AI Researcher

As an AI Researcher at Cognizant, you'll assist in identifying impactful research problems, design new technologies to solve them, and implement these technologies for evaluation against various benchmarks. You'll also be responsible for presenting your findings to stakeholders and the scientific community and assisting with the integration of these technologies into the LEAF platform. Collaboration in a fast-paced environment with your team members will be essential to achieving success.

To be eligible for the AI Researcher position at Cognizant, you will need a PhD in a relevant field such as Artificial Intelligence, Data Science, Computer Science, Statistics, or Engineering. Additionally, demonstrated research experience in these fields and familiarity with programming languages like Python, along with frameworks such as Tensorflow or PyTorch, are crucial for applying. Strong communication skills and attention to detail are also highly valued.

At Cognizant, we promote an ego-free work environment that prioritizes intellectual curiosity, creativity, and collaboration. As an AI Researcher, you can expect to work in a setting that celebrates innovation, encourages innovative thinking, and values contributions from all team members. This supportive culture fosters personal and professional growth, making it exciting to be part of our team.

Unfortunately, the AI Researcher position at Cognizant is not able to offer visa transfer or sponsorship at this time. However, applicants currently residing in Texas or those who can independently arrange their relocation are encouraged to apply and become part of our dynamic team.

Cognizant offers a comprehensive benefits package for the AI Researcher position, which includes Medical, Dental, Vision, and Life Insurance, paid holidays, Paid Time Off, a 401(k) plan with contributions, long-term and short-term disability coverage, paid parental leave, and an Employee Stock Purchase Plan, all subject to eligibility requirements.

When answering this question, detail specific projects you've worked on related to AI or machine learning. Highlight the methodologies you used, the challenges you faced, and the outcomes of your research. This demonstrates your capability and how your experience aligns with the responsibilities of an AI Researcher at Cognizant.

Discuss your proficiency with languages like Python and libraries such as Tensorflow or PyTorch. Explain why you prefer these tools, possibly citing their functionality or efficiency in your past projects. Show that you are adaptable and eager to learn new technologies as well.

Showcase your thought process for identifying research problems that matter. Mention how you conduct literature reviews, engage with industry trends, or consult with stakeholders. Your answer should reflect your analytical thinking and ability to align research with real-world needs.

Describe your step-by-step approach to developing a machine learning model, starting from data collection to preprocessing, selecting algorithms, training the model, and evaluating its performance. Highlight any project illustrating your ability to turn theoretical models into practical applications while engaging in iterative improvements.

Discuss the importance of explainability in AI; emphasized how it builds trust, ensures accountability, and enhances user acceptance. Provide examples from your experience where explainability affected stakeholder decisions or user interactions with AI systems.

Mention specific journals, conferences, or online courses you follow for AI advancements. Highlight your engagement in forums or communities related to AI, demonstrating your dedication to continuous learning and professional development.

Use the STAR method (Situation, Task, Action, Result) to describe a challenging situation in your research. Focus on how you approached the problem, the solutions you implemented, and what you learned from the experience. This illustrates your problem-solving skills and resilience.

Discuss your strategies for integration, emphasizing the importance of thorough testing, documentation, and ensuring compatibility. Describe experiences from past projects where you successfully integrated new technologies into platforms or products.

Explain the significance of collaboration in your work, from gathering diverse insights to verifying findings. Share experiences where teamwork led to innovative solutions, emphasizing your capability to work effectively in a collaborative environment like Cognizant.

Discuss the importance of ethics in AI, touching on biases, fairness, and the societal impact of AI technologies. Point out how you incorporate ethical considerations into your research and model design, underscoring your commitment to responsible AI practices.