LivePerson (NASDAQ: LPSN) is the global leader in enterprise conversations. Hundreds of the world’s leading brands — including HSBC, Chipotle, and Virgin Media — use our award-winning Conversational Cloud platform to connect with millions of consumers. We power nearly a billion conversational interactions every month, providing a uniquely rich data set and safety tools to unlock the power of Conversational AI for better customer experiences. At LivePerson, we foster an inclusive workplace culture that encourages meaningful connection, collaboration, and innovation. Everyone is invited to ask questions, actively seek new ways to achieve success, and reach their full potential. We are continually looking for ways to improve our products and make things better. This means spotting opportunities, solving ambiguities, and seeking effective solutions to the problems our customers care about. Overview We are looking for an experienced Data Engineer to provide data engineering expertise and support to various analytical products of LivePerson, and assist in migrating our existing data processing ecosystem from Hadoop (Spark, MapReduce, Java, and Scala) to Databricks on GCP. The goal is to leverage Databricks’ scalability, performance, and ease of use to enhance our current workflows. You Will Assessment and Planning: Review the existing Hadoop infrastructure, including Spark and MapReduce jobs. Analyze Java and Scala codebases for compatibility with Databricks. Identify dependencies, libraries, and configurations that may require modification. Propose a migration plan with clear timelines and milestones. Code Migration: Refactor Spark jobs to run efficiently on Databricks. Migrate MapReduce jobs where applicable or rewrite them using Spark DataFrame/Dataset API. Update Java and Scala code to comply with Databricks' runtime environment. Testing and Validation: Develop unit and integration tests to ensure parity between the existing and new systems. Compare performance metrics before and after migration. Implement error handling and logging consistent with best practices in Databricks. Optimization and Performance Tuning: Fine-tune Spark configurations for performance improvements on Databricks. Optimize data ingestion and transformation processes. Deployment and Documentation: Deploy migrated jobs to production in Databricks. Document changes, configurations, and processes thoroughly. Provide knowledge transfer to internal teams if required. Required Skills 6+ years of experience in Data Engineering with focus on building data pipelines, data platforms and ETL (Extract, transform, Load) processes on Hadoop and Databricks. Strong Expertise in Databricks (Spark on Databricks, Delta Lake, etc.) preferably on GCP. Strong expertise in the Hadoop ecosystem (Spark, MapReduce, HDFS) with solid foundations of Spark and its internals. Proficiency in Scala and Java. Strong SQL knowledge. Strong understanding of data engineering and optimization techniques. Solid understanding on Data governance, Data modeling and enterprise scale data lakehouse platform Experience with test frameworks like Great Expectations Minimum Qualifications Bachelor's degree in Computer Science or a related field Certified Databricks Engineer- Preferred You Should Be An Expert In Databricks with spark and its internals (3 years) - MUST Data engineering in Hadoop ecosystem (5 years) - MUST Scala and Java (5 years) - MUST SQL - MUST Benefits Health: Medical, Dental and Vision Time away: vacation and holidays Development: Access to internal professional development resources. Equal opportunity employer Why You’ll Love Working Here As leaders in enterprise customer conversations, we celebrate diversity, empowering our team to forge impactful conversations globally. LivePerson is a place where uniqueness is embraced, growth is constant, and everyone is empowered to create their own success. And, we're very proud to have earned recognition from Fast Company, Newsweek, and BuiltIn for being a top innovative, beloved, and remote-friendly workplace. Belonging At LivePerson We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law. We are committed to the accessibility needs of applicants and employees. We provide reasonable accommodations to job applicants with physical or mental disabilities. Applicants with a disability who require reasonable accommodation for any part of the application or hiring process should inform their recruiting contact upon initial connection. The talent acquisition team at LivePerson has recently been notified of a phishing scam targeting candidates applying for our open roles. Scammers have been posing as hiring managers and recruiters in an effort to access candidates' personal and financial information. This phishing scam is not isolated to only LivePerson and has been documented in news articles and media outlets. Please note that any communication from our hiring teams at LivePerson regarding a job opportunity will only be made by a LivePerson employee with an @ liveperson.com email address. LivePerson does not ask for personal or financial information as part of our interview process, including but not limited to your social security number, online account passwords, credit card numbers, passport information and other related banking information. If you have any questions and or concerns, please feel free to contact recruiting-lp@liveperson.com Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

