1204 Probability Jobs - Page 37

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

Position Overview Job Titl e: Credit Officer, AVP Location: Mumbai, India Role Description Risk division has a fundamental responsibility to protect the Bank. With group-wide responsibility for the management and control of credit, market, operational and reputational risks, we have a unique vantage point which allows us a holistic view of our businesses and our clients. Nearly 4,000 employees work together in our division to achieve our ambition to be an industry-leading risk management organisation. In an increasingly complex environment, risk management is fast-becoming the most sought after place to build a career within the banking world. Risk at Deutsche Bank is relied upon to help shape the strategy of the organisation and the wider industry agenda. The Global Credit Analytics Function (GCAF) is entrusted with the work of assigning and surveillance of Probability of Default Rating to Corporate and Institutional counterparties of the Bank. As part of Risk’s transformation journey, GCAF is bringing Credit documentation to its purview and requires strong analysts to handle the same. What We’ll Offer You As part of our flexible scheme, here are just some of the benefits that you’ll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your Key Responsibilities Undertake accurate and timely credit analysis of counterparties (including Corporates and FIs) by identifying business and financial risk based on understanding of business model, financial statement analysis, preparing cash flow model/ forecast and peer analysis. Write Rating reports and credit reviews/analysis for recommendation to Senior members for approval. Active participation in Live trades with onshore credit officers (KCP) by understanding the trade dynamics, providing your recommendation and completing the credit write-ups (Addendum) for the same. On-going monitoring & surveillance of assigned international portfolios, including rating changes, market/industry developments, news events, etc and assessing the impact on credit worthiness of the counterparty, keeping DB’s exposure in mind. Understand the various banking products (including Trade Finance and Derivatives) and credit documentation for the same. Support the KCP with appropriate checks and its inclusion in the credit reviews. Monitoring of limits/exposure: Updating Limit amendments and credit relevant data updates in the credit system. Exposure monitoring and timely clearance of Excess tickets. Timely monitoring of covenants and regular discussion with KCPs. Manage own credit portfolio and assist senior decision makers to make informed decisions based on your recommendations Interface directly across with the Credit officers (KCP) and other stakeholders (business side, Exposure managements, and various ops teams) to ensure complete understanding of DB’s exposure and timely completion of the credit reviews. Participate in ad-hoc projects related to portfolio exercises (industry/regional exercise), regulatory developments, sector notes, audit exercises and support onshore KCPs for various business strategies. Ensure compliance with relevant and applicable local and global regulatory and policy requirements Your Skills And Experience Relevant professional qualifications are MSc / MA / MBA / CA / CFA, etc. Relevant work experience in credit underwriting Strong analytical skills, knowledge of financial markets and economic/industry trends Strong accounting background, knowledge of financial ratios, financial statement analysis, cash flow projections or project finance How We’ll Support You Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About Us And Our Teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment. Show more Show less

Summary Under limited supervision designs, develops and maintains test procedures, tester hardware and software for electronic circuit board production. ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties may be assigned. Leadership And Management Responsibilities Recruitment and Retention: Recruit and interview Process Technicians. Communicate criteria to recruiters for Process Technician position candidates. Coach technicians in the interviewing/hiring process. Monitor team member turnover; identify key factors that can be improved; make improvements. Employee and Team Development: Identify individual and team strengths and development needs on an ongoing basis. Create and/or validate training curriculum in area of responsibility. Coach and mentor Process Technicians to deliver excellence to every internal and external customer. Performance Management: Establish clear measurable goals and objectives by which to determine individual and team results (i.e. operational metrics, results against project timelines, training documentation, attendance records, knowledge of operational roles and responsibilities, personal development goals). Solicit ongoing feedback from Assistant Test Engineering Manager, Workcell Manager (WCM), Business Unit Manager (BUM), peers and team member on team member’s contribution to the Workcell team. Provide ongoing coaching and counseling to team member based on feedback. Express pride in staff and encourage them to feel good about their accomplishments. Perform team member evaluations professionally and on time. Drive individuals and the team to continuously improve in key operational metrics and the achievement of the organizational goals. Coordinate activities of large teams and keep them focused in times of crises. Ensure recognition and rewards are managed fairly and consistently in area of responsibility. Communication: Provide communication forum for the exchange of ideas and information with the department. Organize verbal and written ideas clearly and use an appropriate business