7899 Simulation Jobs - Page 25

Requisition #: 16889 Ansys is now a part of Synopsys. Synopsys, Inc. (Nasdaq: SNPS) accelerates technology innovation from silicon to systems. Catalyzing the era of pervasive intelligence, we deliver design solutions, from electronic design automation to silicon IP, to system design and multiphysics simulation and analysis. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow. Learn more at www.synopsys.com. Summary / Role Purpose The Product Specialist (m/f/d) joins the Ansys Electronics Business Unit to conduct software testing of Ansys Electronics applications such as HFSS, SIwave, Q3D Extractor, Maxwell and Icepak on Cloud environment. This role helps to assess how well the product meets customers needs both in terms of functionality and usability and ensures that product requirements and quality standards are satisfied per the company s quality procedures. The individual works closely with other members of the product creation and field engineering team and communicates with technical specialists on product issues. In this position, the engineer contributes to the quality of tools that are used throughout the industry to develop electronics products in a wide range of industries. Key Duties and Responsibilities Test Ansys Electronics Products on Cloud and HPC (High Performance Computing) Environment Perform benchmark of projects on different HPC and Hardware configuration Develop/contribute to automation scripts Apply standard techniques and procedures and comply with the companys overall development and testing processes Work in a variety of computing environments: Windows, Linux, AWS, Azure, Any programming or scripting language C++/Python/.. Work closely with product owners, documentation and development in an agile environment. Support the team in following the Ansys software development life cycle Analyze defect reports from customers Minimum Education/Certification Requirements and Experience BS in Engineering, Electronics and Communication, Electrical and Electronics or related field Preferred Qualifications and Skills Electromagnetic simulation experience (HFSS highly preferred) Experience with HPC (including GPU) and Cloud environment Familiarity with Python and automation scripts Basic understanding of software testing and verification processes Good communication and interpersonal skills Ability to learn quickly and to collaborate with others in a geographically distributed team Fluent English, both written and spoken Rewards and Benefits: We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process. At Ansys, part of Synopsys, we want talented people of every background to feel valued and supported to do their best work. We consider all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.

Requisition #: 16690 Ansys is now a part of Synopsys. Synopsys, Inc. (Nasdaq: SNPS) accelerates technology innovation from silicon to systems. Catalyzing the era of pervasive intelligence, we deliver design solutions, from electronic design automation to silicon IP, to system design and multiphysics simulation and analysis. We partner closely with our customers across a wide range of industries to maximize their RD capability and productivity, powering innovation today that ignites the ingenuity of tomorrow. Learn more at www.synopsys.com. Summary / Role Purpose The RD Engineer II contributes to the development of software products and supporting systems. In this role, the RD Engineer II will collaborate with a team of expert professionals to understand customer requirements and accomplish development objectives. Key Duties and Responsibilities Performs moderately complex development activities, including the design, implementation, maintenance, testing and documentation of software modules and sub-systems Understands and employs best practices Performs moderately complex bug verification, release testing and beta support for assigned products. Researches problems discovered by QA or product support and develops solutions Understands the marketing requirements for a product, including target environment, performance criteria and competitive issues Works under the general supervision of a development manager Minimum Education/Certification Requirements and Experience BS in Engineering, Computer Science, or related field with 2 years experience or MS Working experience with C/C++ coding, data structures and algorithms. Preferred Qualifications and Skills Technical knowledge and experience with computational geometry or mesh generation and. object-oriented design Technical knowledge and experience with scripting languages like Python is a plus. Technical knowledge and experience with parallel programming and GPU is a plus. Experience in a large-scale commercial software development environment Rewards and Benefits: We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process. At Ansys, part of Synopsys, we want talented people of every background to feel valued and supported to do their best work. We consider all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.