Data Analyst - Data Operations Ahmedabad, India Data Management 312862 Job Description About The Role: Grade Level (for internal use): 07 The Role: Data Analyst - Data Operations Location: Ahmedabad Team: People Data What’s in it for you: Join a dynamic Content Team focused on collecting Officers & Directors’ data from company-filed documents and websites, which is then published on our product. Engage in collecting and updating People Data for public and private companies worldwide, following established data collection procedures. Gain insights into various management structures across different companies and countries. Be part of a vibrant team with numerous opportunities for growth and excellence. Key Responsibilities: Perform high-quality data extraction, collection, and analysis using workflow tools, adhering to guidelines and procedures. Provide accurate, relevant, and comprehensive solutions to client requirements. Identify and address data lapses and gaps in coverage. Understand dataset operations, workflows, and maintain strong knowledge of workflow tools. Achieve individual and team targets, delivering outcomes with quality and excellence. Contribute ideas for new collection methods and product enhancements related to the dataset. Manage projects, ensuring timely completion with the desired quality. Troubleshoot issues and provide support to the team. Explore lean and automation options to improve processes. What We’re Looking For: Excellent written and oral communication skills. Proficiency in secondary research sources. Willingness to work in a 24x5 environment with rotational shifts. Certification or experience in MS Office (Excel, Word, PowerPoint). Strong quantitative, analytical, and interpretive skills. Ability to conduct efficient thematic online research. Knowledge of SQL, Excel, and PowerBI is preferred. Ability to multitask and work in a team environment, adhering to flexible schedules to meet deadlines. Initiative and creativity in solving complex problems. Basic Qualifications: Strong communication skills. Excellent research and analytical abilities. Flexibility and multitasking capabilities. Ability to understand and respond to the 'Voice of the Customer.' Effective problem-solving and interpersonal skills. Willingness to work in rotational shifts as per business requirements. What’s In It For You? Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. - Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf - 20 - Professional (EEO-2 Job Categories-United States of America), DTMGOP203 - Entry Professional (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 312862 Posted On: 2025-06-05 Location: Ahmedabad, Gujarat, India

Data Analyst Gurgaon, India; Ahmedabad, India; Hyderabad, India Data Management 315425 Job Description About The Role: Grade Level (for internal use): 07 The Team: The Transactions team’s mission is to produce the most actionable, transparent, trusted, and comprehensive data & insights in the marketplace for M&A, Public Offerings, Private Placements, Equity Buybacks, and Bankruptcy. We are currently looking for a highly skilled data researcher with exceptional detail orientation and analytical skills to join us in our mission. The Impact: This role will be leading teams that work on collection of Transactions data that is used by our clients. It involves working with team-members, other managers within Transactions and teams within domain/cluster/content organization to drive various projects and initiatives with goal of delivering best in class, differentiated content to meet and exceed client expectations. What’s in it for you: This is an opportunity to manage leadership and/or individual contributors and contribute towards achieving the business results. Accountability would be towards understanding and owning the business objectives; be a role model for people and peer group; communicate with passion and enthusiasm, embrace change as a way of working; and lead by example when communicating new initiatives. Responsibilities: Manage multiple teams working on collection/value added tasks within Transaction teams. Leads teams across assigned business/region for workflow systems with a focus on managing process, productivity and functionality improvements. Effective co-ordination and constructive relationship within internal, intra-cluster and other dataset teams across offices. May interact with internal and external clients as necessary and occasionally works on new projects and data enhancement initiatives as assigned. Owns the performance measurement processes, talent development, team engagement and VIBE for his/her teams. Generates and timely shares various status reports/updates to stakeholders. Manages/supports multiple operational or project/focused teams across offices in planning and implementing process and operational changes across different teams. Proven ambassador of LEAN culture and promoter of various concepts of LEAN, Robotics, AI etc. Identifies individual strengths to appropriately delegate work amongst team. Guide and coach leads & teams for future growth. What we’re looking for: Functional and Business Knowledge: Preferred to have a sound understanding of Transaction dataset processes like M&A, Public Offerings, Private Placements, and understanding of various internal processes. Good oral and written communication skills. Possesses strong analytical skills and out of box thinking. Sound knowledge of SQL & MS Office. Basic Qualifications: Fresher - Graduate (BBA/B.Com/BMS) OR Post-Graduate / MBA in Finance as major Specialization with good academic track record (passing year 2024 or 2025 only) Excellent communication skills, both written and oral Knowledge of corporate finance / accountancy i.e., financial statements and annual reports Well versed with secondary research sources Willing to work in 24*5 environment on rotational shifts (including night shifts) Certification or knowledge/experience in MS-office (Excel, Word, PowerPoint) Strong quantitative, analytical, and interpretive skills Ability to conduct efficient thematic online research What’s In It For You? Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. - Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf - 20 - Professional (EEO-2 Job Categories-United States of America), DTMGOP203 - Entry Professional (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 315425 Posted On: 2025-06-05 Location: Gurgaon, Haryana, India