style. Ask questions; encourage input from team members. Assess communication style of individual team members and adapt own communication style accordingly. Technical Management Responsibilities Review circuit board designs for testability requirements. Support manufacturing with failure analysis, tester debugging, reduction of intermittent failures and downtime of test equipment. Prepare recommendations for testing and documentation of procedures to be used from the product design phase through to initial production. Generate reports and analysis of test data, prepares documentation and recommendations. Review test equipment designs, data and RMA issues with customers regularly. Design, and direct engineering and technical personnel in fabrication of testing and test control apparatus and equipment. Direct and coordinate engineering activities concerned with development, procurement, installation, and calibration of instruments, equipment, and control devices required to test, record, and reduce test data. Determine conditions under which tests are to be conducted and sequences and phases of test operations. Direct and exercise control over operational, functional, and performance phases of tests. Perform moderately complex assignments of the engineering test function for standard and/or custom devices. Analyze and interpret test data and prepares technical reports for use by test engineering and management personnel. Develop or use computer software and hardware to conduct tests on machinery and equipment. Perform semi-routine technique development and maintenance, subject to established Jabil standards, including ISO and QS development standards. Provide training in new procedures to production testing staff. Adhere to all safety and health rules and regulations associated with this position and as directed by supervisor. Comply and follow all procedures within the company security policy. Minimum Requirements Bachelors of Science in Electronics or Electrical Engineering from four-year college or university; and three to five years experience Language Skills Ability to read, analyze, and interpret general business periodicals, professional journals, technical procedures, or governmental regulations. Ability to write reports, business correspondence, and procedure manuals. Ability to effectively present information and respond to questions from groups of managers, clients, customers, and the general public. Mathematical Skills Ability to work with mathematical concepts such as probability and statistical inference, and fundamentals of plane and solid geometry and trigonometry. Ability to apply concepts such as fractions, percentages, ratios, and proportions to practical situations. REASONING ABILITY Ability to define problems, collect data, establish facts, and draw valid conclusions. Ability to interpret an extensive variety of technical instructions in mathematical or diagram form and deal with several abstract and concrete variables. PHYSICAL DEMANDS The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The employee is frequently required to walk, and to lift and carry PC’s and test equipment weighing up to 50 lbs. Specific vision abilities required by this job include close vision and use of computer monitor screens a great deal of time. WORK ENVIRONMENT The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Individual’s primary workstation is located in the office area, with some time spent each day on the manufacturing floor. The noise level in this environment ranges from low to moderate. , BE AWARE OF FRAUD: When applying for a job at Jabil you will be contacted via correspondence through our official job portal with a jabil.com e-mail address; direct phone call from a member of the Jabil team; or direct e-mail with a jabil.com e-mail address. Jabil does not request payments for interviews or at any other point during the hiring process. Jabil will not ask for your personal identifying information such as a social security number, birth certificate, financial institution, driver’s license number or passport information over the phone or via e-mail. If you believe you are a victim of identity theft, contact your local police department. Any scam job listings should be reported to whatever website it was posted in. Show more Show less

Job Description What We Do At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets. Engineering, which is comprised of core and business-aligned teams, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here. Asset Management Goldman Sachs Asset Management delivers innovative investment solutions through a global, multi-product platform that offers clients the advantages that come with working with a large firm, while maintaining the benefits of a boutique. We are a top 10 global asset manager with a leadership position across asset classes and key market segments. Our success is driven by a global team of talented professionals who collaborate to deliver innovative client solutions. Quantitative Strategists Quantitative strategists work in close collaboration with bankers, traders, and portfolio managers on complex financial and technical challenges. We work on alpha generating strategies; discuss portfolio allocation problems; and build models for prediction, pricing, trading automation, data analysis and more. The strats platform is designed for people to express themselves by providing creative solutions to business problems. Strats own analytics, models for pricing, return and risk, as well as portfolio management platform. Responsibilities As a quantitative strategist your responsibilities will include Working with revenue-generating businesses to solve a broad range of problems, including quantitative strategy development, quantitative modelling, portfolio construction, portfolio optimization, infrastructure