complex concepts and statistical models to non-technical audiences through data visualizationsPerforms statistical analysis and using results to improve models Identify opportunities and formulate data science / machine learning projects to optimize business impact Serve as a subject matter expert in data science and analytics research, and adopt the new tooling and methodologies in Knowbe4 Manage the release, maintenance, and enhancement of machine learning solutions in a production environment via multiple deployment options such as APIs, embedded software, or stand-alone applications Advise various teams on Machine Learn Practices and ensure the highest quality and compliance standards for ML deployments Design and develop cyber security awareness products and features using Generative AI, machine learning, deep learning, and other data ecosystem technologies. Collaborate with cross-functional teams to identify data-related requirements, design appropriate NLP experiments, and conduct in-depth analyses to derive actionable insights from unstructured data sources. Staying updated with the latest advancements in machine learning, deep learning, and generative AI through self-learning and professional development. Research, design, and implement Machine Learning, Deep Learning algorithms to solve complex problems Communicate complex concepts and statistical models to non-technical audiences through data visualizationsPerforms statistical analysis and using results to improve models Identify opportunities and formulate data science / machine learning projects to optimize business impact Serve as a subject matter expert in data science and analytics research, and adopt the new tooling and methodologies in Knowbe4 Manage the release, maintenance, and enhancement of machine learning solutions in a production environment via multiple deployment options such as APIs, embedded software, or stand-alone applications Advise various teams on Machine Learn Practices and ensure the highest quality and compliance standards for ML deployments Requirements BS or equivalent plus 10 years experience MS or equivalent plus 5 years experience Ph.D. or equivalent plus 4 years experience Expertise working experience with programming languages like Python, R, and SQL Solid understanding of statistics, probability, and machine learning 10+ years of relevant experience in designing ML/DL/GenAI systems Expertise in rolling out Generative AI SAAS product and features. Expertise in AWS ecosystem. Proficiency in machine learning algorithms and techniques, including supervised and unsupervised learning, classification, regression, clustering, and dimensionality reduction. Strong understanding and practical experience with deep learning frameworks such as TensorFlow or PyTorch. Ability to design, train, and optimize deep neural networks for various tasks like image recognition, natural language processing, and recommendation systems. Knowledge and experience in generative models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Ability to create and use generative models for tasks such as image generation, text generation, and data synthesis. Exposure to LLMs, Transformers, and a few technologies like Langchain, Llamaindex, Pinecone, Sagemaker Jumpstart, Chatgpt, AWS Bedrock, and VertexAI. Strong data manipulation skills, including data cleaning, preprocessing, and feature engineering. Experience with data manipulation libraries like Pandas. Ability to create compelling data visualizations using tools like Matplotlib or Seaborn to communicate insights effectively. Proficiency in NLP techniques for text analysis, sentiment analysis, entity recognition, and topic modeling. Strong understanding of data classification, sensitivity, PII, and personal data modeling techniques Experience in model evaluation and validation techniques, including cross-validation, hyperparameter tuning, and performance metrics selection. Proficiency in version control systems like Git for tracking and managing code changes. Strong communication skills to convey complex findings and insights to both technical and non-technical stakeholders. Ability to work collaboratively in cross-functional teams. Excellent problem-solving skills to identify business challenges and devise data-driven solutions. Nice To Have Experience in designing data pipelines and products for real-world applications Experience with modern/emerging scalable computing platforms and languages (e.g. Spark) Familiarity with big data technologies like Hadoop, Spark, and distributed computing frameworks for handling large datasets. Our Fantastic Benefits We offer company-wide bonuses based on monthly sales targets, employee referral bonuses, adoption assistance, tuition reimbursement, certification reimbursement, certification completion bonuses, and a relaxed dress code - all in a modern, high-tech, and fun work environment. For more details about our benefits in each office location, please visit www.knowbe4.com/careers/benefits. Note: An applicant assessment and background check may be part of your hiring procedure. Individuals seeking employment at KnowBe4 are considered without prejudice to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation or any other characteristic protected under applicable federal, state, or local law. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please visit www.knowbe4.com/careers/request-accommodation. No recruitment agencies, please.