Description Company Overview: When it comes to IT solution providers, there are a lot of choices. But when it comes to providers with innovative and differentiating end-to-end service offerings, there’s really only one: Zones – First Choice for IT.TM Zones is a Global Solution Provider of end-to-end IT solutions with an unmatched supply chain. Positioned to be the IT partner you need, Zones, a Minority Business Enterprise (MBE) in business for over 35 years, specializes in Digital Workplace, Cloud & Data Center, Networking, Security, and Managed/Professional/Staffing services. Operating in more than 120 countries, leveraging a robust portfolio, and utilizing the highest certification levels from key partners, including Microsoft, Apple, Cisco, Lenovo, Adobe, and more, Zones has mastered the science of building digital infrastructures that change the way business does business ensuring whatever they need, they can Consider IT Done. Follow Zones, LLC on Twitter @Zones, and LinkedIn and Facebook. Position Overview Looking for strong System Engineer who would be responsible for supporting and maintaining business intelligence dashboards and reports. This role focuses on ensuring optimal performance and usability of visualizations created in Power BI and Oracle Analytics Cloud. Need someone with strong skillset to ensure production (Operation/support) related activities are delivered as per SLA. Work activities involve bug fixes, break fix, changes, co-ordinate with the development team in case of any issues, work on enhancements. What you’ll do as the System Engineer - Oracle Analytics Cloud & Power BI: The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Hands-on experience with Power BI (report building, dashboard design, DAX, Power Query). Strong knowledge of Oracle Analytics Cloud, including dashboard configuration and data integration. Familiarity with SQL and data querying to support data extraction and troubleshooting. Power BI developer having Experience in Creating reports & dashboards using DAX. Excellent in using DAX functions, and M query language. Good understanding of Power BI premium services Excellent knowledge of Dataset Refresh using Gateways, configuring, and managing gateways Strong understanding of service features, governance, deployment pipelines, data gateway, schedule refreshes, XMLA end points Experienced in implementing and managing Row Level Security, workspace creation and manage workspace access. Excellent knowledge in Performance optimization and tuning of PBI reports. Weekly and monthly presentation to the business users about the reports and their changes as required. Strong working knowledge of SQL queries Worked on Power BI Visuals including Tree Map, Funnel, Line Chart Knowledge working with Map Reports and Stacked Reports Strong Knowledge on Power Query Lists, Tables and Records Created Scorecards, Bookmarks, ToolTip, conditional formatting, Drill Down Reports, Drill Through Report. What You Will Bring To The Team B.E/B. Tech/M.Tech in Computer Science or related technical degree. Knowledge BI & Oracle cloud. Knowledge on SQL is added advantage. Fast learner and good problem-solving skills Good oral and written communication skills Ability to manage multiple users and systems Zones offers a comprehensive Benefits package. While we’re committed to providing top-tier solutions, we’re just as committed to supporting our own teams. We offer a competitive compensation package where our team members are rewarded based on their performance and recognized for the value, they bring into our business. Our team members enjoy a variety of comprehensive benefits, including Medical Insurance Coverage, Group Term Life and Personal Accident Cover to handle the uncertainties of life, flexible leave policy to balance their work life. At Zones, work is more than a job – it's an exciting careers immersed in an inventive, collaborative culture. If you’re interested in working on the cutting edge of IT innovation, sales, engineering, operations, administration, and more, Zones is the place for you! All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status or on the basis of disability. Show more Show less

Description Pipeline Integrity GIS Specialist Job Summary We are seeking a skilled Pipeline Integrity GIS Specialist to support our pipeline integrity projects. The ideal candidate will be responsible for extracting, processing, and validating GIS data while ensuring compliance with industry standards. This role involves working closely with section managers and engineers to convert spatial data into required formats, verify pipeline features, and maintain high data accuracy. Key Responsibilities Extract GIS data from the client’s enterprise geodatabase and convert it into a file geodatabase for further processing. Transform spatial data into various formats as per engineering requirements. Develop and document detailed procedures for data extraction, quality control, and validation. Calibrate pipeline centerlines based on provided documents and update feature locations accordingly. Verify and relocate pipeline features to align with the corrected centerline. Integrate and standardize extracted data from multiple sources into a common dataset. Perform quality checks to ensure data accuracy and adherence to enterprise geodatabase standards. Collaborate with engineers and project teams to validate GIS datasets before transferring data back to the client’s system. Maintain an organized database of pipeline integrity information and support GIS-related project needs. Qualifications Qualifications & Experience: Degree or diploma in Civil Engineering, Pipeline GIS, Geo-Informatics, Remote Sensing, Geology, Geography, or a related field. 