Roles & Responsibilities : SW QA Engineer will perform testing on the Control Logics developed by Control SW Engineer. Also be responsible for testing UI. Preparation of tests cases for HiL, SiL environments by understanding the control SW models developed using MATLAB/Simulink Preparation of tests cases for HiL, SiL environments by understanding the control SW algorithms developed using C++ Automation of test cases for HiL, SiL environments using Python, C/C++

We are now looking to hire strong performance verification engineers with a sharp understanding of CPU and memory architecture. NVIDIA makes some of the fastest CPUs in the world and is solving problems, with its vast arsenal of CPUs, GPUs and SW, in areas such as High-performance computing, Automated driving, Medical imaging and much more! We are seeking highly motivated engineers to join this dynamic and innovative team that owns performance alignment of CPUs and CPU fabrics made by NVIDIA! Do you want to be part of the team that explores and defines the next generation of CPUs What will you be doing: Responsibilities will include development of test plans and strategies, develop simulation environments, system bring-up, validation, and automation to deliver best-in-class CPUs. Develop and maintain CPU simulator infrastructure, hardware CPU test and performance infrastructure. Analyze and validate CPU and fabric performance, helping to understand current, and guide the development of future CPU products. Definition and development of tool chain and workflows that enables the full system performance alignment. Silicon based competitive analysis of NVIDIA CPUs. What we need to see: Masters or Bachelors degree in EE/CS or equivalent experience 5+ years of experience preferably in the areas of CPU / SOC Performance Verification and Analysis Strong understanding of computer system architecture and operating system fundamentals. Hands-on experience with HDLs such as Verilog / System Verilog. Knowledge of verification methodologies and tools for IP and SoC level verification. Experience with System Verilog, C/C++, Python languages and relevant frameworks. Background with debug on Silicon. Ways to stand out from the crowd: Detailed knowledge of the ARM and/or x-86 architecture. Prior experience with performance analysis of CPUs. Experience with analysis and characterization of CPU workloads. #LI-Hybrid

NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel. NVIDIA is a learning machine that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life s work , to amplify human creativity and intelligence. As an NVIDIAN, you ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join our diverse team and see how you can make a lasting impact on the world! What you ll be doing: Work on structural and functional verification of low power aspects of NVIDIA s family of chips. Come up with test plans and coverage plans of these features. Write test cases, test bench components like assertions and coverage points, and own verification convergence. Collaborate with system level and unit level teams to cover the features well from functional, electrical, performance, and noise aspects. Work with architects, designers, pre- and post-silicon verification teams, synthesis, timing and back-end teams to accomplish your tasks. Validate the effectiveness of the low power features on silicon. What we need to see: BS/MS or equivalent experience with specialization related to Low Power techniques and Verification. 2+ years of experience. Fundamental understanding of power basics including transistor-level leakage/dynamic characteristics of VLSI circuits. Knowledge of power intent formats - UPF/CPF. Experience in Static Power check - tools like VCLP/MVRC or similar. Hands-on knowledge in Power aware dynamic verification - NLP/MVSIM or similar tools. Experience in design and verification tools (VCS or equivalent simulation tools, Verdi or other debug tools). Familiarity with low power design techniques such as multi VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS). Ways to stand out from the crowd: Good software programming skills. Python/Perl/C++ preferred. Confident debugging and problem-solving skills. Good communication skills and ability & desire to work as a great teammate. With competitive salaries and a generous benefits package, Nvidia is widely considered to be one of the most desirable employers in the world. #LI-Hybrid

We are looking for a skilled and innovative Simulation Engineer for the Research & Development team. The ideal candidate will be responsible for conceptualizing and designing mechanical components, performing advanced electromagnetic simulations, and supporting the production team on the shop floor. Key Responsibilities: Apply product design concepts and simulation techniques to support electromagnetic simulations. Conduct simulations using ANSYS HFSS; knowledge of mechanical and thermal integration preferred. Automate simulation workflows using Python or similar programming languages. Provide simulation support for various R&D projects. Analyze simulation results and optimize product design based on outcomes. Perform mechanical and thermal simulations, capacitor characterization, and thermal mapping. Collaborate with design and manufacturing teams to translate concepts into simulation models. Skills & Knowledge: Strong fundamentals in electromagnetic simulations. Hands-on experience with ANSYS HFSS, ANSYS Q3D, Solid Edge/SolidWorks. Knowledge of plastic injection molding, adhesives, stamping, and punching processes. Familiarity with FMEA, APQP processes. Understanding of material properties and testing methods. Knowledge of industry standards (ZVEI, AEC Q200, IEC, IATF, ISO). Good programming skills in Python, C#, or JavaScript. Soft Skills: Self-motivated and independent contributor. Strong analytical and logical thinking. Team player with flexibility and innovation mindset. Good communication, documentation, and reporting skills.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

