Internship, Quantum Computing & Machine Learning

Company Description

Atomic Computing is an AWS Advanced Consulting Partner with a strong presence across North America, Europe, the Middle East, and Africa. The company has delivered more than 200 customer projects, helping organizations modernize using Managed Security Services, Generative AI, Dev Ops, Application modernization and cloud migration best practices. Atomic Computing supports clients throughout their cloud modernization journey, from initial assessments and workshops to workload migration and application development.

The team focuses on building scalable, secure, and innovative cloud solutions that accelerate business outcomes. Joining Atomic Computing means collaborating with experts in AWS and emerging technologies in a fast-evolving environment.

Role Description

This is an internship role in Quantum Computing & Machine Learning based in the Greater Delhi Area, structured as a hybrid position with a mix of on-site and work-from-home days. The intern will assist in researching quantum computing algorithms, quantum-inspired methods, and their applications to machine learning problems. Daily tasks may include running experiments on quantum simulators or available quantum hardware, preparing datasets, training and evaluating machine learning models, and documenting results.

The intern will support senior engineers and scientists in prototyping proof-of-concept solutions that could integrate with cloud-based services, including AWS. The role also involves reviewing academic literature, contributing to internal knowledge-sharing sessions, and preparing concise reports, notebooks, or presentations to communicate findings to technical and non-technical stakeholders.

Qualifications

Foundational knowledge of quantum computing concepts (e.g., qubits, gates, circuits) and familiarity with at least one quantum SDK (such as Qiskit, Cirq, or Braket) is strongly preferred.
Solid understanding of core machine learning principles (e.g., supervised and unsupervised learning, model evaluation) and hands-on experience with Python-based ML frameworks such as scikit-learn, Tensor Flow, or PyTorch.
Proficiency in Python programming, scientific computing libraries (Num Py, pandas), and basic software engineering practices such as version control (Git) and reproducible workflows.
Strong analytical, mathematical, and problem-solving skills, ideally with coursework or experience in linear algebra, probability, optimization, or related areas.
Ability to read and summarize technical research papers, design small-scale experiments, and clearly communicate findings in written and verbal form.
Currently pursuing or recently completed a degree in Computer Science, Physics, Mathematics, Engineering, or a related quantitative field.
Interest in cloud computing (AWS exposure is a plus), high-performance computing, and applying emerging technologies to real-world business challenges.
Comfort working in a hybrid environment, collaborating with distributed teams, and managing time effectively across academic and internship commitments.