0-4 years of experience in GIS, with a minimum of 2 years in pipeline integrity GIS preferred. Strong proficiency in GIS tools and software including ArcGIS Pro, ArcGIS Online, QGIS, SQL, and Geodatabases. Solid understanding of pipeline integrity concepts, including design, construction, inspections, and linear referencing. Familiarity with industry-standard GIS data models such as APDM, UPDM, and PODS. Ability to work with large geospatial datasets and ensure data consistency and accuracy. Strong analytical and problem-solving skills with attention to detail. Good communication and teamwork skills to collaborate with engineers and project teams effectively. This role offers an excellent opportunity to grow in the field of pipeline integrity GIS, contributing to innovative solutions and best practices in geospatial data management. Job Engineering Primary Location India-Karnataka-Bengaluru Other Locations India-Maharashtra-Mumbai Schedule: Full-time Travel: No Req ID: 251178 Job Hire Type Experienced Not Applicable #BMI N/A Show more Show less

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning we would like to talk to you. Function : Data Science and Analysis → Data Science / Machine Learning Desired Skills & Competencies: Strong learning acumen High sense of ownership Ability to work in a fast-paced and deadline-driven environment Loves technology Highly skilled at Data Interpretation Problem solver Good exposure to machine learning concepts and algorithms Must be fluent with any one of Python, R, Java Strong in statistical & machine learning concepts Knowledge of Python Libraries - SciPy, NumPy, Pandas, I Python, Scikit-learn Knowledge of distributed big data processing (PySpark, Jupyter, Linux, AWS) Responsibilities: Hypothesis testing, insights generation, root cause analysis, factor analysis Statistical model (predictive & prescriptive) development using various statistical & machine learning techniques/algorithms Test/train the model, Improve Model accuracy, Monitor model performance Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation, transformation), performing EDA Desired Experience & Education: 3 - 5 years of relevant Machine Learning experience. B. Tech from Tier-1 college / M.S or M. Tech is preferred in Computer Science, Information Technology, or similar degree. Show more Show less

The vertical is basically responsible for providing financial and non-financial information to the clients on companies across the globe. Environment, Social and Corporate Governance team (ESG) provides integrated financial and extra-financial information, which is essential for understanding the long-term performance and risk profile of major corporations. A Content Analyst must research on the documents relating to the company and collect the Environmental and Social data from the sourced documents. They should also handle Queries pertaining to team and provide expert advice on specific content knowledge relating to quality concepts and techniques in order to drive improvement activities within the content collection team and quality & service groups. Their responsibility also includes to deliver on all tasks as per the strategic plans set for the ESG team. Also, must have hands on experience with the database and should be able to handle database queries independently. Essential Responsibilities To be responsible for database administration and sourcing of exchange and contributed data. To be up to date with the latest collection policies and procedures and other significant developments pertaining to different markets which would impact data collection To assist in projects with emphasis on data content. To review the work of the analyst/data provider. Take responsibility for data quality, accuracy, timeliness and completeness within the team. To take on the responsibility of resolving client queries in a timely manner, with very high standards of quality of response and customer satisfaction. Should be able to take right decisions quickly and independently. To coach analysts on data collection policies and procedures. To continuously find ways to improve quality and reduce number of service requests from clients and to help meet Service targets. To continuously suggest improvement ideas on collection tools, internal processes and should suggest permanent fixes as well as on-going actions for preventing client queries. To carry out special projects or specialized tasks related to the ESG dataset as per the strategic plans. To effectively collaborate with all global team and the data provider to provide high quality data to our clients. Cultivate a learning and positive work environment SCOPE & IMPACT Researching on Company website, Filings to understand the reports and to be able to accurate identify the data to be captured. Accountable for the quality of own work, delivered within agreed time-frames and quality standards. Quality of work is reviewed by manager to ensure it is delivered within set parameters of timeliness, accuracy and completeness. Works independently within defined area, taking ownership of problems within own area of knowledge. Makes recommendations for process improvements to immediate manager. Decisions taken are made within guidelines set by others. Required Skills: Expert in Arabic language must be able to understand and update the ESG data as per policy. Communication, Collaboration and Analytical skills. Researching on Company website, Filings to understand the reports and to be able to accurate identify the data to be captured. Should have the Curiosity to learn and know more on the Content. Should have Reading Comprehension Skills to read the paragraphs and dotted lines in the report. High Accountability & Responsibility Should be proficient in using MS-Excel Candidate should be open to work in shifts LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth. Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership , Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions. Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce. You will be part of a collaborative and creative culture where we encourage new ideas and are committed to sustainability across our global business. You will experience the critical role we have in helping to re-engineer the financial ecosystem to support and drive sustainable economic growth. Together, we are aiming to achieve this growth by accelerating the just transition to net zero, enabling growth of the green economy and creating inclusive economic opportunity. LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives. We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject. If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice. Show more Show less

The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data. As a Machine Learning Engineer at Sumo Logic, you will actively contribute in the design and development of innovative ML-powered product capabilities to help our customers make sense of their huge amounts of log data. This involves working through the entire feature lifecycle including ideation, dataset construction, experimental validation, prototyping, production implementation, deployment, and operations. Responsibilities Identifying and validating opportunities for the application of ML or data-driven techniques Assessing requirements and approaches for large-scale data and ML platform components Driving technical delivery through the full feature lifecycle, from idea to production and operations Helping the team design and implement extremely high-volume, fault-tolerant, scalable backend systems that process and manage petabytes of customer data. Collaborating within and beyond the team to identify problems and deliver solutions Work as a member of a team, helping the team respond quickly and effectively to business needs. Requirements B.Tech, M.Tech, or Ph.D. in Computer Science or related discipline 4-6 years of industry experience with a proven track record of ownership and delivery Experience formulating use cases as ML problems and putting ML models into production Solid grounding in core ML concepts and basic statistics Experience with software engineering of production-grade services in cloud environments handling data at large scale Desirable Cloud-based application and infrastructure deployment and management Common ML libraries (eg, scikit-learn, PyTorch) and components (eg, Airflow, MLFlow) Relevant cloud provider services (eg, AWS Sagemaker) LLM core concepts, libraries, and application design patterns Experience in multi-threaded programming and distributed systems Agile software development experience (test-driven development, iterative and incremental development) is a plus. About Us Sumo Logic, Inc., empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its SaaS analytics platform. The Sumo Logic Continuous Intelligence Platform™ helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com. Show more Show less

Description Pipeline Integrity GIS Specialist Job Summary We are seeking a skilled Pipeline Integrity GIS Specialist to support our pipeline integrity projects. The ideal candidate will be responsible for extracting, processing, and validating GIS data while ensuring compliance with industry standards. This role involves working closely with section managers and engineers to convert spatial data into required formats, verify pipeline features, and maintain high data accuracy. Key Responsibilities Extract GIS data from the client’s enterprise geodatabase and convert it into a file geodatabase for further processing. Transform spatial data into various formats as per engineering requirements. Develop and document detailed procedures for data extraction, quality control, and validation. Calibrate pipeline centerlines based on provided documents and update feature locations accordingly. Verify and relocate pipeline features to align with the corrected centerline. Integrate and standardize extracted data from multiple sources into a common dataset. Perform quality checks to ensure data accuracy and adherence to enterprise geodatabase standards. Collaborate with engineers and project teams to validate GIS datasets before transferring data back to the client’s system. Maintain an organized database of pipeline integrity information and support GIS-related project needs. Qualifications Qualifications & Experience: Degree or diploma in Civil Engineering, Pipeline GIS, Geo-Informatics, Remote Sensing, Geology, Geography, or a related field. 0-4 years of experience in GIS, with a minimum of 2 years in pipeline integrity GIS preferred. Strong proficiency in GIS tools and software including ArcGIS Pro, ArcGIS Online, QGIS, SQL, and Geodatabases. Solid understanding of pipeline integrity concepts, including design, construction, inspections, and linear referencing. Familiarity with industry-standard GIS data models such as APDM, UPDM, and PODS. Ability to work with large geospatial datasets and ensure data consistency and accuracy. Strong analytical and problem-solving skills with attention to detail. Good communication and teamwork skills to collaborate with engineers and project teams effectively. This role offers an excellent opportunity to grow in the field of pipeline integrity GIS, contributing to innovative solutions and best practices in geospatial data management. Job Engineering Primary Location India-Karnataka-Bengaluru Other Locations India-Maharashtra-Mumbai Schedule: Full-time Travel: No Req ID: 251178 Job Hire Type Experienced Not Applicable #BMI N/A Show more Show less

