2893 Physics Jobs - Page 48

Entity: Technology Job Family Group: Engineering Group Job Description: About Fuels & Low Carbon Technology: F&LCT is a team of over 300 technologists, scientists and engineers who provide pioneering solutions to support bp’s Fuels, Refining, Bioenergy and Hydrogen businesses. We also support the Technology group through Innovation Management, Modelling, Digital Science and our academic research programmes. Let me tell you about the role: The Scale-Up team in Bioenergy & Hydrogen Technology develop, de-risk and scale up novel processes in the bioenergy and hydrogen value chains. You will be responsible for leading a team of process engineers based in India, who support global process development. Your line manager will be Senior Manager Scale-up based in UK. What you will deliver: Lead the India Engineering team including technical and performance management. Oversee day-to-day team operations including coordinating research and third party projects. Delivery of safe and compliant operations, contributing to the development of a strong HSSE culture. Collaborates seamlessly with other teams to deliver exceptional results. Build scientific capability and insight applied to low carbon challenges . Grow the use of modelling to complement experimentation . Energise the team to solve complex challenges at pace Build relationships based on trust with a wide range of stakeholders Prioritise activities based on potential value and carbon impact. Use relationships and external thinking to generate new insights around major challenges. Spearhead work with business and technology colleagues to identify needs and opportunities involving process engineering, and deliver impactful results and insights that drive success. Take the technical lead in early technology appraisal studies and/or due diligence studies, including techno-economic assessments related to all conversion pathways. Design and lead process scaleup activities related to conversion pathways, including specifying process equipment, project objectives, and communicating priorities. What you will need to be successful (experience and qualifications) : A Bachelors degree in Chemical Engineering (advanced degree desirable) with a strong grasp of underlying fundamentals of physics, reaction engineering, kinetics, and various process technologies. 12+ years of demonstrated professional experience. Prior experience in managing a team. Experience in project delivery, entrepreneurial thinking and building partnerships. Strong networking skills, able to manage delivery of multiple projects across multiple interfaces. A background which mixes a strong theoretical basis with practical, large scale experience in a manufacturing environment, preferably Chemicals or Refining. Expert knowledge or demonstration of engineering scale up design - designing and operating pilot plants and scaling / commercializing new process technologies. Strong leadership, collaboration and communication skills, with proven record of decision-making and appropriate risk-taking. A firm grasp on risk analysis, techno-economic modelling, and safety principles. Process simulation capability, ASPEN+ /Petro-Sim or similar. Demonstrated understanding of key elements related to physical property modelling, techniques and software. Excellent analytical and problem-solving skills. Good to have experiences/skills: Deep experience working in the renewable / low carbon fuels space. Practical experience operating, troubleshooting, or designing larger unit operations; e.g. fixed bed reactors, hydrogen production, syngas production, fermentation, carbon-capture, compression, fired operations. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. About bp: Our purpose is to deliver energy to the world, today and tomorrow. For over 100 years, bp has focused on discovering, developing, and producing oil and gas in the nations where we operate. We are one of the few companies globally that can provide governments and customers with an integrated energy offering. Delivering our strategy sustainably is fundamental to achieving our ambition to be a net zero company by 2050 or sooner! Travel Requirement Up to 25% travel should be expected with this role Relocation Assistance: This role is eligible for relocation within country Remote Type: This position is a hybrid of office/remote working Skills: Legal Disclaimer: We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, socioeconomic status, neurodiversity/neurocognitive functioning, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp’s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us. If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks. Show more Show less

