Job Description
We are looking for a Senior Mechanical Engineering Research and Design Engineer to play a crucial role in developing and enhancing the Applix AI Copilot. The ideal candidate will bring a unique blend of mechanical engineering expertise, systems thinking, and enthusiasm for AI-driven design optimization. You will work closely with our interdisciplinary team to research, implement, and refine cutting-edge design optimization techniques and models.
Responsibilities:
• Contribute to the development and improvement of AI-driven design optimization algorithms for mechanical systems.
• Apply and enhance Design for X (DFx) principles within the Applix AI Copilot platform, focusing on manufacturability, assembly, quality, performance, and cost.
• Implement and refine Failure Mode and Effects Analysis (FMEA) methodologies in our AI-driven quality control processes.
• Research and integrate state-of-the-art mechanical design optimization techniques into our platform.
• Collaborate with cross-functional teams (AI engineers, software developers, UX designers) to enhance the Applix AI Copilot's capabilities and user experience.
• Analyze complex manufacturing data to identify patterns and opportunities for optimization.
• Develop and maintain documentation for design optimization models and processes.
• Contribute to the continuous learning and improvement of our AI system by providing domain expertise and feedback.
• Identify and analyze defects at both production and post-production stages, conducting comprehensive Root Cause Analysis (RCA).
• Examine and interpret diverse data points from various sources, including production inspections, warranty recall data, user complaints, telemetry data, and information from IoT devices, CRM, ERP, and MES systems.
• Develop and implement predictive analytics models to identify potential defects before they occur.
• Create prescriptive models that recommend actions to prevent predicted defects.
• Continuously refine and improve defect prediction and prevention models based on new data and insights.
Requirements:
• Master's or Ph. D. in Mechanical Engineering or a related field.
• 5+ years of experience in mechanical design, with a focus on design optimization and manufacturing processes.
• Strong understanding of DFx principles, including Design for Manufacturing (DFM) and Design for Assembly (DFA).
• Expertise in FMEA and other quality control methodologies in manufacturing.
• Experience with CAD/CAM/CAE software and simulation tools.
• Proven experience in defect analysis and root cause identification in manufacturing environments.
• Strong background in data analysis and interpretation, particularly with diverse data sources relevant to manufacturing and product lifecycle.
• Experience with predictive and prescriptive analytics, preferably in a manufacturing or engineering context.
• Familiarity with machine learning and AI concepts, particularly as applied to engineering design.
• Strong analytical and problem-solving skills, with the ability to think critically about complex systems.
• Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Preferred:
• Experience with programming languages such as C++, Python, and MATLAB for data analysis and model development.
• Knowledge of Industry 4.0 concepts and technologies.
• Familiarity with cloud computing platforms and big data technologies.
• Experience with additive manufacturing technologies and processes.
• Track record of publications or patents in the field of design optimization or AI-driven manufacturing.
• Familiarity with IoT technologies and their application in manufacturing.
• Experience working with CRM, ERP, and MES systems, and ability to integrate data from these sources for comprehensive analysis.
• Knowledge of statistical process control (SPC) and its application in defect prevention.
• Experience with data visualization tools to effectively communicate complex data insights.
• Passionate about the intersection of AI and mechanical engineering.
• Enthusiastic team player with the ability to work in a fast-paced, innovative environment.
• Self-motivated learner, always eager to explore new technologies and methodologies.
• Creative problem-solver, able to think outside the box to address complex engineering challenges.
• Adaptable and resilient, comfortable with the uncertainties of cutting-edge technology development.
• Detail-oriented with a strong ability to see both the big picture and granular details in complex systems and data sets.
Responsibilities:
• Contribute to the development and improvement of AI-driven design optimization algorithms for mechanical systems.
• Apply and enhance Design for X (DFx) principles within the Applix AI Copilot platform, focusing on manufacturability, assembly, quality, performance, and cost.
• Implement and refine Failure Mode and Effects Analysis (FMEA) methodologies in our AI-driven quality control processes.
• Research and integrate state-of-the-art mechanical design optimization techniques into our platform.
• Collaborate with cross-functional teams (AI engineers, software developers, UX designers) to enhance the Applix AI Copilot's capabilities and user experience.
• Analyze complex manufacturing data to identify patterns and opportunities for optimization.
• Develop and maintain documentation for design optimization models and processes.
• Contribute to the continuous learning and improvement of our AI system by providing domain expertise and feedback.
• Identify and analyze defects at both production and post-production stages, conducting comprehensive Root Cause Analysis (RCA).
• Examine and interpret diverse data points from various sources, including production inspections, warranty recall data, user complaints, telemetry data, and information from IoT devices, CRM, ERP, and MES systems.
• Develop and implement predictive analytics models to identify potential defects before they occur.
• Create prescriptive models that recommend actions to prevent predicted defects.
• Continuously refine and improve defect prediction and prevention models based on new data and insights.
Requirements:
• Master's or Ph. D. in Mechanical Engineering or a related field.
• 5+ years of experience in mechanical design, with a focus on design optimization and manufacturing processes.
• Strong understanding of DFx principles, including Design for Manufacturing (DFM) and Design for Assembly (DFA).
• Expertise in FMEA and other quality control methodologies in manufacturing.
• Experience with CAD/CAM/CAE software and simulation tools.
• Proven experience in defect analysis and root cause identification in manufacturing environments.
• Strong background in data analysis and interpretation, particularly with diverse data sources relevant to manufacturing and product lifecycle.
• Experience with predictive and prescriptive analytics, preferably in a manufacturing or engineering context.
• Familiarity with machine learning and AI concepts, particularly as applied to engineering design.
• Strong analytical and problem-solving skills, with the ability to think critically about complex systems.
• Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Preferred:
• Experience with programming languages such as C++, Python, and MATLAB for data analysis and model development.
• Knowledge of Industry 4.0 concepts and technologies.
• Familiarity with cloud computing platforms and big data technologies.
• Experience with additive manufacturing technologies and processes.
• Track record of publications or patents in the field of design optimization or AI-driven manufacturing.
• Familiarity with IoT technologies and their application in manufacturing.
• Experience working with CRM, ERP, and MES systems, and ability to integrate data from these sources for comprehensive analysis.
• Knowledge of statistical process control (SPC) and its application in defect prevention.
• Experience with data visualization tools to effectively communicate complex data insights.
• Passionate about the intersection of AI and mechanical engineering.
• Enthusiastic team player with the ability to work in a fast-paced, innovative environment.
• Self-motivated learner, always eager to explore new technologies and methodologies.
• Creative problem-solver, able to think outside the box to address complex engineering challenges.
• Adaptable and resilient, comfortable with the uncertainties of cutting-edge technology development.
• Detail-oriented with a strong ability to see both the big picture and granular details in complex systems and data sets.
💡 Quick Summary
Seeking a career-building opportunity? The Senior Mechanical Research Engineer position is now open for candidates interested in the Work from home Jobs sector. This role in Jaipur offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Work from home Jobs is a plus.
