Applied Scientist I

Amazon’s interview process typically starts with an online coding assessment, followed by a technical phone screen focusing on data structures, algorithms, and core ML concepts. Successful candidates are invited to an onsite loop of 4–5 interviews covering coding, system design, research depth, and behavioral questions (Leadership Principles). The difficulty is high, demanding strong problem‑solving speed and clear communication. Preparing with mock interviews, reviewing ML fundamentals, and practicing behavioral storytelling are key to success.

Amazon’s work culture emphasizes customer obsession, ownership, and a bias for action. Employees enjoy rapid career growth, exposure to large‑scale problems, and a supportive environment that encourages continuous learning and innovation.

Minimum B.Tech/M.Tech/Ph.D. in Computer Science, Electrical Engineering, Mathematics, Statistics or related fields; CGPA 7.0/10 or equivalent; graduating batch 2024‑2026; no active backlogs; strong foundation in machine learning, deep learning, NLP or computer vision; proficiency in at least one programming language (Python, C++, Java).

Round 1: Online assessment (coding & ML fundamentals) → Round 2: Technical phone screen (algorithmic coding + ML concepts) → Round 3: Onsite interviews (4 rounds: coding, system design, research discussion, behavioral) → HR round

Amazon is a global technology leader headquartered in Seattle, with a massive presence in India across e‑commerce, cloud services (AWS), digital streaming, and artificial intelligence. The company’s mission – to be Earth’s most customer‑centric place – drives relentless innovation, massive scale, and a culture of ownership. In India, Amazon employs hundreds of thousands of people, offering opportunities that span product development, operations, research, and more. Its AI and Machine Learning teams are at the forefront of building services that power Alexa, Amazon Go, AWS AI services, and countless customer‑facing features. The Applied Scientist I role sits within Amazon’s AWS AI division, focusing on Speech and Language technologies. As an early‑career researcher‑engineer, you will collaborate with world‑class scientists and engineers to push the boundaries of Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Translation (MT), Text‑to‑Speech (TTS), and Dialog Management. You will have access to Amazon’s massive, heterogeneous data sets—audio recordings, transcriptions, structured logs—and world‑class compute infrastructure, enabling rapid experimentation and large‑scale model deployment. Key responsibilities: - Design and implement novel algorithms for ASR, NLU, MT, TTS, and Dialog Management. - Conduct rigorous research, publish findings internally, and contribute to top‑tier conferences when possible. - Build and optimize large‑scale training pipelines on distributed systems such as Spark and Hadoop. - Develop end‑to‑end prototypes that integrate with AWS services and Amazon products. - Perform error analysis on real‑world speech and text data to drive iterative improvements. - Collaborate cross‑functionally with product managers, software engineers, and data scientists to translate research into production‑ready features. - Write high‑quality code in Python, C++ or Java, adhering to Amazon’s engineering standards. - Mentor interns and junior team members, fostering a culture of knowledge sharing. - Contribute to the AI community within Amazon through internal talks, code reviews, and documentation. Tech stack: Python, PyTorch/TensorFlow, CUDA, Spark, Hadoop, AWS SageMaker, Docker/Kubernetes, Git, Linux, and familiarity with large language model architectures. Growth path: Successful Applied Scientists can progress to Senior Applied Scientist, Principal Scientist, and eventually Distinguished Scientist roles, with opportunities to lead teams, own product roadmaps, and influence Amazon’s AI strategy globally. Why join Amazon? You will work on problems that impact millions of customers worldwide, receive mentorship from industry pioneers, enjoy a compensation package that includes competitive salary, RSUs, and benefits, and be part of a culture that prizes invention, bias for action, and customer obsession.