Company Description Yazhvin Software Private Limited is India's pioneering deep tech powerhouse with a bold vision to rival the technological depth and breadth of companies like Google. The company designs and develops a wide range of products from chips to cloud, aiming to build an independent ecosystem for the next era of computing, intelligence, and connectivity. Yazhvin's products span AI Infrastructure, Quantum Computing & Hardware, Yazh Devices, Operating Systems & Dev Tools, Cloud & Search, and Enterprise & Business Software. Role Description This is a full-time hybrid role for a Quantum Chip Designer at Yazhvin. The Quantum Chip Designer will be responsible for designing and developing quantum chips, working on the integration of quantum systems, and contributing to the overall quantum computing hardware development. The role is based in Chennai, but some work from home is acceptable. Qualifications Quantum computing and quantum chip design skills Experience in developing chip architectures and integrating quantum systems Proficiency in semiconductor physics and quantum mechanics Strong programming skills in languages such as Python, C++, or Java Experience with CAD tools and simulation software for chip design Excellent problem-solving and analytical skills Ability to work in a collaborative team environment Master's or Ph.D. in Electrical Engineering, Computer Science, Physics, or related field Show more Show less

Lab49 is an award winning specialist consultancy that creates bespoke technology in partnership with the most important companies in finance. We were founded in 2002 to bring Silicon Valley solutions to Wall Street’s door. Since then, we have worked on successive waves of technological change, including distributed computing, high-speed automation, enterprise UX and digital distribution (for which Lab49 was among the first significant practices established on Wall Street), DevOps, cloud and data science. Today, we are an established partner in financial markets, having delivered hundreds of projects for clients including all the world’s tier-one investment banks and many of the largest buy-side firms globally. Being part of Lab49 means bringing your drive and creativity into an environment where your contributions will make immediate impact. Engineers work in cross functional teams, consulting directly with our clients, shaping not only technical solutions to business problems but delivering them into production. We are seeking a Senior UI Developer, working with our clients in the high frequency trading space. Your close collaboration with both our existing team and our client’s team is essential to both make progress against an existing backlog of work for a custom trading UI, but also manage the ecosystem of UI products in our client’s tech environment. You will report to the Interactive Practice Head and help drive the direction of UI engineering across Responsibilities Act as a hands-on engineer/architect and to support work across the UI & Mobile Engineering Practice; from small initiatives all the way up to the design and build of complex systems. Lead and participate in projects directly, serving as a role model for project teams and working with all other practices to ensure successful project outcome. Lead engineers and stakeholders to ensure appropriate progress and results; must be commercial in approach. Develop strong relationships with clients as a strategic partner and technical advisor, helping us to expand our footprint and secure follow-on work. Partner with and support the business development team to create and deliver compelling pitches that help define the problem, captivate the client, present a solution, and work out the engagement (scope, structure, deliverables) terms. Build and reinforce your professional network through active engagement in industry events, public speaking opportunities, etc. Provide thought leadership for the UI & Mobile Engineering Practice and actively encourage learning and development. Help drive the ongoing effort to find, attract, interview, and hire top software engineering talent. People Management, including coaching, mentoring and performance management of employees may be included in this role. Required Skills And Experience 8+ years of commercial-grade web/front-end development experience. Strong experience in modern JavaScript, ideally TypeScript, building web applications with modern frameworks such as React, Angular and/or Vue. Primary experience in React. Solid skills interacting with multiple types of API formats, preferably REST and GraphQL, but additional skills with Websockets would be desired. Contribute to the design process from gathering requirements, planning and ideating from the start of a project. Demonstrate an understanding of user behavior and how to tailor web experiences to meet the needs of users. Work with designers and other partners to collaborate on design & wireframing and take responsibility for delivering high-quality implementations. Experience with Agile development methodologies. Strong interpersonal and organizational skills. Demonstrable team leadership experience. Knowledge of, and strong demonstrated interest in, global financial markets and financial products is a strong plus. Bachelors or Masters in Computer Science, Engineering, Physics, Math, or related work experience. Why Lab49? Lab49 is an established partner for most financial institutions on Wall Street. You will gain exposure into a variety of environments, business domains, technologies, and people. Your ability to bring drive and creativity to the role will be the key component to success at Lab49. The broad and intense exposure to a variety of challenges accelerates your career growth, and Lab49’s structure is designed to enable you to learn and grow as an engineer and consultant. Show more Show less

