Life @ESPL At ESPL, we believe continuous learning is key to staying ahead in the ever-evolving world of technology. Being a growing mid-sized organization, we offer opportunities for our employees at every level of their expertise and journey with us. We ensure our employees grow systematically through our training programs that foster that growth. Unity in diversity: Young and dynamic professionals with passion for engineering form the ESPL team. With focus on innovation and growth, ESPL family as a whole has strived through different challenges. We appreciate our team for their contribution and dedication. Technical competence is basic requirement of CAE domain and we ensure that our team is well acquainted with latest technical trends in the business. We have developed comprehensive training programs for our team for developing Technical know- how, Soft skills, Leadership development and Data security awareness. Work Culture We support multi-continental customers. It is always interesting to know different work cultures from different regions and we like to implement the best from each in our team. Professionalism and commitment are the key values at the core of ESPL team. We ensure development of our employee’s professional career by providing long term opportunities to work on challenging tasks, developing expertise required for the execution and maintaining work- life balance in a supportive and approachable manner. Various team bonding activities ensures that at the end we stand strong together as one unit. Knowledge sharing and communication plays a vital role in development of each and every person individually as well as in a team. Why Work with ESPL We are committed to delivering comprehensive virtual engineering solutions from concept to prototype. Our team of skilled engineers resonates with this objective and stays at the core of every project. Here’s what makes ESPL a great place for engineers. Advanced Engineering Challenges Addressing and resolving engineering challenges is one of the factors defining our existence. With us, you will have the opportunity to solve complex problems in fields like Model-Based System Engineering (MBSE), AI-driven Data Engineering, and E-Powertrain development for global automotive brands. Are you game for it? Professional Development We prioritize continuous learning to keep our engineers at the forefront of technology and innovation. That’s one reason our engineers consistently deliver competent solutions. Collaborative Culture At ESPL, we value collaborations and nurture a culture that drives inter-team collaborations. We boast a team-oriented workplace where you get the opportunity to work with top and seasoned engineers. Please send your profile at [email protected] Data Science Researcher Key Responsibilities Develop and implement machine learning algorithms, including neural networks, to optimize mechanical engineering processes and predict system behaviors. Use Python programming and libraries (such as TensorFlow, PyTorch, SciPy, pandas) to design and test machine learning models for Finite Element / Finite Volume simulations. Collaborate with mechanical engineering teams to integrate data-driven solutions into product designs and simulations. Analyze large datasets from simulations, experiments, and real-world systems to derive meaningful insights for design optimization and predictive maintenance. Build and fine-tune predictive models to improve the accuracy and performance of engineering products. Conduct data pre-processing, feature engineering, and model validation to ensure high-quality results. Prepare reports and visualizations to communicate complex findings to technical and non-technical stakeholders. Stay updated with the latest advancements in machine learning and data science, particularly as they apply to mechanical engineering. Qualifications Experience: 3-5 years of experience in data science or machine learning, with a strong background in mechanical engineering or a related field. Education: Master’s degree in Mechanical Engineering, Data Science, Applied Mathematics, or a related discipline. PhD Candidates are welcomed. Technical Skills: Proficiency in Python programming and machine learning libraries such as TensorFlow, Keras, PyTorch, and Scikit-learn. Strong understanding of neural networks, deep learning, and machine learning algorithms. Knowledge of mechanical engineering concepts, such as structural mechanics, thermodynamics, or fluid dynamics. Familiarity with data manipulation and visualization tools (e.g., pandas, NumPy, matplotlib, seaborn).
**Job Description** At ESPL, continuous learning is emphasized to help you stay ahead in the ever-evolving world of technology. As a growing mid-sized organization, opportunities are offered for employees at every level of expertise. Training programs are in place to ensure systematic growth, fostering development in technical knowledge, soft skills, leadership, and data security awareness. - Perform multi-body dynamics (MBD) simulations using Simpack or Adams to analyze mechanical systems" behavior. - Develop, test, and validate dynamic models of complex mechanical systems. - Conduct system-level analysis to enhance performance and durability. - Analyze simulation results, identify improvements, and provide recommendations. - Prepare detailed technical reports and presentations for clients and stakeholders. **Qualifications** - Experience: 3-5 years in relevant field - Education: Bachelors or Masters in Mechanical Engineering or Automotive Engineering - Technical Skills: - Proficiency in Simpack or Adams for MBD simulations - Strong understanding of mechanical system dynamics - Experience with system-level simulations for automotive or machinery systems - Familiarity with model validation and optimization techniques At ESPL, professionalism, commitment, and teamwork are valued. Development of employees" professional careers is supported through long-term opportunities for challenging tasks, expertise development, and maintaining work-life balance. Various team bonding activities ensure a strong unit. Collaboration, knowledge sharing, and communication play vital roles in individual and team development. If you are ready for advanced engineering challenges and wish to work in a collaborative culture that focuses on professional development, send your profile to HR@eqmsol.com.,
As a NVH/Durability Analyst at ESPL, your role will involve conducting NVH and durability simulations using Abaqus, Nastran, and other industry-standard software. You will collaborate with design, engineering, and testing teams to optimize product designs for noise reduction, durability, and vibration minimization. Additionally, you will be responsible for providing detailed documentation, reports, and presentations to effectively communicate findings and recommendations to project stakeholders. Qualifications required for this role include: - Experience: 3-5 years of experience in NVH and durability analysis, preferably in automotive, aerospace, or related fields. - Education: Bachelors or Masters degree in Mechanical Engineering, Automotive Engineering, or a related discipline. Key Responsibilities: - Conduct NVH and durability simulations using Abaqus, Nastran, and other industry-standard software. - Collaborate with design, engineering, and testing teams to optimize product designs for noise reduction, durability, and vibration minimization. - Provide detailed documentation, reports, and presentations to communicate findings and recommendations to project stakeholders. Technical Skills required for this role: - Proficiency in Abaqus and Nastran for NVH and durability simulations. - Strong understanding of structural mechanics, dynamics, and fatigue analysis. - Experience with pre- and post-processing tools (such as HyperMesh, ANSA, or similar). At ESPL, we believe in continuous learning and growth, offering comprehensive training programs to enhance technical know-how, soft skills, leadership development, and data security awareness. The work culture at ESPL emphasizes professionalism, commitment, and a supportive environment that encourages career development and work-life balance. Team bonding activities and knowledge sharing initiatives ensure a cohesive and collaborative workplace where individual and team development are paramount. ESPL is committed to delivering comprehensive virtual engineering solutions and offers engineers the opportunity to work on advanced engineering challenges in fields like Model-Based System Engineering (MBSE), AI-driven Data Engineering, and E-Powertrain development for global automotive brands. Professional development is a priority at ESPL, with a focus on continuous learning to stay at the forefront of technology and innovation. The company fosters a collaborative culture that values inter-team collaborations and provides the opportunity to work with top and seasoned engineers. If you are ready to take on complex engineering challenges, prioritize professional development, and thrive in a collaborative culture, we invite you to send your profile to HR@eqmsol.com for consideration.,