Job Description Undertake process design work for projects and studies including the following typical activities and deliverables:- Concept design and layout development Process descriptions and design basis Material balances Preparation of process flow diagrams & piping and instrumentation diagrams Preparation of equipment lists, equipment datasheets, specifications Fluids lists and materials selection Process hazard studies (including HAZOP) and design safety reviews Detailed process design calculations Pressure relief design Hazardous area classification/assessment Utilities schedules, utilities flow diagrams and line sizing Process simulation using Hysys / Aspen Plus. Checking / Approval of process deliverables Commissioning plans and support Qualifications Knowledge of process engineering design in fine chemicals, pharmaceutical and/or biopharmaceutical industries OR Operating experience within chemicals or pharmaceutical sectors would be beneficial. Awareness of process safety systems design in high hazard industries and /or process safety training . eg HAZOP, Hazardous Area Assessment, SIL assessment, Pressure Relief etc. Experience with process modelling software (steady state & dynamic). Awareness of applicable regulatory standards, policies, and codes of practice for the process industries. Good interpersonal skills and able to work as part of a multi-discipline team. Versatile, reliable and resourceful. Personal qualities that include the ability to gain trust and confidence with a variety of clients as well as within the company. Customer focus, commitment to quality management and problem solving. Ability to work as an engineer on a variety of projects at the same time.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

We are seeking a highly skilled and analytical Senior QA Engineer specializing in Application Performance and Regression Testing . This role is crucial for ensuring the stability, scalability, and reliability of our enterprise applications, particularly as we modernize and migrate existing workloads to cloud environments like AWS and Azure. The ideal candidate will possess a strong blend of application performance engineering expertise, meticulous regression testing practices, and a solid understanding of cloud-native architectures. You will be responsible for designing, executing, and analyzing performance and regression tests, identifying critical bottlenecks, and ensuring seamless application functionality post-migration. Responsibilities Application Performance Testing & Engineering: Design, develop, and execute comprehensive performance test plans and strategies for complex enterprise applications, including workload modeling, stress, soak, and scalability testing. Create and maintain performance test scripts using tools such as JMeter, LoadRunner, k6 , or similar, ensuring accurate simulation of user behavior and business transactions. Monitor and analyze application performance metrics (e.g., response times, throughput, resource utilization, error rates) using APM tools (e.g., Dynatrace, New Relic, AppDynamics, CloudWatch, Azure Monitor) to identify bottlenecks and areas for optimization. Collaborate closely with development, DevOps, and cloud engineering teams to pinpoint root causes of performance degradation and recommend solutions. Conduct performance baselining and compare results against non-functional requirements and pre-migration benchmarks to validate performance improvements or identify regressions. Provide insights into the impact of cloud infrastructure configurations (e.g., instance types, database performance, networking) on application performance. Application Regression Testing (Cloud Migration Focus) Develop and execute robust regression test suites to ensure that new features, bug fixes, and especially cloud migrations do not introduce new defects or negatively impact existing application functionality and performance. Verify the integrity of migrated applications within AWS and Azure environments, focusing on application-level functionality, data consistency, service interactions, and configuration adherence post-migration. Actively participate in all phases of the cloud migration process , focusing specifically on the quality assurance of application functionality, performance, and data integrity within the new cloud landscape. Review and analyze system specifications, architectural designs, and migration plans to ensure comprehensive test coverage for functional, integration, and performance aspects of migrated applications. Engage in functional, integration, and system regression testing of cloud-deployed applications, microservices, and their integrated components. Defect Management & Reporting Identify, document, and meticulously track defects related to application functionality, performance, and regressions. Collaborate effectively with development and cloud engineering teams to prioritize, troubleshoot, and coordinate defect resolution. Generate detailed testing reports and metrics for management review, providing clear insights into application performance, regression status, and overall quality, particularly in the context of cloud migrations. Collaboration & Best Practices Contribute to the continuous improvement of performance and regression testing methodologies , tools, and processes. Work with development teams to incorporate performance testing best practices earlier in the development lifecycle (Shift-Left). Utilize version control systems effectively for test assets (scripts, plans, data). Maintain a fair understanding of application security considerations as they relate to performance and functional integrity. Communicate complex ideas and technical information clearly and concisely through excellent verbal and written communication skills to both technical and non-technical stakeholders. AI Adoptions : Should adapt to new AI standards in Testing and implement the same in house to improve team productivity and efficiency Qualifications Bachelor's degree in Computer Science, Engineering, or a related field. 5+ years of dedicated experience in Application Performance Testing and Engineering. 3+ years of experience in Application Regression Testing , particularly in complex enterprise environments. Demonstrated expertise with performance testing tools such as JMeter (strong proficiency required), LoadRunner, or k6. Hands-on experience in at least two significant engagements involving the analysis and migration of existing enterprise applications to AWS or Azure , with a focus on ensuring application quality and performance post-migration. Solid understanding of application architectures (monolithic, microservices), databases, and network fundamentals. Familiarity with APM tools and cloud-native monitoring services (e.g., AWS CloudWatch, Azure Monitor). Experience with version control systems (e.g., Git). Strong analytical and problem-solving skills, with the ability to diagnose performance bottlenecks and root causes of defects. Excellent communication and collaboration skills.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