Company Description AVIS (Ananta Veda International School) is dedicated to providing quality learning and fostering the overall development of students. The school emphasizes academic excellence as well as extracurricular activities like yoga, karate, and sports. As an institution, we are committed to continuous improvement and welcome fresh ideas to enhance the student experience. Role Description This is a full-time on-site role for an IGCSE Physics Teacher located in Tiruppur. The Physics Teacher will be responsible for lesson planning, teaching physics concepts, and educating students in mathematics. The role will focus on delivering high-quality physics education to students. Qualifications Physics and Physics Education skills Experience in Lesson Planning Strong background in Mathematics Teaching experience in the relevant subject Excellent communication and interpersonal skills Bachelor's or Master's degree in Physics or related field 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

Summary: We are looking for fresh graduates to join our team as Calibration Engineers, responsible for performing precise lab calibration and equipment adjustment activities. This role is ideal for candidates passionate about quality, accuracy, and technical problem-solving in the field of instrumentation and engineering. Job Title: Calibration Engineer Qualification: Diploma, ITI, B.E. in Electronics & Communication, Instrumentation, Mechanical, Electrical, or B.Sc. in Physics. Note: Biomedical not eligible Key Role and Responsibilities: Perform lab calibration and adjustment of instruments and equipment as per defined procedures. Maintain detailed records of calibration activities including dates, results, and equipment condition. Assist customers with technical support related to calibration and equipment usage. Ensure compliance with relevant industry standards and regulatory requirements. Stay updated on advancements in calibration techniques and tools. Skills: Technical knowledge in electronics, instrumentation, mechanical, or electrical systems. Analytical thinking and keen attention to detail. Ability to follow procedures and maintain documentation. Good communication and customer interaction skills. Ability to work independently and manage time effectively. Required Skills: Basic knowledge of electronic, mechanical, thermal, or optical systems. Ability to manage multiple tasks in a fast-paced environment. Clear verbal and written communication skills. Willingness to learn and grow in a technical field. Desired Skills: Familiarity with ISO 17025 calibration standards. Prior lab or workshop exposure through projects or internships (preferred, not mandatory). Reporting To: Manager / Senior Calibration Engineer Job Types: Full-time, Permanent, Fresher Pay: ₹13,000.00 - ₹15,000.00 per month Benefits: Provident Fund Schedule: Day shift Fixed shift Monday to Friday Morning shift Location: Porur, Chennai, Tamil Nadu (Preferred) Work Location: In person

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

Type: Full-time Experience: 5+ Years Industry: Simulation and Technical Animation About the Role: We are seeking a highly skilled Senior 3D Expert with deep expertise in Blender 3D or Unreal Engine 5 to lead and support the development of high-quality, technically accurate 3D training content for the maritime and ship management industry. The ideal candidate will guide and mentor a growing 3D team, contribute to pipeline optimization, and ensure all deliverables meet international standards in realism, efficiency, and functionality. Key Responsibilities: Lead the design and development of high-fidelity 3D environments, characters, assets, and animations using Blender and Unreal Engine 5. Review and optimize existing models and scenes for performance and visual quality across platforms. Provide technical direction and creative supervision to junior 3D artists and animators. Collaborate closely with instructional designers, video editors, and technical content teams to align 3D assets with real-world training objectives. Research, propose, and implement best practices in 3D modelling, lighting, shading, rendering, and optimization workflows. Support interactive/real-time visualization in Unreal Engine 5, including lighting, materials, level design, and FX. Conduct regular training sessions, provide feedback, and mentor the 3D team on toolsets and workflows. Troubleshoot and resolve complex 3D-related technical issues. Maintain consistency, accuracy, and realism across all 3D outputs. Required Skills & Qualifications: 5+ years of hands-on experience in 3D modelling, texturing, animation, and scene setup. Expert-level proficiency in Blender 3D or Unreal Engine 5 . Solid understanding of 3D production pipelines for training simulations or technical animations. Strong knowledge of lighting, shading, rigging, rendering, and real-time optimization techniques. Experience working with technical scripts or visual logic systems (Blueprints in UE5). Good understanding of real-world physics , material behaviour, and photorealistic design. Ability to guide junior artists and review work with a sharp eye for detail. Preferred / Advantageous Skills: Working knowledge of Autodesk Maya , AutoCAD , 3ds Max , Cinema4D , or ZBrush . Familiarity with