development and implementation, financial product and markets analytics Develop quantitative analytics and signals using advanced statistical, quantitative, or econometric techniques to improve portfolio construction process and implement fund management models to track longer term portfolio performance Develop sustainable production systems, which can evolve and adapt to changes in our fast-paced, global business environment Provide quantitative analytics to optimize investment structure, pricing, returns and capital sourcing Partner globally across multiple divisions and engineering teams to create quantitative modeling-based solutions Prioritize across competing problems, communicate with key stakeholders Basic Qualifications Bachelor's / master's degree in a quantitative discipline with quantitative analytics/ research, financial modeling experience Strong understanding of mathematical concepts including probability and statistics, time series analysis, regression analysis, forecasting, optimization, machine learning, regression analysis, and other numerical techniques Strong fundamentals in design and analysis of algorithms, data structures Ability to implement coding solutions to quantitative problems, experience in developing finance and statistics-based applications and proficiency in at least one programming language such as Slang, Python, C, C++ Strong written, oral communication skills and ability to work in a team environment Ability to multi-task and prioritize work effectively Passion and self-motivation to deliver technology solutions in a dynamic business environment goldmansachs.com/careers Goldman Sachs Engineering Culture At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html © The Goldman Sachs Group, Inc., 2025. All rights reserved. Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity Show more Show less

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. Are you interested in using the power of automation technology to transform the way IT services are delivered? The Tech@Lilly Enterprise Automation organization is seeking a technical delivery lead to join the Tech Enablement team. The Tech Enablement team addresses enterprise IT business needs by supporting the necessary transformations in people, processes, and culture through innovation that accelerates the development of automation solutions. If you are passionate about using automation to bring significant efficiency gains, enhanced employee experiences, and cost savings to the enterprise, come join our team! What You’ll Be Doing In this position, you will manage automation projects that reimagine tech delivery, to improve IT services across the company. Overseeing the technical delivery of these assets, you'll ensure these projects provide value, functionality, and business results, and drive automation adoption among various IT teams. How You’ll Succeed Continually assessing and managing the health and customer experience, entailing working with vendors and Tech@Lilly teams to remove barriers to success, leading the implementation of automation capabilities, and driving adoption of all the above. This will require a love of technology, high learning agility, technical breadth, ability to work well with the engineering team as well as business stakeholders, and influence others. Driving demand, implementation and/or improvement of automation for defined key capabilities, working alongside team members across platforms for best-in-class delivery. Broker across Tech@Lilly teams to leverage self-service tools and reusable components. Communicate across geographies and leadership levels to modernize automation practices and technology across Tech@Lilly with low code/no code and out-of-the-box solutions that can be leveraged to quickly adopt efficiencies. Propose and prototype innovative ways of approaching solutions to align to the larger Enterprise Automation strategy, developing inclusive relationships with Tech@Lilly partners across the enterprise to promote the importance of automation and influence colleagues and leadership in the adoption of technology. Provide technical delivery oversight, ensuring scope management and creation of a pipeline to deliver value to the customer early in the release cycle utilizing Agile methodology and automated testing strategies. Anticipate, measure, and track demand of automation capabilities through valuation in the form of metrics and KPI dashboards/visualizations, providing critical visibility to the team’s project delivery as well as business specific KPIs. Utilize internal and external professional relationships to improve the probability of successful automation strategy execution. Must Have What You Should Bring: Experience as a delivery leader, influencing strategic direction and driving implementation of multiple technical projects, systems, and applications Agility to rapidly understand new technologies and the infrastructure/architectures to support them Demonstrated ability to influence and deliver results through others, particularly by establishing relationships, and being an effective team member and business partner Good social, collaboration, and self-management skills Strong analysis/problem assessment/problem-solving abilities Demonstrated agility to learn new business processes, identify the appropriate technology, and influence others to adopt Proven track record of technical project delivery, managing multiple projects simultaneously, and effective use of governance processes Understanding of automation technology space, full-stack custom development, and integrations Good To Have Previous pharmaceutical or regulated industry experience Experience with or understanding of relevant technologies and infrastructure/architecture which could include the following: AI/ML-driven automation solutions, including generative