About Marut Marut Drones is India's leading Industrial Drone Manufacturer based in Hyderabad. Known for our powerful and innovative drones, we have developed popular models like Agricopter for precision agriculture, Hepicopter for long-range deliveries, Seed copter for afforestation, and Marut ZAP for mosquito eradication and disease prediction. Marut Drones has been recognized with numerous prestigious awards for its innovation and contributions to various sectors. These accolades include the FICCI Award for Sustainable Agriculture , the Telangana State Industries Award 2022 for Best Startup , the NASSCOM Emerging Technology Award for Drones and AI , and the South India Business Award . These awards highlight the company's commitment to excellence, sustainability, and its transformative impact across industries. Job Description Marut Drones is seeking a Senior Lead UAV Engineer to lead the design, development, and integration of cutting-edge unmanned aerial vehicles (UAVs). The role involves overseeing a team of engineers, driving innovation, and ensuring the technical excellence of drone systems throughout the product lifecycle—from conceptualization to testing and deployment. Key Responsibilities Lead UAV Development: Oversee the design, development, and integration of UAV systems and subsystems, ensuring performance, safety, and reliability. Lead the engineering team in designing systems such as propulsion, flight control, power, and payload integration. Team Leadership: Manage and mentor a team of UAV engineers, providing technical guidance, support, and leadership. Foster a collaborative, innovative, and high-performance engineering environment. System Integration: Ensure seamless integration of mechanical, electrical, and software components to create fully functional UAV systems. Coordinate between cross-functional teams to ensure alignment in design and testing. R&D and Innovation: Drive innovation in UAV design and technology by researching emerging trends and technologies in the aerospace and drone sectors. Implement new features, improvements, and optimizations. Testing and Validation: Lead the testing and validation of UAV systems, ensuring they meet industry standards and company requirements. Oversee flight tests, performance evaluations, and failure analysis. Design Optimization: Continuously iterate and optimize designs to improve UAV performance, reliability, and efficiency. Use simulation tools and analysis to validate and refine designs. Quality Assurance & Compliance: Ensure UAV systems comply with regulatory standards and industry certifications, maintaining high levels of quality control. Contribute to safety protocols, design reviews, and audits. Cross-Department Collaboration: Work closely with manufacturing, marketing, and operations teams to ensure that UAV systems are optimized for production, user requirements, and market expectations. Documentation & Reporting: Maintain detailed technical documentation of design processes, test results, and engineering reports. Present technical findings and progress updates to senior management. Knowledge And Skill Required Expertise in UAV design, development, and integration across mechanical, electrical, and software domains. Proficiency in UAV flight dynamics, control systems, navigation, and payload integration. Strong understanding of UAV components including motors, sensors, batteries, communication systems, and flight controllers. Familiarity with UAV simulation software (e.g., MATLAB, Simulink) and flight control systems. Solid background in product lifecycle management (PLM), design validation, and testing processes. Strong leadership, team management, and interpersonal skills. Problem-solving abilities and capacity to innovate within the UAV engineering field. Knowledge of regulatory requirements, safety standards, and certifications related to UAVs (e.g., FAA, EASA). Familiarity with drone development tools such as CAD, CAM, and PLM software. Qualifications Bachelor’s or Master’s degree in Aerospace Engineering, Mechanical Engineering, Electrical Engineering, or a related field. 7+ years of experience in UAV engineering, with at least 3 years in a leadership role. Proven experience in the design, development, and integration of UAV systems. Strong background in aerospace systems, propulsion, flight control, or avionics. Experience in both hardware and software integration for UAV systems. Experience with regulatory compliance and quality assurance processes for UAVs is highly preferred. Compensation Competitive and we are open to discuss.