substance tools (Substance Painter/Designer). Prior experience in marine or industrial training videos, simulations, or AR/VR environments . Basic understanding of video post-production tools like DaVinci Resolve or After Effects . Experience in project leadership or team management. Why Join Us: Work on impactful, real-world 3D projects in the maritime training sector. Collaborate with a passionate team on next-gen simulations and educational content. Opportunity to lead, innovate, and shape the 3D pipeline and training culture. Competitive compensation with room for growth and creative freedom. How to Apply: Please send your resume, portfolio, and a short note about your experience with Blender and Unreal Engine 5 to: karthik@qcentro.com / hr@qcentro.com Job Type: Permanent Ability to commute/relocate: Kochin, Kerala: Reliably commute or planning to relocate before starting work (Required) Experience: 3D Expert – Blender 3D & Unreal Engine 5: 5 years (Required) Work Location: In person

Embark your transformative journey as a Unsecured Capital Model Risk-Vice President. At Barclays we are committed to pushing boundaries where you'll spearhead the evolution of our Model Risk landscape, driving innovation and excellence. You will be working with experts like Model developers and Tech consultants, connect the dots with Regulatory requirements, Portfolio strategy; brainstorm within team and then taking a sustainable decision that can withstand the challenges from IVU, Audit & Regulators. You will be understanding the customer credit behavioural trends, optimise portfolio risk and return, analytically design credit policies and underwriting strategies, and set credit parameters for all programmes that impact customers to ensure loss rates remain within risk appetite whilst the expected reward is achieved which cuts across the several different products within the UK market including Credit Card, Loan, Partner Finance, and personal Current Account & Overdraft businesses. To be successful as a Unsecured Capital Model Risk-Vice President, you should have experience with: Excellent communication skills who appreciate the importance of narratives, ability to challenge and speak-up to drive the right outcomes for the business and our customers. Sound people management skills . Ability to work independently, advise stakeholders, and thrive in a dynamic and fast paced environment. Expert with Advanced Statistical model development or validation . Proficient with Regulation (Basel, IFRS9) and interpretation. Proficient with SAS/ Python, Ms-office tools. Ability to provide oversight to strategic initiatives to large scale changes in the data or platform. Some Other Highly Valued Skills May Include Strong academic background in a numerical discipline e.g. mathematics, statistics, informatics, economics, physics etc. Excellent quantitative skills with exceptional analytical skills and logical thinking. Understanding of Basel 3.1, IFRS9 and BCBS regulation and how they interact. Experience designing Regulatory Capital models – PD, EAD, LGD for retail portfolios. Advanced understanding of automation tools like Tableau, GenAI integration into productivity improvement . You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role will be based out of Noida. Purpose of the role To manage and optimise the bank's overall credit risk exposure by monitoring, analysing, and reporting on the creditworthiness of its lending portfolio. Accountabilities Monitoring the financial performance and risk profile of the entire lending portfolio, including individual borrowers, sectors, and geographic regions. Analysis of credit trends, identify early warning signs of potential borrowers' issues, and assess the impact of economic and market developments on the portfolio. Development and utilisation of quantitative models and risk forecasting tools to measure and predict potential credit losses. Performance of portfolio stress testing exercises to assess the impact of various economic and market scenarios on the portfolio's risk profile. Definition and setting of portfolio, segment and customer risk appetite, policy and limits. Overseeing first line execution within these parameters. Vice President Expectations To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures.. If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.. OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions.. Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment. Manage and mitigate risks through assessment, in support of the control and governance agenda. Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does. Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies. Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions. Adopt and include the outcomes of extensive research in problem solving processes. Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. 