AI, observability, monitoring DevOps, CI/CD, and cloud-based automation tools, including AWS or Azure Enterprise architecture and integration strategies Scripting languages and automation frameworks Test automation UI/UX and accessibility best practices Basic Qualifications Bachelor’s Degree in Computer Science, Information Technology or related technical field, AND 7+ years of experience, with at least 5 years specifically demonstrating technical project delivery execution About The Company At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. Lilly Capability Center India provides a strategic advantage to Lilly through delivery of capabilities using cutting edge technologies like most prominent tech companies. What differentiates Lilly IT is that leverage technology to advance our purpose – creating medicines that make life better for people around the world. We hire the best technology professionals from a variety of backgrounds, so they can bring an assortment of knowledge, skills, and diverse thinking to deliver innovative solutions in every area of our business. Will This Position Support Sponsorship No Travel Percentage For This Position 0-10% Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status. #WeAreLilly Show more Show less

Experience with Natural Language Processing (NLP) and Computer Vision (CV) techniques. Knowledge of DevOps methodologies and practices for continuous integration/continuous delivery (CI/CD). Experience with data warehousing and data lakes solutions like BigQuery or Snowflake. Familiarity with real-time data processing and streaming analytics. Passion for learning and staying at the forefront of data science and machine learning advancements. Master's degree in Computer Science, Statistics, Mathematics, or a related field. 7+ years of experience in data science and machine learning with a strong focus on model development and deployment. Expert-level knowledge of statistics, including probability theory, hypothesis testing, and statistical inference. In-depth knowledge of machine learning algorithms, including linear regression, logistic regression, decision trees Good knowledge on software configuration management systems Strong business acumen, strategy and cross-industry thought leadership Awareness of latest technologies and Industry trends Logical thinking and problem solving skills along with an ability to collaborate Two or three industry domain knowledge Understanding of the financial processes for various types of projects and the various pricing models available Client Interfacing skills Knowledge of SDLC and agile methodologies Project and Team management Show more Show less

Position: Business Development Representative (Female) Location: On-site, NCT of Delhi Experience: 1–2 years in B2B SaaS sales Joining Timeline: Immediate joiner Company Overview Mobisec Technologies is a cybersecurity company specializing in mobile device management and cross-platform endpoint auditing and compliance monitoring solutions. As an IIT-Delhi–incubated, DPIIT-recognized startup with ISO 9001:2015 and ISO 27001:2022 certifications, our flagship offerings include MobiHeal MDM (Android Enterprise-validated Mobile Device Management) and Cyber Auditor (automated cybersecurity auditing and compliance monitoring tool). These solutions serve our clients across BFSI, healthcare, government, defence, and manufacturing sectors. We are looking for a proactive Sales professional (Female) to drive our B2B GTM for both mobility and cybersecurity auditing solutions. Role Overview As a Business Development Representative , you will be accountable for hitting clearly defined, measurable targets. Your primary focus will be to: Generate and qualify a consistent pipeline of leads that convert into sales-qualified opportunities. Arrange and coordinate product demos regularly. Achieve deal closures in each quarter, aligning revenue outcomes with company’s growth objectives. Execute high-volume outreach through multiple touchpoints to build and maintain a robust pipeline. Perform field visits to engage directly with decision-makers (e.g., CISO, CIO, IT Head, Security Officer, Compliance Lead) across target sectors and segments. Maintain disciplined CRM hygiene by logging details of outreach, demo, field visit, follow-up—with clear next-step documentation promptly after each interaction. You will be measured strictly against these KPIs. Anything that does not directly contribute to demos, qualified leads, outreach volume, field visits, or closed sales will be deprioritized. Key Responsibilities Lead Generation & Qualification Execute high-volume outreach across multiple channels—targeting relevant IT and security personas. Convert outreach touches into sales-qualified leads, using lead qualification criteria (e.g., budget availability, decision-making authority, timeline). Log relevant touchpoint in the CRM promptly, capturing key qualification details such as company size, use case, and existing vendor. Demo Coordination & Follow-ups Schedule and coordinate product demos for MobiHeal MDM and Cyber Auditor. Document demo outcomes immediately (prospect feedback, next-step agreements) and update CRM records without delay. Field Visits Conduct on-site visits to prospective clients to introduce our offerings, understand technical and operational requirements, and arrange demos. Capture decision-maker contact details and send follow-up communication for each visit. Ensure field-visit notes, next actions, and any immediate objections are logged in the CRM promptly. Conference Participation Represent Mobisec Technologies at leading national conferences—network with industry stakeholders, gather market intelligence, and generate new lead opportunities. Coordinate pre- and post-event outreach to maximize engagement from conference contacts. Sales Closure Achieve