It's more than a job As a Contract Logistics Specialist at Kuehne+Nagel, you will manage end-to-end warehousing operations for our customers. By doing so with precision, you not only contribute to the success of your team, but also to the day-to-day operations and success in the warehouse and distribution centres. For example, storing and delivering delicate flowers and fresh ingredients to local stores for everyday lunches and family celebrations. At Kuehne+Nagel, our work truly contributes to more than we imagine. ‎ You will be part of our contract logistics team, adding your leadership expertise + skills to the delivery of Customer + Operational Excellence. Your primary objective is to be successful in gaining + retaining customers by offering industry leading solutions. How you create impact You will be working with internal + external stakeholders while focusing on the following key objectives: To manage others in the development of successful customer solutions. To take the lead in major customer tender proposals, driving compelling logistics concepts. To drive innovation, introducing + implementing new concepts + technology while building on existing best practices. To present solutions to the customer as key part of the tendering process. To be the business partner for your management team when addressing solution queries from customers, as well as challenging the status quo + customers in a constructive way where needed. To manage partnerships with key vendors to optimize costing + lead-times. To support the development of others in terms of skills + knowledge levels, assuring high standards of compliance. What we would like you to bring Experience in logistic and supply chain industry in 3PL. Have 7 to 10 years of working experience in a managerial position. A solo contributor managing West India. Has done solution designing and network design for warehouse and transport solution. Has AutoCAD and Loghub knowledge and experience. Data analysis, creation of volume/material flow Process Flow and Blue men diagram Storage design, space calculation, 2D/3D Layout, Simulation and Video Warehouse process design (Time and motion study) Resource and Equipment calculation Productivity analysis Design & evaluate multiple transportation/Network scenario/supply chain solutions specific to customer requirements and goals. Solution Costing and pricing Preparation of proposal document and presentation to customer What's in it for you Global Industry Leader – Work for one of the top logistics and supply chain companies worldwide, offering stability and international reach. Career Growth Opportunities – Access to strong internal development programs, training, and global mobility. Diverse & Inclusive Culture – Collaborate with teams across the globe in a supportive and multicultural environment. Innovative & Future-Focused – Be part of a company investing in sustainability, digitalization, and green logistics. Competitive Benefits – Enjoy attractive compensation, flexible working options, and comprehensive benefits packages. Who we are Logistics shapes everyday life - from the goods we consume to the healthcare we rely on. At Kuehne+Nagel, your work goes beyond logistics; it enables both ordinary and special moments in the lives of people around the world. As a global leader with a strong heritage and a vision to move the world forward, we offer a safe, stable environment where your career can make a real difference. Whether we help deliver life-saving medicines, develop sustainable transportation solutions or support our local communities, your career will contribute to more than you can imagine.

