Applied Scientist I

Amazon's interview process typically starts with an online coding assessment followed by one or two technical phone screens. Successful candidates are invited to an onsite loop consisting of 4–5 back‑to‑back interviews covering data structures, system design, and research depth. The difficulty is high, with a strong emphasis on problem‑solving, clear communication, and leadership principles. Practicing coding problems and articulating research contributions are key to success.

Amazon promotes a fast‑paced, data‑driven environment where engineers are encouraged to experiment and iterate quickly. Employees benefit from clear career ladders, mentorship programs, and the ability to work on products that impact millions globally, while maintaining a focus on work‑life balance through flexible work arrangements.

Bachelor's or Master's degree in Computer Science, Electrical Engineering, Mathematics, or related fields (PhD preferred). Minimum 60% aggregate or CGPA 6.0/10. Eligible batch years: 2025, 2026, 2027. No active backlogs at the time of application. Strong academic record in algorithms, statistics, and machine learning is essential.

Round 1: Online assessment (coding & ML fundamentals) → Round 2: Technical phone screen (algorithmic & system design) → Round 3: Onsite loop (multiple technical interviews covering research, coding, and system design) → Round 4: HR discussion (fit and compensation)

Amazon, founded in 1994, has grown from an online bookstore to a global technology powerhouse with operations in e‑commerce, cloud computing (AWS), digital streaming, and artificial intelligence. In India, Amazon employs over 100,000 people across major cities, driving innovation in logistics, retail, and cloud services. The company’s culture emphasizes customer obsession, long‑term thinking, and a bias for action, making it a fertile ground for engineers who want to solve real‑world problems at massive scale. The Applied Scientist I role sits within the Amazon Web Services (AWS) AI team, focusing on Speech and Language technologies. As an entry‑level research‑oriented position, you will collaborate with senior scientists, software engineers, and product managers to design, prototype, and ship novel algorithms that power automatic speech recognition (ASR), natural language understanding (NLU), machine translation, text‑to‑speech, and related computer‑vision applications. Your work will directly influence products used by millions of customers worldwide, from Alexa voice assistants to AWS AI services. Key Responsibilities: 1. Design and implement state‑of‑the‑art machine‑learning models for speech and language tasks. 2. Conduct experiments on large‑scale heterogeneous data (audio, text, structured logs) using AWS compute resources. 3. Publish research findings internally and, where appropriate, in top‑tier conferences. 4. Optimize model training and inference pipelines for latency, scalability, and cost efficiency. 5. Collaborate with cross‑functional teams to integrate research prototypes into production services. 6. Develop evaluation metrics and benchmarking suites to track model performance. 7. Contribute to open‑source tools and internal libraries (TensorFlow, PyTorch, SageMaker). 8. Mentor interns and junior team members on best practices in ML research. 9. Stay abreast of emerging trends in NLP, ASR, and computer vision, proposing new research directions. 10. Participate in code reviews and ensure adherence to Amazon’s engineering standards. Tech Stack: Python, C++, TensorFlow, PyTorch, AWS SageMaker, Spark, Hadoop, Docker, Kubernetes, and various NLP/ASR toolkits (Kaldi, ESPnet). The role offers a clear growth path—from Applied Scientist I to Senior, Principal, and eventually Distinguished Scientist—providing opportunities to lead large research programs and influence Amazon’s AI roadmap. Joining Amazon means access to unparalleled data, compute resources, and a culture that rewards bold ideas, making it an ideal launchpad for aspiring researchers who want to make a global impact.