quarterly sales targets by rigorously following up on successful demos/POCs. Update deal status and expected close date in the CRM to maintain forecast accuracy. Pipeline Management & Reporting Maintain the entire sales pipeline in the CRM, ensuring that every lead is assigned a stage and probability soon after each interaction. Provide regular performance reports highlighting actual demos conducted, qualified leads generated, field visits completed, and deals closed against targets. Identify any gaps (e.g., insufficient demos or field visits) early and adjust outreach or scheduling to meet KPI thresholds. Qualifications & Experience 1-2 years of proven B2B SaaS sales experience, with a documented track record of meeting or exceeding quantitative targets for demos, lead counts, closed deals. (required) Comfortable executing high-volume outreach and converting prospects into qualified leads. (required) Strong communication skills—able to conduct concise, impactful demos and negotiate deal terms with IT decision-makers under tight timelines. (required) Discipline in CRM usage—logging all activities, maintaining pipeline hygiene, and delivering accurate forecasts. (required) Bachelor’s degree in Engineering, Computer Science, Business, or equivalent. (required) Familiarity with EMM/MDM concepts—device enrollment, policy enforcement, app management, compliance reporting. (preferred) Basic understanding of cybersecurity audit processes and compliance frameworks like DPDP, CIS and ISO 27001 etc. (preferred) Skills & Attributes Results-Driven Mindset: Obsessive about hitting or exceeding KPIs. Self-Starter: Thrives in a structured, metric-driven environment; able to carry out consistent outreach and field visits without hand-holding. Organization & Time Management: Can schedule and conduct multiple demos, visits, and follow-ups while ensuring CRM updates occur promptly. Adaptability: Quick to adjust outreach messaging and demo scripts based on real-time feedback. Basic Technical Aptitude: Understands high-level EMM architecture and cybersecurity audit flows—enough to engage prospects effectively, though deep engineering expertise is not required. Compensation: INR 5-6 Lakhs per annum Job Types: Full-time, Permanent Pay: ₹500,000.00 - ₹600,000.00 per year Benefits: Commuter assistance Leave encashment Schedule: Day shift Ability to commute/relocate: New Delhi, Delhi: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Can you attend a face-to-face interview at our corporate ofice at R&I Park, IIT-Delhi? Are you an immediate joiner? Experience: B2B sales: 1 year (Required) Work Location: In person

Title: Manager - Regulatory Affair Date: Jun 3, 2025 Location: Gurgaon - R&D Company: Sun Pharmaceutical Industries Ltd JOB DESCRIPTION Position : Manager/Senior Manager Job Location : Gurgaon Education : M.Pharm Department : Global Regulatory Affairs Job Responsibilities Serve as a Regulatory CMC Product Lead and provide CMC Regulatory leadership within Regulatory and on cross-functional teams for the assigned branded being developed for US and other advanced markets like EU & Canada Ensure lifecycle management through timely submission of annual reports, supplements etc to ensure product continuity The CMC Product Lead is accountable for the delivery of all regulatory milestones for higher complexity products in which responsible including assessment of the probability of regulatory success together with risk mitigation measures. Lead the development, communication, and review of the CMC Regulatory Strategy Document for projects of increasing complexity. Provide regulatory leadership as needed in product in-license/due diligence review, product divestment and product withdrawal. Manage execution of CMC documentation including PIND/IND/CTA, original NDA/MAA, agency background packages and responses to health authority questions per established business processes and systems. Support new technology development within our Company. Demonstrate an understanding of regulatory affairs and applies this understanding to the benefit of the company to ensure the approval and continued market supply of our Branded products worldwide. Conduct all activities with an unwavering focus on compliance. May need to manage or mentor junior team members. Technical Skills: Hands of expertise of preparation & review of dossiers, response to queries, communication with agencies for developed markets like US/EU Proven experience in critically reviewing detailed scientific information and assessing whether technical arguments are presented clearly and conclusions are adequately supported by data. Demonstrated superior oral and written communication skills in multicultural settings and ability to communicate complex issues in a succinct and logical manner. Strong listening skills. Demonstrated sound understanding of related fields (e.g., manufacturing, analytical, quality assurance) and the ability to be creative and imaginative in the approach to new and diverse problem solving. Demonstrated ability to generate innovative solutions to complex regulatory problems and effectively work with and communicate to key stakeholders. Demonstrated flexibility in responding to changing priorities or dealing with unexpected events. Demonstrated effective leadership, communication, interpersonal and negotiating skills. Education Minimum Requirement: M-Pharm in pharmaceutical sciences Required Experience and Skills: 10-15 years of hands on experience in regulatory affairs This role needs a seasoned professional who is aware of the regulatory activities for NDAs, can work in R & D CFT and who has the management capability of leading a group of team members The candidate must be proficient in English; additional language skills are a plus. Good inter-personnel skills with ability to direct multi-departmental functions.