Our people work differently depending on their jobs and needs. From hybrid working to flexible hours, we have plenty of options that help our people to thrive. This role is based in India and as such all normal working days must be carried out in India. Job Description Join us as a Senior Risk Quantitative Analyst This is a great opportunity for someone with experience in a quantitative role to join our Risk function You’ll be working closely with quantitative analysts across asset classes to identify and assess diffusion models and pricer approximations Hone your analytical skills and advance your career in this fast paced, critical role We're offering this role at senior analyst level What you'll do This key role will see you providing model, pricing and functional specifications of the models for the various asset classes, and for the subsequent validation by risk analytics. We’ll also look to you to support to a team of quantitative analysts and technical specialists, providing quantitative and technical mentoring to help them develop in their roles. Day-to-day, you’ll also be: Supporting a phased delivery of the simulation models and pricer prototypes Producing model documentation to be delivered to the PRA for internal review Advising senior management on and actively managing a project’s non-delivery risk Maintaining and making sure that adequate documentation is produced for governance Assisting our IT department in implementing the models, and overseeing the implementation of the functional specifications back-testing against the prototypes The skills you'll need We’re looking or someone with substantial experience in a quantitative role of specified asset classes, and experience in credit valuation adjustments, expected positive exposure, building valuation models, optimising pricing routines and computing efficiency. You’ll have a proven ability to facilitate work across organisational boundaries, and you’ll be able to remove barriers that constrain performance excellence and make sure that quality improvements meet the needs and expectation of a diverse population. We’ll also expect: Exceptional Problem-Solving Skills. Ability to approach complex challenges with analytical rigor and creativity. Strong Quantitative and Statistical Expertise. Solid foundation in probability theory, statistics, calculus and data analysis techniques. Proficient Programming Skills. Python or similar languages for data analysis and model development. Financial and Risk Acumen. Good understanding of financial instruments and core risk concepts. Attention to Detail. Careful and thorough approach to data, models, and documentation, ensuring accuracy and reliability in all aspects of analysis. Effective Communication. Ability to explain technical concepts effectively to both technical and non-technical audiences

Siemens Digital Industries Software is a leading provider of solutions for the design, simulation, and manufacture of products across many different industries. Formula 1 cars, skyscrapers, ships, space exploration vehicles, and many of the objects we see in our daily lives are being conceived and manufactured using our Product Lifecycle Management (PLM) software. We are seeking a Software Engineering Manager with a strong background in Java Spring Boot, AWS Cloud, Microservices and Angular to lead and manage development teams. The candidate should have understanding of AI The ideal candidate should have end-to-ended project management experience, the ability to provide technical leadership, and excellent communication skills for handling partners and multi-functional teams. Key Responsibilities: Lead and mentor development teams, providing guidance to achieve project goals. Foster a collaborative work environment, ensuring effective team communication. Conduct performance reviews, identify development needs, and provide ongoing coaching. Participate in the recruitment and hiring of new engineers. Oversee project management, including scope definition, delivery milestones, and timelines. Track project progress, present status updates, and identify risks with mitigation plans. Collaborate with product managers, product owners, architects, and partner teams to gather requirements and prioritize features. Ensure adherence to coding standards, best practices, and design principles. Provide technical guidance and expertise on complex design decisions. Maintain smooth communication with stakeholders, offering clear project status updates and addressing challenges proactively. Mandatory Requirements: 9 to 15 years of experience in software development and engineering management. Proven expertise in Java Spring Boot, AWS Cloud, Microservices, Angular, TypeScript, JavaScript, HTML, and CSS. Experience in working with Databases (SQL, NoSQL) and data structures Strong experience in leading and managing development teams. Ability to provide technical leadership and guidance to engineers. Excellent skills in cross-team communication, stakeholder management, and communicating complex technical concepts to diverse audiences. Strong problem-solving skills, with the ability to analyze issues, develop effective solutions, and make timely decisions. Good to Have: Experience with other cloud platforms like Azure and open-source cloud components. Knowledge of Docker & Kubernetes, Terraform, and Python ! Knowledge of modern data stack (ETL, data warehousing, analytics, and AI) Familiarity with AI/ML frameworks and tools Preferred Skills & Attributes: Ability to drive team performance, ensuring alignment with business objectives. Experience managing large-scale cloud-based applications. Strong understanding of Agile methodologies and project execution. Exceptional leadership, coaching, and team-building skills. Ability to work in fast-paced environments, handling multiple priorities effectively. 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, veteran status, or disability status. We are Siemens A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow! We offer a comprehensive reward package which includes a competitive basic salary, bonus scheme, generous holiday allowance, pension, and private healthcare. Siemens Software. ‘Transform the everyday' , #SWSaaS