Job Summary – As an Artificial Intelligence Engineer, you will play a crucial role in designing, developing, and deploying AI systems. Your work will involve translating complex data into AI-driven solutions that can operate autonomously in real-time environments. You'll be responsible for writing code, deploying models to production, and continuously monitoring and updating them as needed. Years of experience needed – 8+ years of experience Technical Skills: ∙ Algorithm Development: Design and implement algorithms, neural networks, and other machine learning techniques to simulate human intelligence process ∙ Model Creation: Develop and validate algorithms, neural networks, and other machine learning models. ∙ Generative AI: Specialize in generative AI, which involves creating AI systems that autonomously generate content such as text, images, and music. ∙ Machine Learning: Leverage your expertise in machine learning to train models on large datasets and optimize them for creative content generation. ∙ Natural Language Processing (NLP): Apply NLP techniques for text generation projects, including text parsing, sentiment analysis, and the use of transformer models like GPT. ∙ Data Management : Handle data pre-processing, augmentation, and synthetic data generation. Hard Skills: ∙ Advanced Programming: Proficiency in programming languages such as Python, along with AI-centric libraries like TensorFlow, PyTorch, and Keras. ∙ Generative Models: Expertise in generative models, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). ∙ NLP: Familiarity with NLP techniques for text generation. ∙ Data Management: Knowledge of data pre-processing, augmentation, and synthetic data generation. Hard Skills: ∙ Creativity: Ability to think creatively and solve complex, creative challenges using AI. ∙ Collaboration: Work effectively with researchers, engineers, and other team members. ∙ Continuous Learning : Stay updated with evolving AI technologies and applications. Certifications Needed: ∙Bachelor’s or master’s degree in computer science, Artificial Intelligence, or related fields. ∙Proven experience in machine learning, generative AI,

About the job Position : AI & Machine Learning Trainer Location : Hyderabad, Telangana Duration : 40 working days Compensation : ₹40,000–₹60,000 per month Job description : ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications. Skills Required : Foundational ML : Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems. Deep Learning : ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT). Data Preprocessing : Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering. Generative AI : Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS. Web & Cloud Deployment : Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment. Mathematics : Calculus, vector algebra, probability. Prompt Engineering : Zero-shot, few-shot, prompt tuning, and designing effective prompts. Case Studies : Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset). Qualifications : Education : Bachelor’s/Master’s in Computer Science, AI, ML, or related fields. Experience : 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in: Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch. Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA). Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure). Tools like Hugging Face, FAISS, LangChain, and Streamlit. Teaching Skills : Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students. Certifications : Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus. Logistics : Local Candidates (Hyderabad) : College bus transportation and lunch provided at the college hostel. Non-Local Candidates : Accommodation and food provided at the college hostel.

About the job Birlasoft, a powerhouse where domain expertise, enterprise solutions, and digital technologies converge to redefine business outcomes. We take pride in our consultative and design thinking approach, driving societal progress by enabling our customers to run businesses with unmatched efficiency and innovation. As part of the multibillion-dollar CK Birla Group, Birlasoft, boasting a team of 12,500+ professionals, is committed to carrying forward the Group's illustrious 162-year legacy. At our core, we prioritize Diversity, Equity, and Inclusion (DEI) initiatives, along with Corporate Sustainable Responsibility (CSR) activities, ensuring our commitment to building not just businesses but inclusive and sustainable communities. Join us in shaping a future where technology aligns seamlessly with purpose. Gen AI LLM Data science · Must have 6+ years of experience working in Data science, Machine learning and especially NLP technologies. · Exposure to various LLM technologies and solid understanding of Transformer Encoder Networks. · Able to apply deep learning and generative modeling techniques to develop LLM solutions in the field of Artificial Intelligence. · Utilize your extensive knowledge and expertise in machine learning (ML) with a focus on generative models, including but not limited to generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer-based architectures. · Solid understanding of Model development, model serving, training/re-training techniques in a data sparse environment. · Very good understanding of Prompt engineering techniques in developing Instruction based LLMs. · Must be able to design, and implement state-of-the-art generative models for natural language processing (NLP) tasks such as text generation, text completion, language translation, and document summarization. · Work with SAs and collaborate with cross-functional teams to identify business requirements and deliver solutions that meet the customer needs. · Passionate to learn and stay updated with the latest advancements in generative AI and LLM. · Nice to have -contributions to the research community through publications, presentations, and participation in relevant conferences or workshops. · Evaluate and preprocess large-scale datasets, ensuring data quality and integrity, and develop data pipelines for training and evaluation of generative models. · Ability to articulate to business stakeholders on the hallucination effects and various model behavioral analysis techniques followed. · Exposure to developing Guardrails for LLMs both with open source and cloud native models. · Collaborate with software engineers to deploy and optimize generative models in production environments, considering factors such as scalability, efficiency, and real-time performance. · Nice to have- provide guidance to junior data scientists, sharing expertise and knowledge in generative AI and LLM, and contribute to the overall growth and success of the data science team.

