Research Intern, AI

SHL’s interview process typically starts with a timed online coding test focusing on data structures, algorithms, and Python basics. Successful candidates move to a technical interview where they discuss past AI/ML projects, solve case‑based problems, and answer theory questions on deep learning. The final HR round assesses cultural fit, communication skills, and internship logistics. Preparation should include strong coding practice, clear articulation of research work, and familiarity with SHL’s AI products.

SHL promotes a collaborative and inclusive environment where employees are encouraged to experiment and share ideas. The company offers flexible work hours, regular learning sessions, and a strong focus on work‑life balance, allowing interns to grow both professionally and personally.

Final year or recent graduate (2024‑2026) of B.Tech/M.Tech/M.Sc in Computer Science, Electrical Engineering, Information Technology, Data Science or related fields; Minimum 60% aggregate (or CGPA 6.5/10); Strong programming skills in Python; No active backlogs; Ability to commit full‑time for 3‑6 months.

Round 1: Online coding assessment (DSA and Python) → Round 2: Technical interview (AI/ML concepts, project discussion) → Round 3: HR interview (fit, availability, expectations)

SHL, a global leader in people science, has been helping organisations make smarter talent decisions for over four decades. With a portfolio that spans psychometric assessments, talent analytics, and AI‑driven insights, SHL combines deep research with cutting‑edge technology to unlock human potential. The company’s culture is built around diversity, continuous learning, and a strong emphasis on scientific rigor, making it an attractive destination for aspiring data and AI professionals. As a Research Intern in AI, you will be immersed in a high‑impact environment where research meets product development. Working side‑by‑side with SHL’s AI team, you will tackle real‑world challenges in natural language processing, speech/audio analysis, and computer vision. The internship is designed to give you hands‑on exposure to the entire AI lifecycle – from data collection and model prototyping to deployment and performance monitoring – with a clear pathway to a full‑time Research Engineer role based on performance. **Key Responsibilities** 1. Design, develop, and fine‑tune deep learning models for NLP, speech, and vision tasks. 2. Prototype generative AI solutions such as large language models (LLMs), Retrieval‑Augmented Generation (RAG), and multimodal architectures. 3. Assist in building end‑to‑end AI pipelines, including data ingestion, annotation, and validation. 4. Implement orchestration frameworks (e.g., Docker, Kubernetes) and monitoring tools to ensure model reliability. 5. Collaborate with product managers and engineers to integrate AI models into production services. 6. Conduct experiments, analyse results, and document findings for internal research papers. 7. Contribute to code reviews, testing, and best‑practice documentation. 8. Stay updated with the latest AI research trends and propose innovative solutions. 9. Participate in weekly knowledge‑sharing sessions and hackathons within the AI team. 10. Support the creation of technical demos and presentations for stakeholders. **Tech Stack**: Python, PyTorch, TensorFlow, Hugging Face Transformers, Keras, Docker, Kubernetes, Git, SQL/NoSQL, Linux, Jupyter notebooks, and cloud platforms (AWS/GCP). **Growth Path**: Successful interns are often offered a full‑time Research Engineer position, with opportunities to lead AI projects, publish in top conferences, and mentor future interns. SHL’s emphasis on continuous learning means you will have access to internal workshops, external courses, and conferences. **Why Join SHL?** The internship offers a rare blend of academic research and product‑centric engineering, exposure to a global client base, and mentorship from seasoned AI scientists. You will be part of a transformative journey that shapes the future of work while building a strong foundation for a career in AI research and development.