Join us as a Data Engineer We’ll look to you to drive the build of effortless, digital-first customer experiences as you simplify our bank while keeping our data safe and secure Day-to-day, you’ll develop innovative, data-driven solutions through data pipeline modelling and ETL design, inspiring to be commercially successful through insights This is your opportunity to explore your leadership potential while bringing a competitive edge to your career profile by solving problems and creating smarter solutions We're offering this role at director level What you’ll do In this role, you’ll develop and share knowledge of business data structures and metrics, advocating for changes when needed for product development. You’ll also educate and embed new data techniques into the business through role modelling, training, and experiment design oversight. We’ll look to you to drive DevOps adoption into the delivery of data engineering, proactively performing root cause analysis while resolving issues. You’ll also deliver a clear understanding of data platform cost levers to meet department cost savings and income targets. You’ll Also Be Responsible For Driving customer value by understanding complex business problems and requirements to correctly apply the most appropriate and reusable tools to gather and build data solutions Actively participating in the data engineering community to deliver opportunities to support our bank’s strategic direction Driving data engineering strategies to build complex, scalable data architecture and a customer feature rich dataset Driving the advanced automation of data engineering pipelines through the removal of manual stages Working alongside colleagues, scrums and project teams while liaising with technology and engineering teams to build business stakeholder engagement and to develop data solutions The skills you’ll need We’re looking for someone with strong communication skills and the ability to proactively engage and manage a wide range of stakeholders. You’ll have extensive experience working in a governed, and regulatory environment. You’ll Also Need Experience of extracting value and features from large scale data Advanced experience of designing efficient data models that meet organisational needs. Familiarity with various modelling techniques like star and snowflake schemas can significantly enhance data retrieval and reporting performance Proven proficiency in relational databases (e.g., MySQL, PostgreSQL) as well as NoSQL databases (e.g., MongoDB, Cassandra) is critical for storing and managing various types of data. An understanding of modern code development practices Show more Show less

Join us as a Data Engineer We’ll look to you to drive the build of effortless, digital-first customer experiences as you simplify our bank while keeping our data safe and secure Day-to-day, you’ll develop innovative, data-driven solutions through data pipeline modelling and ETL design, inspiring to be commercially successful through insights This is your opportunity to explore your leadership potential while bringing a competitive edge to your career profile by solving problems and creating smarter solutions We're offering this role at director level What you’ll do In this role, you’ll develop and share knowledge of business data structures and metrics, advocating for changes when needed for product development. You’ll also educate and embed new data techniques into the business through role modelling, training, and experiment design oversight. We’ll look to you to drive DevOps adoption into the delivery of data engineering, proactively performing root cause analysis while resolving issues. You’ll also deliver a clear understanding of data platform cost levers to meet department cost savings and income targets. You’ll Also Be Responsible For Driving customer value by understanding complex business problems and requirements to correctly apply the most appropriate and reusable tools to gather and build data solutions Actively participating in the data engineering community to deliver opportunities to support our bank’s strategic direction Driving data engineering strategies to build complex, scalable data architecture and a customer feature rich dataset Driving the advanced automation of data engineering pipelines through the removal of manual stages Working alongside colleagues, scrums and project teams while liaising with technology and engineering teams to build business stakeholder engagement and to develop data solutions The skills you’ll need We’re looking for someone with strong communication skills and the ability to proactively engage and manage a wide range of stakeholders. You’ll have extensive experience working in a governed, and regulatory environment. You’ll Also Need Experience of extracting value and features from large scale data Advanced experience of designing efficient data models that meet organisational needs. Familiarity with various modelling techniques like star and snowflake schemas can significantly enhance data retrieval and reporting performance Proven proficiency in relational databases (e.g., MySQL, PostgreSQL) as well as NoSQL databases (e.g., MongoDB, Cassandra) is critical for storing and managing various types of data. An understanding of modern code development practices Show more Show less