Area(s) of responsibility Must have 10+ years of experience working in Data science, Machine learning and especially NLP technologies. Exposure to various LLM technologies and solid understanding of Transformer Encoder Networks. Able to apply deep learning and generative modeling techniques to develop LLM solutions in the field of Artificial Intelligence. Utilize your extensive knowledge and expertise in machine learning (ML) with a focus on generative models, including but not limited to generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer-based architectures. Solid understanding of Model development, model serving, training/re-training techniques in a data sparse environment. Very good understanding of Prompt engineering techniques in developing Instruction based LLMs. Must be able to design, and implement state-of-the-art generative models for natural language processing (NLP) tasks such as text generation, text completion, language translation, and document summarization. Work with SAs and collaborate with cross-functional teams to identify business requirements and deliver solutions that meet the customer needs. Passionate to learn and stay updated with the latest advancements in generative AI and LLM. Nice to have -contributions to the research community through publications, presentations, and participation in relevant conferences or workshops. Evaluate and preprocess large-scale datasets, ensuring data quality and integrity, and develop data pipelines for training and evaluation of generative models. Ability to articulate to business stakeholders on the hallucination effects and various model behavioral analysis techniques followed.

Area(s) of responsibility Must have 10+ years of experience working in Data science, Machine learning and especially NLP technologies. Must have education from Tier 1 college like IIT, NIT, IIM Must have experience with Agentic AI frameworks – LangGraph, LlamaIndex, MCP etc. Expert in using paid (OpenAI on Azure) and open source LLMs Strong understanding of Agents development. Experience with Python programming language in a must. Ability to develop Python code as needed and train the Developers based on business needs. Experience with AWS / Azure ecosystem is a must. Preferable candidate should possess Pharma R&D background Strong understanding of cloud native application development in AWS / Azure. Able to apply deep learning and generative modeling techniques to develop LLM solutions in the field of Artificial Intelligence. Utilize your extensive knowledge and expertise in machine learning (ML) with a focus on generative models, including but not limited to generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer-based architectures. Must be able to design, and implement state-of-the-art generative models for natural language processing (NLP) tasks such as text generation, text completion, language translation, and document summarization. Passionate to learn and stay updated with the latest advancements in generative AI and LLM Exposure to developing Guardrails for LLMs both with open source and cloud native models

Area(s) of responsibility About Us Birlasoft, a global leader at the forefront of Cloud, AI, and Digital technologies, seamlessly blends domain expertise with enterprise solutions. The company’s consultative and design-thinking approach empowers societies worldwide, enhancing the efficiency and productivity of businesses. As part of the multibillion-dollar diversified CKA Birla Group, Birlasoft with its 12,000+ professionals, is committed to continuing the Group’s 170-year heritage of building sustainable communities. Job Description Location: Hyderabad Must have 10+ years of experience working in Data science, Machine learning and especially NLP technologies. Exposure to various LLM technologies and solid understanding of Transformer Encoder Networks. Able to apply deep learning and generative modeling techniques to develop LLM solutions in the field of Artificial Intelligence. Utilize your extensive knowledge and expertise in machine learning (ML) with a focus on generative models, including but not limited to generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer-based architectures. Solid understanding of Model development, model serving, training/re-training techniques in a data sparse environment. Very good understanding of Prompt engineering techniques in developing Instruction based LLMs. Must be able to design, and implement state-of-the-art generative models for natural language processing (NLP) tasks such as text generation, text completion, language translation, and document summarization. Work with SAs and collaborate with cross-functional teams to identify business requirements and deliver solutions that meet the customer needs. Passionate to learn and stay updated with the latest advancements in generative AI and LLM. Nice to have -contributions to the research community through publications, presentations, and participation in relevant conferences or workshops. Evaluate and preprocess large-scale datasets, ensuring data quality and integrity, and develop data pipelines for training and evaluation of generative models. Ability to articulate to business stakeholders on the hallucination effects and various model behavioral analysis techniques followed. Exposure to developing Guardrails for LLMs both with open source and cloud native models. Collaborate with software engineers to deploy and optimize generative models in production environments, considering factors such as scalability, efficiency, and real-time performance. Nice to have- provide guidance to junior data scientists, sharing expertise and knowledge in generative AI and LLM, and contribute to the overall growth and success of the data science team. Experience on Marklogic is good to have in it

