Whether you are a student or professional, you can make your way into deep tech by landing the right internship. These programmes not only offer you a chance to sharpen your resume and make connections but also to learn how a large organisation or a start-up works. Not all internships are equal, especially when it comes to deep technology companies. Here are some factors to consider:
Interest and values alignment: This is one of the most important decisions when choosing an internship. It is more likely that you will put in more effort if you really care about what you are doing. Therefore, look at the company’s vision and focus area, the problem being solved, and whether there are any innovative and exciting projects in the pipeline.
Team, resources and partners: Do a thorough background check on the company and the people you will be working with. Sometimes it is better to work with companies who have already proven their technology. Access to capital, labs or partners for research and development should also be considered.
Role and work: Deep tech companies can have a long period of research before the product is ready for the market (“gestation period”). Knowing your specific job responsibilities in advance can make an internship more aligned with your expectations. Focus on skills that will be useful in the future, not just things you want to learn or want an employer to know. If you are looking for Machine Learning internships, ensure the company does end-to-end model creation and deployment, rather than employing a Data Science team that does the Maths. This will give you hands-on experience with model creation, validation and deployment.
Key interview skills
Remember, internships are not just about getting your foot into the door but also about learning and gaining experience. The most obvious approach is to highlight the contributions and insights that you made during your internship. Artefacts, patents, publications or systems built by the intern or references from an internship go a long way in demonstrating the aptitude for the work and ability to come up to speed and contribute quickly.
The next step is to describe why the work was impressive and who benefited from it. What motivated you to pursue the work and what was your role in completing it? If you did not make significant contributions, then you must show that you had great ideas or insights that led to new directions for exploration or research. If you did a lot of work that didn't result in a product or publication, focus on the work that was most impressive within the context of your internship. Last, people hire for culture fit, so show that you belong.
Whether it is a large/small company or a start-up, deep tech requires a plethora of skills, which can be gained through hands-on experience. So keep your eyes open for opportunities and learn as much about the field as possible.
The writer is head of Engineering, Drishti