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Join us as a Vice President Senior Senior KDB/Q Developer at Barclays. To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure. The ideal candidate is responsible and accountable for building and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data, design and implementation of data warehouse and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. The candidate is also expected for the development of processing and analysis algorithms fit for the intended data complexity and volumes in collaboration with data scientist to build and deploy machine learning models. To contribute or set strategy, drive requirements and make recommendations for change. To be successful as a Vice President Senior Senior KDB/Q Developer, you should have experience with: Excellent Q/Kdb+ programming skills on Linux Development experience in front office / electronic trading systems Strong knowledge of agile and SDLC processes Experience with Maven / Java / Git / Team City / Jira / Confluence Some Other Highly Valued Skills May Include Strong academic record with a numerate degree (2:1 or higher) - e.g., computer science, maths, physics, engineering. Full-lifecycle development on at least 1 large commercial system, with ideal candidate focusing on significant development of large distributed Kdb+ systems You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skill. This role is for Pune location. Purpose of the role To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure. Accountabilities Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data. Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. Development of processing and analysis algorithms fit for the intended data complexity and volumes. Collaboration with data scientist to build and deploy machine learning models. Vice President Expectations To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures.. If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.. OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions.. Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment. Manage and mitigate risks through assessment, in support of the control and governance agenda. Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does. Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies. Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions. Adopt and include the outcomes of extensive research in problem solving processes. Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. 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Embark your transformative journey as a Unsecured Capital Model Risk-Vice President. At Barclays we are committed to pushing boundaries where you'll spearhead the evolution of our Model Risk landscape, driving innovation and excellence. You will be working with experts like Model developers and Tech consultants, connect the dots with Regulatory requirements, Portfolio strategy; brainstorm within team and then taking a sustainable decision that can withstand the challenges from IVU, Audit & Regulators. You will be understanding the customer credit behavioural trends, optimise portfolio risk and return, analytically design credit policies and underwriting strategies, and set credit parameters for all programmes that impact customers to ensure loss rates remain within risk appetite whilst the expected reward is achieved which cuts across the several different products within the UK market including Credit Card, Loan, Partner Finance, and personal Current Account & Overdraft businesses. To be successful as a Unsecured Capital Model Risk-Vice President, you should have experience with: Excellent communication skills who appreciate the importance of narratives, ability to challenge and speak-up to drive the right outcomes for the business and our customers. Sound people management skills . Ability to work independently, advise stakeholders, and thrive in a dynamic and fast paced environment. Expert with Advanced Statistical model development or validation . Proficient with Regulation (Basel, IFRS9) and interpretation. Proficient with SAS/ Python, Ms-office tools. Ability to provide oversight to strategic initiatives to large scale changes in the data or platform. Some Other Highly Valued Skills May Include Strong academic background in a numerical discipline e.g. mathematics, statistics, informatics, economics, physics etc. Excellent quantitative skills with exceptional analytical skills and logical thinking. Understanding of Basel 3.1, IFRS9 and BCBS regulation and how they interact. Experience designing Regulatory Capital models – PD, EAD, LGD for retail portfolios. Advanced understanding of automation tools like Tableau, GenAI integration into productivity improvement . You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role will be based out of Noida. Purpose of the role To manage and optimise the bank's overall credit risk exposure by monitoring, analysing, and reporting on the creditworthiness of its lending portfolio. Accountabilities Monitoring the financial performance and risk profile of the entire lending portfolio, including individual borrowers, sectors, and geographic regions. Analysis of credit trends, identify early warning signs of potential borrowers' issues, and assess the impact of economic and market developments on the portfolio. Development and utilisation of quantitative models and risk forecasting tools to measure and predict potential credit losses. Performance of portfolio stress testing exercises to assess the impact of various economic and market scenarios on the portfolio's risk profile. Definition and setting of portfolio, segment and customer risk appetite, policy and limits. Overseeing first line execution within these parameters. Vice President Expectations To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures.. If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.. OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions.. Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment. Manage and mitigate risks through assessment, in support of the control and governance agenda. Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does. Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies. Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions. Adopt and include the outcomes of extensive research in problem solving processes. Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. 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Project Role Application Lead Project Role Description Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills Automotive ECU Software Good to have skills NA Minimum 5 year(s) of experience is required Educational Qualification 15 years full time education SummaryAs a Test Development Engineer, design test cases, develop validation framework, and ensure that the system requirements are effectively validated. Roles and Responsibilities:1.Analyze system requirements and develop structured test cases for validation. 2.Design and implement validation strategies to ensure robust testing methodologies. 3.Develop and refine test frameworks and automation techniques for efficient validation. 4.Work with physics-based models, simulation tools, and validation processes to improve testing effectiveness. 5.Support the development and validation of tire models.6.Perform test data review to ensure accuracy and completeness of validation results. 7.Utilize Dspace modeling for test environment setup and validation support. 8.Collaborate with cross-functional teams to identify potential issues, innovate test approaches, and enhance validation efficiency. 9.Document test strategies, procedures, and validation results to support continuous improvement. 10.Contribute to innovative approaches in validation, leveraging AI-driven techniques, automation, and advanced test methodologies.Professional & Technical Skills: 1.Minimum 7 years of experience in performing validation tests across systems and vehicles (preferably in ADAS domain).2.Experience with data analysis tools (MATLAB, Python, or similar). 3.Familiarity with simulation environments and test automation frameworks. 4.Experience with vehicle dynamics models and prior automotive industry knowledge. 5.Understanding of ASPICE, ISO 26262, and systems engineering processes. 6.Experience with JIRA and Polarion for test case management and validation tracking.7.Understanding of vehicle dynamics, test methodologies, and validation strategies. 8.Knowledge of tire modeling or vehicle physics-based modeling is a plus.Additional Information:1.The candidate should have a minimum of 5 years of experience in Automotive ECU Software2.This position is based at our Hyderabad office3.A 15 years full time education is required (Bachelor of Engineering in Electronics, or any related stream.) Qualification 15 years full time education

Job Description Consultant-Intern – EComm/Electrical We are looking at hiring candidates with B. Tech / M. Tech (qualified/ final year students) Electronics/Electrical/Electronics & Communication with specialization in semiconductor/solid-state devices, who are willing to work in Intellectual Property (IP) / Patents domain. The candidate will work on various projects such as re-classification projects, patent and non-patent prior art searching, infringement analysis, and other related services. We would love to speak with you if you have aptitude to work on emerging technologies. About You Bachelor/master’s degree in physics, Semiconductor Physics and/or in Microelectronic Devices. BE/B. Tech/M. Tech in Electronics/Electrical/Electronics & Communication with specialization in semiconductor/solid-state devices. Should have deep understanding of organic and inorganic semiconductor/solid-state devices such as diodes (PN Junction Diodes, Schottky Diodes etc.), resistors, capacitors, thyristors, transistors, Bipolar Junction Transistors (BJTs), Field Effect Transistors (FETs), MOSFET, IGFET, EDMOS, DDMOS, Integrated Devices, Charge Transfer Devices etc. Should have deep understanding of fabrication process of the semiconductor/solid-state devices. Should have deep understanding of functioning, structure and materials used in semiconductor/solid-state devices. Must be a quick learner and must demonstrate strong aptitude for out-of-the-box thinking and problem solving Proficient in written & verbal communication skills What will you be doing in this role? Reclassification of patent and/or non-patent documents into relevant classification codes. Ownership of work products and effective project communication with relevant stakeholders. Quality Assurance - Adherence and compliance to set quality standards ensuring customer requirement are met in full. Updating technical skills proactively in upcoming technologies being widely used across industry. Hours of Work This is a fix-term (6 months) role requiring 45 hours per week (IST). At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations. Show more Show less