Area(s) of responsibility Birlasoft, a global leader at the forefront of Cloud, AI, and Digital technologies, seamlessly blends domain expertise with enterprise solutions. The company’s consultative and design-thinking approach empowers societies worldwide, enhancing the efficiency and productivity of businesses. As part of the multibillion-dollar diversified CKA Birla Group, Birlasoft with its 12,000+ professionals, is committed to continuing the Group’s 170-year heritage of building sustainable communities. As a Senior Automation Architect with GenAI/AI/ML background, you will play a pivotal role in designing, developing, and implementing advanced automation frameworks. You will leverage your expertise in Java, Selenium, Playwright, and Python to create robust, scalable, and efficient automation solutions. Your deep understanding of Shift left, no-code/less-code frameworks, and design patterns will be crucial in driving our automation strategy forward. Design and develop automation frameworks for Shift left, no-code/less-code environments. Lead the automation architecture design and implementation using Java, Selenium, and Python. Ensure hands-on involvement in coding and scripting to develop and maintain automation scripts. Collaborate with cross-functional teams to integrate automation solutions into the CI/CD pipeline. Apply design patterns (Factory, Abstract Factory, Command, Builder, Singleton) to create scalable and maintainable automation frameworks. Good understanding on Design principles Provide technical leadership and mentorship to junior automation engineers. Conduct code reviews and ensure adherence to best practices and coding standards. Stay updated with the latest industry trends and advancements in automation technologies. Interface with Business/Engineering and help convert requirements into implementation architectures. Experience designing and implementing generative models and architectures, including RAG, fine-tuning, etc. Programming skills in Python and proficiency with ML frameworks like TensorFlow or PyTorch. Preferred experience with AWS/Azure and its Generative Al capabilities, including containerization technologies; Docker/ Kubernetes Understanding of generative models, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models (e.g., GPT, BERT for text). Qualifications Bachelor’s or master’s degree in computer science, Engineering, or a related field. Proven experience as an Automation Architect or similar role. Strong proficiency in Java and Python programming languages. Extensive experience with Selenium and Playwright for automation testing. Hands-on experience in developing automation frameworks for Shift left and no-code/less-code environments. In-depth knowledge of design patterns (Factory, Abstract Factory, Command, Builder, Singleton) and design principles. Preferred Qualifications Experience with CI/CD tools such as Jenkins, GitLab, or similar. Knowledge of cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Familiarity with Accessibility testing, Test Data management tools or process to handle any one ERP application among SAP, Guidewire, Salesforce, Microsoft 365, Oracle ERP (Nice to have).

Job Description: Overview: An expert in their field, applying broad business knowledge and strategic insight surrounding emerging trends and technologies to solve complex problems and drive organizational results. Leads critical, high-impact projects and designs/implements innovative business strategies. Works with minimal oversight, frequently consulting senior leadership and influencing executive decisions. Serves as a mentor and assists others with challenging issues. Performs very complex data science work, creates new ways of analyzing data, builds very complex business models, and makes recommendations that impact an entire business unit or very large complex sector. Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following: Data Extraction and Preparation: Collect data from various structured and unstructured sources (datalakes, databases, data warehouses, on cloud, internal, external) and ensure its quality for analysis through cleaning and preprocessing. Designs, builds, and analyzes large (e.g. 100’s of Terabytes or higher as technology advances) and complex data sets while thinking strategically about data use and data design. Tools can include snowflake and databricks. Coding Solutions, Algorithms and Feature Engineering: Create relevant features and conduct exploratory data analysis. Codes solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining, business process and/or system implementations, high level proof of concept and trials, visualization, deployment to production, post deployment ML ops monitoring/diagnosis/resolutions. Coding proficiency required in at least one data science language (Python, R, Scala, etc.), as well as expertise with modern ML packages and libraries (Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools). Model Development, Deployment and Optimization: Build, evaluate, and optimize machine learning models through hyperparameter tuning. Implement models into production, continuously monitor their performance, and ensure they remain explainable and reliable to minimize model decay. Ability to develop custom Machine Learning (ML). Highly proficient in the full AI workflow such as (1) data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining and (2) Uses concepts like mlflow to log metrics. Well-versed in Interactive Development Environments (IDEs) such as Databricks Workspaces or Visual Studio Code. Proficiency in algorithm categories such as Supervised Learning, Unsupervised Learning, Optimization Algorithms, Deep Learning, AI-Computer Vision, Natural Language Processing, Deep Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs. Visualization and Collaboration: Create visualizations and reports for stakeholders while working closely with cross-functional teams to align efforts with business objectives. Can utilize advanced coding methods to produce visualizations (e.g. ggplot, D3.js, etc.). Generative AI: Develop and implement generative AI models, focusing on creating new content or augmenting existing data. Generative Models-Understanding of GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Fine-Tuning-Techniques for adapting pre-trained models to specific tasks using smaller, task-specific datasets. Agentics-Understanding of agentic architecture, concepts and optimization of solutions. Prompt Engineering-Crafting effective prompts to guide generative models in producing desired outputs. Retrieval-Augmented Generation (RAG)-Combining generative models with retrieval systems to enhance performance and relevance. Text Generation-Proficiency in using models like GPT-3/4 for generating human-like text. Image Generation-Familiarity with tools like DALL-E and Stable Diffusion for creating images from text descriptions. Key Skills: Python, R, Scala, Generative AL, Credit, Modele development, Fraud, tiral analysis, Machine Learning (ML), Snowflake, databricks, Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, AutoML Weekly Hours: 40 Time Type: Regular Location: Bangalore, Karnataka, India It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.