We seek an experienced mathematician passionate about designing and delivering high-impact casino games to our global customers. You will be part of a Studio with a talented team of PMO, Artists, Game Mathematicians, Game Developers, and Test Engineers. The Studio puts a strong emphasis on quality, individual ownership, and values team players who take pride in developing games. The role involves Game Design of Class 3 & Class 2 casino games for different markets. The role provides the challenge of complexity (Visual design, game mathematics modelling, compliance requirements, etc.) and variety (different cabinets, markets, and languages). Each game is different, and you will be challenged each time. Your work will directly impact the game's delivery to global markets. What You Will Do: Analysis of games requirements with business stakeholders Development of math models for Class 3 & Class 2 slot games - Calculate the probability of the game event. Document game mathematics using Excel-based templates Writes simulations to check math and ensure compliance to jurisdictional requirements Knowledge of C programming language (or equivalent) to check game mathematics and simulate game play Review of math test plan and math testing results. Ensuring the game is compliant with to target market requirements Creating new game concepts Key performance measurements are game quality and time to market What We're Looking For Minimum 2 years of industry experience in Maths or Statistics-related role Basic programming skills in C/C++ under Windows/Linux operating systems Good skills in probability theory and applications Proficient in MS Office tools (MS Excel, MS-doc and PowerPoint) Good understanding of the Software development life cycle Mathematics or Statistics education (MSc, M Tech.) Why Aristocrat? Aristocrat is a world leader in gaming content and technology, and a top-tier publisher of free-to-play mobile games. We deliver great performance for our B2B customers and bring joy to the lives of the millions of people who love to play our casino and mobile games. And while we focus on fun, we never forget our responsibilities. We strive to lead the way in responsible gameplay, and to lift the bar in company governance, employee wellbeing and sustainability. We’re a diverse business united by shared values and an inspiring mission to bring joy to life through the power of play. We aim to create an environment where individual differences are valued, and all employees have the opportunity to realize their potential. We welcome and encourage applications from all people regardless of age, gender, race, ethnicity, cultural background, disability status or LGBTQ+ identity. EEO M/F/D/V World Leader in Gaming Entertainment Robust benefits package Global career opportunities Our Values All about the Player Talent Unleashed Collective Brilliance Good Business Good Citizen Travel Expectations None Additional Information Depending on the nature of your role, you may be required to register with the Nevada Gaming Control Board (NGCB) and/or other gaming jurisdictions in which we operate. At this time, we are unable to sponsor work visas for this position. Candidates must be authorized to work in the job posting location for this position on a full-time basis without the need for current or future visa sponsorship.

We seek an experienced mathematician passionate about designing and delivering high-impact casino games to our global customers. You will be part of a Studio with a talented team of PMO, Artists, Game Mathematicians, Game Developers, and Test Engineers. The Studio puts a strong emphasis on quality, individual ownership, and values team players who take pride in developing games. The role involves Game Design of Class 3 & Class 2 casino games for different markets. The role provides the challenge of complexity (Visual design, game mathematics modelling, compliance requirements, etc.) and variety (different cabinets, markets, and languages). Each game is different, and you will be challenged each time. Your work will directly impact the game's delivery to global markets. What You Will Do: Analysis of games requirements with business stakeholders Development of math models for Class 3 & Class 2 slot games - Calculate the probability of the game event. Document game mathematics using Excel-based templates Writes simulations to check math and ensure compliance to jurisdictional requirements Knowledge of C programming language (or equivalent) to check game mathematics and simulate game play Review of math test plan and math testing results. Ensuring the game is compliant with to target market requirements Creating new game concepts Key performance measurements are game quality and time to market What We're Looking For Minimum 2 years of industry experience in Maths or Statistics-related role Basic programming skills in C/C++ under Windows/Linux operating systems Good skills in probability theory and applications Proficient in MS Office tools (MS Excel, MS-doc and PowerPoint) Good understanding of the Software development life cycle Mathematics or Statistics education (MSc, M Tech.) Why Aristocrat? Aristocrat is a world leader in gaming content and technology, and a top-tier publisher of free-to-play mobile games. We deliver great performance for our B2B customers and bring joy to the lives of the millions of people who love to play our casino and mobile games. And while we focus on fun, we never forget our responsibilities. We strive to lead the way in responsible gameplay, and to lift the bar in company governance, employee wellbeing and sustainability. We’re a diverse business united by shared values and an inspiring mission to bring joy to life through the power of play. We aim to create an environment where individual differences are valued, and all employees have the opportunity to realize their potential. We welcome and encourage applications from all people regardless of age, gender, race, ethnicity, cultural background, disability status or LGBTQ+ identity. EEO M/F/D/V World Leader in Gaming Entertainment Robust benefits package Global career opportunities Our Values All about the Player Talent Unleashed Collective Brilliance Good Business Good Citizen Travel Expectations None Additional Information Depending on the nature of your role, you may be required to register with the Nevada Gaming Control Board (NGCB) and/or other gaming jurisdictions in which we operate. At this time, we are unable to sponsor work visas for this position. Candidates must be authorized to work in the job posting location for this position on a full-time basis without the need for current or future visa sponsorship.