Siemens Digital Industries Software is a leading provider of solutions for the design, simulation, and manufacture of products across many different industries. Formula 1 cars, skyscrapers, ships, space exploration vehicles, and many of the objects we see in our daily lives are being conceived and manufactured using our Product Lifecycle Management (PLM) software. We are seeking AI Backend Engineers to play a pivotal role in building our Agentic Workflow Service and Retrieval-Augmented Generation (RAG) Service. In this hybrid role, you'll leverage your expertise in both backend development and machine learning to create robust, scalable AI-powered systems using AWS Kubernetes, Amazon Bedrock models, AWS Strands Framework, and LangChain / LangGraph. Understanding of and expertise in: Design and implement core backend services and APIs for agentic framework and RAG systems LLM-based applications using Amazon Bedrock models RAG systems with advanced retrieval mechanisms and vector database integration Implement agentic workflows using technologies such as AWS Strands Framework, LangChain / LangGraph Design and develop microservices that efficiently integrate AI capabilities Create scalable data processing pipelines for training data and document ingestion Optimize model performance, inference latency, and overall system efficiency Implement evaluation metrics and monitoring for AI components Write clean, maintainable, and well-tested code with comprehensive documentation Collaborate with multiple multi-functional team members including DevOps, product, and frontend engineers Stay ahead of with the latest advancements in LLMs and AI agent architectures Minimum Experience Requirements 6+ years of total software engineering experience Backend Development Experience With Strong Python Programming Skills Experience in ML/AI engineering, particularly with LLMs and generative AI applications Experience with microservices architecture, API design, and asynchronous programming Demonstrated experience building RAG systems and working with vector databases LangChain/LangGraph or similar LLM orchestration frameworks Solid understanding of AWS services, particularly Bedrock, Lambda, and container services Experience with containerization technologies and Kubernetes Understanding of ML model deployment, serving, and monitoring in production environments Knowledge of prompt engineering and LLM fine-tuning techniques Excellent Problem-solving Abilities And System Design Skills Strong communication skills and ability to explain complex technical concepts Experience in Kubernetes, AWS Serverless Experience in working with Databases (SQL, NoSQL) and data structures Ability to learn new technologies quickly Preferred Qualifications: Must have AWS certifications - Associate Architect / Developer / Data Engineer / AI Track Must have familiarity with streaming architectures and real-time data processing Must have experience with ML experiment tracking and model versioning Must have understanding of ML/AI ethics and responsible AI development Experience with AWS Strands Framework Knowledge of semantic search and embedding models Contributions to open-source ML/AI projects 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, veteran status, or disability status. We are Siemens A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow! We offer a comprehensive reward package which includes a competitive basic salary, bonus scheme, generous holiday allowance, pension, and private healthcare. Siemens Software. ‘Transform the everyday' , #SWSaaS