Company Description Maharshi Industries Pvt. Ltd. is a leading authority in Robotics, Special Purpose Machinery (SPM), Embedded Systems, Artificial Intelligence, Virtual reality, and Engineering Design. Their advanced Robotics, AI, and VR solutions are tailored for Defense, Oil & Gas, Railways, Nuclear, and Public Safety sectors, aiming to boost operational efficiency, safety, and resilience. Role Description This is a full-time on-site role for an Artificial Intelligence-Computer Vision Engineer at Maharshi Industries Pvt. Ltd. located in Ahmedabad. The engineer will be responsible for tasks such as pattern recognition, neural networks, software development, and natural language processing as part of their day-to-day responsibilities. We are looking for a Computer Vision-focused AI/ML Engineer who can build robust, real-time models using image/video data. You will work on critical safety, defense, and industrial inspection projects, including: Human detection & identification Behavior recognition (sleeping, loitering, missing person, PPE compliance) Quality Control (QC) anomaly detection – cracks, surface defects, packaging issues Bird detection for aviation safety (runway & airspace) HSSE Compliance Monitoring for Oil & Gas, Railways, and Industrial setups Your work will directly contribute to saving lives, protecting critical infrastructure, and supporting national security missions. Key Responsibilities Develop, train, and deploy deep learning models for object detection, classification, and anomaly detection using CV data Handle datasets including thermal, IR, RGB video , and still images from surveillance or industrial cameras Optimize models for real-time inference on edge devices (Jetson Nano/Xavier, OpenVINO, etc.) Build pipelines for automatic defect and behavior detection in industrial and outdoor environments Collaborate with hardware, VR, and embedded teams for deployment and testing in real-world settings Continuously fine-tune models using on-field data and adversarial conditions. Must-Have Skills Strong experience in AI/ML model development using PyTorch / TensorFlow / Keras Deep understanding of Computer Vision techniques : ▫ Object detection (YOLO, Faster R-CNN, SSD) ▫ Instance segmentation (Mask R-CNN, Detectron2) ▫ Anomaly detection / QC using autoencoders or custom CNNs Hands-on with OpenCV , image preprocessing , and video analytics Familiarity with edge computing platforms (NVIDIA Jetson series, Coral, etc.) Working knowledge of model deployment frameworks (ONNX, TensorRT, Flask APIs) Experience with datasets like COCO, ImageNet , and custom data labeling Skills (Preferred) Bird or animal detection models Human pose estimation or behavior analysis (e.g., OpenPose, MediaPipe, LSTM-based tracking) Background in industrial inspection , aviation , or defense-related AI systems Basic knowledge of Docker , CI/CD , or Linux-based deployments Why Join Us? Work on prestigious projects for Indian Armed Forces, Airports, Oil & Gas PSUs, and DRDO labs Apply your skills in mission-critical real-world AI systems Join a team where innovation meets impact —your code could help save lives and protect national assets