General Responsibilities: Teaching & Curriculum Delivery: Deliver lectures on Mathematics topics relevant to BBA and BCA courses (e.g., Business Mathematics, Quantitative Techniques, Discrete Mathematics, Statistics, Linear Algebra, etc.). Design lesson plans, lecture materials, and assignments as per the university/college syllabus. Use innovative and interactive teaching methodologies to enhance student learning. Assessment & Evaluation: Prepare question papers, evaluate answer sheets, and conduct internal assessments. Provide timely and constructive feedback on assignments, tests, and examinations. Syllabus Planning & Development: Contribute to curriculum development and syllabus updates in coordination with academic committees. Align course content with the learning outcomes and industry requirements. Academic Mentorship: Guide and mentor students on academic performance and mathematical problem-solving. Assist students in applying mathematical concepts in business and computer application contexts. Research & Professional Development: Engage in research, publish academic papers, and participate in seminars and conferences. Stay updated with the latest developments in mathematics and its applications in business and technology. Administrative & Departmental Duties: Participate in departmental meetings, college events, and examination duties. Maintain academic records, attendance, and report progress to department heads. Support for Co-curricular Activities: Encourage and support student participation in math-related competitions, workshops, and events. Organize seminars, guest lectures, or student projects that integrate mathematics with real-world applications. BBA-Specific Responsibilities: Teach mathematical concepts applied in business such as: Business Mathematics Financial Mathematics Quantitative Techniques Business Statistics Help students develop analytical skills for business decision-making. BCA-Specific Responsibilities: Teach mathematics courses relevant to computing such as: Discrete Mathematics Graph Theory Probability and Statistics Numerical Methods Job Type: Full-time Pay: ₹25,000.00 - ₹38,000.00 per month Schedule: Day shift Education: Master's (Required) Experience: TOTAL: 4 years (Required) Language: English (Preferred) Work Location: In person

About Company- MDIndia Health Insurance TPA Pvt. Ltd. was founded in November 2000, with exclusive focus on healthcare insurance and aim of providing TPA (Third Party Administration) services to Indian Health Insurance Sector. IRDA (Insurance Regulatory and Development Authority) issued the TPA License (No. 005) to MD India in March 2001 and very soon MD India became a leading company in the insurance industry. Our company wide reputation is built on Integrity, Knowledge, and Service. MD India Health Insurance TPA Pvt. Ltd. is a young, professional and dynamic organization with a strong workforce of 8000 plus professionals, including over 1000 medicos. Our company services over 25 cr. lives across India through a strong network of over 150 branches and 19000 plus empaneled hospitals and service providers. We are ISO 9001:2018 and 27001:2018 certified. We are associated with all the PSUs and 25 major private insurance companies. We believe in Care, Client Value Retention, Integrity, Respect, Nurturing, and Automation. Website - https://mdindiaonline.com Job Description Designation - Sr.Executive (Data Scientist) Location - Wadgaonsheri, Pune Experience - 2 to 3 yrs Type - On site, Full Time Work Mode - Office only Responsibilities Analyze large volumes of structured and unstructured data to extract meaningful insights. Build and deploy predictive models using machine learning algorithms. Design and execute A/B tests and experiments to validate hypotheses. Collaborate with business stakeholders to identify opportunities where data science can add value. Visualize data and communicate findings through dashboards and presentations. Work with data engineering teams to improve data availability, integrity, and pipelines. Requirements and skills Proven experience as a Data Scientist Understanding and experience of machine-learning, NLP . Knowledge of R, SQL and Python . Experience using business intelligence tool (e.g. Power bi ) would be an advantage and operations research Analytical mind and business acumen Strong math skills (e.g. Statistics, Algebra, Probability ) Problem-solving aptitude Key Skills Machine Learning, Python, SQL, NLP, Deployment. Benefits 1. Exposure in fastest growing industry 2. Experience in domain and support 3. In depth experience in Data Science If interested, kindly share your resume to bshinde@mdindia.com with below required details- Total Experience- Relevant Experience- Current CTC- Expected CTC- Current Company- Current Designation- Reason for leaving- Are you serving Notice period- If no, then Notice Period- How soon you can join, if selected- Current Location in Pune- Available for face to face interview- How many years of experience do you have in ML?- How many years of experience do you have in Python?- How many years of experience do you have in SQL?- Updated CV- Show more Show less