Job Responsibilities : Work output Installation and maintenance of software tools. Use of software tools for process design, troubleshooting, revamp and what if studies. Critical analysis of plant data for model tuning purpose. Generate Heat & Material balances and equipment process data sheet. Carryout /check equipment design/revamp calculations. Support equipment installation. PIO review and participation in Root cause Analysis, Benchmarking etc. Support technology groups for chronic problem solving. Check calculations for hydraulics, utility networks, flare system design /analysis. Perform system engineering. Develop and use advanced tools for engineering analysis. Prepare document for sending enquiry document to LBEC. Review the technical offers and process design documents. Check preliminary economic analysis for OPEX, net contribution and CAPEX/EBITDA. Prepare SG2 and SG3 documents. Technology management Identify need for interactions with institutes/agencies for specialized model development. Perform discussions with vendors on relevant modelling tools. Attend vendor meetings, review technical bid evaluation documents and prepare recommendations. Initiate / propose software vendor interactions. Periodically update models Assess simulation tools Data Management Update data in process design, models and development of multiple projects and manage the same. Check internal technical reports Database Management on standard software available for improving process work. Ensure accurate records as per IPR requirements. HSE & other regulatory compliances Develop awareness of HSE procedures/ practices for related process design areas Ensure compliance with applicable local environmental site, statutory regulations affecting process design decisions Understand MSDS of chemicals being handled in a particular project. Participate in PSM activities. Participate in HAZOP / SIL studies / model review during progress of project Learning & mentoring Learn aspects of detailed process design and development Be conversant with design guidelines /codes /standards. Learn to model complex processes. Master all relevant models/chemical engineering thermodynamics Learn economic evaluation & financial aspects of PIOs/ new projects. Extra Mural Activities Draft / Review publications (paper/patent) and oral presentations. Read and assimilate technical articles from process design journals. Attend technical programmes. Education Requirement : Bachelor's degree in Chemical Engineering from a reputed university. Masters or Ph.D. preferred Experience Requirement : Minimum 5 years of experience out of which 2 years should be on using simulation software's. Knowledge of programming preferred. Skills & Competencies : Thorough understanding of chemical engineering principles Good analytical thinking, learning & problem solving Good communication, writing & presentation skills Ability to learn quickly any simulation software Ability to understand process plants Good in building & maintaining relationships

Siemens Digital Industries Software is a leading provider of solutions for the design, simulation, and manufacture of products across many different industries. Formula 1 cars, skyscrapers, ships, space exploration vehicles, and many of the objects we see in our daily lives are being conceived and manufactured using our Product Lifecycle Management (PLM) software. We are seeking Backend Engineers to play a pivotal role in building our Data & AI services Agentic Workflow Service and Retrieval-Augmented Generation (RAG) Service. In this hybrid role, you'll leverage your expertise in both backend development and AI knowledge and skills to create robust, scalable Data & AI services using AWS Kubernetes, Amazon Bedrock models. Expertise and understanding in: Backend development experience with strong Java programming skills along with basic Python programming knowledge Design and develop microservices with Java spring boot that efficiently integrate AI capabilities Experience with microservices architecture, API design, and asynchronous programming Experience in working with Databases (SQL, NoSQL) and data structures Solid understanding of AWS services, particularly Bedrock, Lambda, and container services Experience with containerization technologies, Kubernetes and AWS serverless Understanding of RAG systems with advanced retrieval mechanisms and vector database integration Understanding of agentic workflows using technologies such as AWS Strands Framework, LangChain / LangGraph Build scalable data processing pipelines for training data and document ingestion Write clean, maintainable, and well-tested code with comprehensive documentation Collaborate with multiple cross-functional team members including DevOps, product, and frontend engineers Stay current with the latest advancements in Data, LLMs and AI agent architectures Minimum Experience Requirements 4+ years of total software engineering experience Understanding building RAG systems and working with vector databases ML/AI engineering, particularly with LLMs and generative AI applications Awareness about LangChain/LangGraph or similar LLM orchestration frameworks Understanding of ML model deployment, serving, and supervising in production environments Knowledge of timely engineering Excellent problem-solving abilities and system design skills Strong communication skills and ability to explain complex technical concepts Ability to learn new technologies quickly Preferred Qualifications: Must have AWS certifications - Associate Architect / Developer / Data Engineer / AI Track Must have familiarity with streaming architectures and real-time data processing Must have developed, delivered and operated microservices on AWS Understanding of ML/AI ethics and responsible AI development Knowledge of semantic search and embedding models 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, veteran status, or disability status. We are Siemens A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow! We offer a comprehensive reward package which includes a competitive basic salary, bonus scheme, generous holiday allowance, pension, and private healthcare. Siemens Software.‘Transform the every day ' , #SWSaaS