What does a research engineer do?
Research engineers are responsible for conducting applied research and developing innovative solutions in their fields of expertise, such as technology, manufacturing, artificial intelligence, energy, aerospace, material science, and more. They bridge the gap between theoretical research and practical applications, working on cutting-edge projects that push the boundaries of technology and engineering.
These professionals work with the research and development (R&D) teams to prototype, test, and refine new technologies by creating and optimising processes, products, and systems.
The role of research engineers involves data modelling, data analysis, algorithm development, prototype testing, simulation, and performance evaluation to validate hypotheses. Depending on the industry, they may also contribute to software development, machine learning models, material innovation, or robotics.
Research engineers are also called R&D engineers, research scientists, development engineers, and innovation engineers.
Note that research engineers are different from systems engineers. While the former are more involved in the R&D phase, the latter focuses on designing and managing complex systems over their life cycles. Similarly, a software engineer is primarily involved in designing, developing, and maintaining software applications, whereas a research engineer is more focused on research and development of new technologies.
Job Description: Template
We’re seeking a detail-oriented research engineer to join our team at [Company X].
In this role, you will work on innovative research projects, design experiments, develop prototypes, and translate complex research into practical applications. You will collaborate with a multidisciplinary team, contribute to technical advancements, and play a crucial role in developing new technologies, products, or methodologies. The ideal candidate has a strong background in engineering, data analysis, and experimental research.
If you’re a problem-solver with a strong analytical mindset, excellent research skills, and expertise in your domain, we invite you to apply for the role. Along with an attractive remuneration package, we offer a collaborative work environment, professional growth opportunities, and employee benefits like health insurance, flexible work arrangements, and continuous learning programs.
Objectives of this role
- Conducting research, experiments, and simulations to develop new technology solutions.
- Analysing existing technologies and identifying opportunities for improvement or innovation.
- Developing algorithms, prototypes, simulations, and proof-of-concept models to validate research findings.
- Designing and executing experiments, collecting and analysing data to support conclusions.
- Collaborating with cross-functional teams, including engineers, data scientists, and product managers, to integrate research outcomes into practical applications.
- Analysing and interpreting data from experiments, identifying patterns and trends to refine solutions.
- Documenting research methodologies and technical reports for internal use and communicating findings to stakeholders, technical teams, and leadership.
- Assisting in securing funding for research projects through grant proposals and collaborations.
- Ensuring compliance with regulatory standards and company policies in research activities.
Your tasks
- Conduct feasibility studies, performance evaluations, and risk assessments for new technologies to define research objectives and develop experimental setups.
- Evaluate and select appropriate technologies, methodologies, and materials for hardware or software development.
- Use simulation tools, computational models, and statistical analysis for research validation.
- Work with software, hardware, or laboratory equipment teams to test, implement, and refine concepts.
- Optimise research methodologies to improve efficiency, accuracy, and reproducibility.
- Translate research insights into technical recommendations for product teams or business units.
- Develop and patent novel technologies or contribute to intellectual property development.
- Publish research findings in peer-reviewed journals, conferences, or technical whitepapers.
- Collaborate with academic institutions, industry partners, or external research organisations.
- Stay updated with industry trends, academic research, and emerging technologies relevant to the field.
Required skills and qualifications
- Master’s or Ph.D. in Engineering, Computer Science, Applied Sciences, Applied Mathematics, Physics, or a related field.
- 3+ years of experience in research, engineering, development, or equivalent academic research experience.
- Proficiency in programming languages (Python, C++, MATLAB) for computational research and data modelling.
- Hands-on experience with simulation tools, machine learning algorithms, or mathematical modelling.
- Working knowledge of AI/ML models, simulation tools, and data analytics platforms.
- Knowledge of research methodologies, documentation processes, and industry standards in the field of research.
- Knowledge of hardware/software integration, depending on research focus.
- Familiarity with cloud computing, high-performance computing, or embedded systems.
- Familiarity with machine learning frameworks such as TensorFlow or PyTorch.
- Strong analytical and problem-solving skills with experience in experimental design and data analysis.
- Excellent technical writing and communication skills for presenting research findings.
- Ability to work independently and as part of a collaborative research team.
- Passion for innovation and continuous learning.
Preferred skills and qualifications
- Experience in artificial intelligence, machine learning, internet of things, robotics, material science, energy systems, or other relevant domains based on industry focus.
- Publications in peer-reviewed journals or patents in relevant fields.
- Familiarity with research funding applications and grant writing.
- Knowledge of statistical modelling, optimisation algorithms, or numerical simulations.
- Experience in deep learning, computer vision, or natural language processing.
- Familiarity with software development practices and version control systems.