About The Team You’ll be part of the Analytics Team at Meesho. We are trying to revolutionize the way our consumers shop online by experimenting with a video based shopping format. About The Role As a Lead Business Analyst, you will work on improving the reporting tools, methods, and processes of the team you are assigned to. You will also create and deliver weekly, monthly and quarterly metrics critical for tracking and managing the business. You will manage numerous requests concurrently and strategically, prioritising them when necessary. You will actively engage with internal partners throughout the organisation to meet and exceed customer service levels and transport-related KPIs. You will brainstorm simple, scalable solutions to difficult problems, and seamlessly manage projects under your purview. You will maintain excellent relationships with our users – and in fact, advocate for them – while keeping in mind the business goals of your team. What You Will Do Create various algorithms for optimizing demand and supply data Conduct analysis and solution-building based on insights captured from data Give insights to management and help in strategic planning Analyze metrics, key indicators and other available data sources to discover root causes of process defects Support business development and help to create efficient designs and solution processes Determine efficient utilization of resources Research and implement cost reduction opportunities What You Will Need B.Tech/M.Tech /MBA in any discipline 4+ years of experience as a Business Analyst Proficiency in Advanced Excel and Advanced SQL (must-have) – Python is Plus Understanding of basic statistics and probability concepts Proven problem-solving skills Show more Show less

As a Senior Data Scientist, you will apply your expertise in statistics, machine learning, and data analysis to extract valuable insights from structured and unstructured data. You will work closely with cross-functional teams to develop predictive models, improve business processes, and contribute to data-driven decision-making across the organization. Required Skills (Must have) Tech: Advanced programming knowledge in Python and SQL. Advanced knowledge in Probability and Statistics, including hypothesis testing. Advanced knowledge in Practical Machine Learning and awareness of the key-pitfalls in the practice of machine learning and approaches to addressing them. Advanced knowledge of data visualization technologies like Tableau, and PowerBI, and comfortable using relevant libraries in Python like seaborn and matplotlib. Experienced in modern development tools and writing code collaboratively. Intermediate knowledge of Cloud technologies and experience in developing data science solutions in one or more cloud platforms. Experienced in modern development tools, writing code collaboratively and developing solutions on cloud platforms. Non Tech : Ability to recognize and pursue pragmatic alternatives vis--vis a perfect solution, balancing priorities of time with potential business impact. Plan projects, break them down across individual data scientists in the team, track their performance and manage risks. Ability to storyboard an entire presentation to a non-technical audience. Ability to work independently to develop data science solutions, while also being able to work as part of a team to communicate findings and collaborate on solutions. Strong written skills. This is required for submitting technical papers, whitepapers, and developing project documentations. Technical leadership and mentorship to the community of data scientists in the organization. Required Skills (Good to have) Tech: Advanced knowledge in one or more areas besides Machine Learning – Operations Research, Natural Language Processing, Deep learning and its applications, Time Series forecasting at scale. Reinforcement Learning, Graph Machine Learning, Explainable Machine learning. Advanced understanding of Cloud technologies and experience of deploying applications on cloud. Non Tech: Ability to solution critical business problems into its component parts and match each such part with an appropriate technical approach. Roles and Responsibilities As Senior Data Scientist, you will be responsible for a wide range of engagements listed below: Formulates complex problems into hypotheses and proofs of concept for testing. Socializes this with the rest of the team and guides them to deliver on it. Applies business acumen in analyses to extract meaningful and actionable information. Communicates complex ideas and insights effectively to stakeholders with various levels of technical experience. Leverages various analytical techniques, appropriate to solving the business problem at hand. Performs research for solutions and solves problems efficiently to overcome data analytics challenges. Engages in the collection, integration, analysis, and presentation of data for various business contexts Understands good software development practices (versioning, peer reviews, refactoring, and pair programming), adapts them to the needs of the team and sets an example for others by following them. Creates and maintains technical documentation of the scientific experimentations performed, preferably in the CRISP-DM framework or like. Keeps up with the latest trends, technologies, and best practices in the field of Data Science and Engineering. Shares this knowledge with the rest of the data science team. Does peer reviews of codes and approaches of fellow members of the data science team. Provides mentorship to junior data scientists in the team. Looks for improvements in data science delivery processes, actively seeks buy-in on the improvements from peers and managers, implements them in the team and monitors their adoption. 4 to 6 years experience is mandatory