Qureos Mentor

DGi WORX

<ul><li>Concepts: qubits, superposition, measurement, Bloch sphere, single/two-qubit gates, circuits.</li><li>Parameterized circuits (VQCs): building, initializing, and training with PyTorch.</li><li>Core algorithms: QAOA, VQE, quantum kernels (QSVM), QCNN at a basic level.</li><li>Noise &amp; NISQ reality: shots, error rates, mitigation basics; sim vs real hardware trade-offs.</li><li>Transpilation &amp; resources: depth, width, fidelity, run-time/credit estimation.</li><li>Tooling: Qiskit or PennyLane (one solid), plus ability to run on IBM/ IonQ simulators; MLflow/W&amp;B for reproducibility.</li></ul>Nice-to-have<ul><li>OR/optimization (OR-Tools), graph problems; OCR/NLP pipelines; pgvector/FAISS.</li><li>Basic Docker &amp; FastAPI to expose prototypes.</li></ul>What you&rsquo;ll do<ul><li>Clean &amp; prep data (SQL, Pandas/Polars); build baseline ML (sklearn/XGBoost, PyTorch).</li><li>Prototype small QML pilots (Qiskit/PennyLane): simple variational circuits, quantum kernels.</li><li>Compare classical vs hybrid results; document metrics, costs, and trade-offs.</li><li>Package models (notebooks &rarr; FastAPI/batch), write tests, and monitor basics.</li></ul>Must-haves<ul><li>1&ndash;2 yrs in ML (or strong projects), solid Python, SQL, Git.</li><li>Hands-on with sklearn + at least basic PyTorch.</li><li>Exposure to Qiskit or PennyLane and parameterized circuits (coursework/projects okay).</li><li>Clear communication and reproducible work (MLflow/W&amp;B or similar a plus)</li></ul>Job Types: Full-time, Permanent, Fresher, Internship Contract length: 6 monthsPay: From &#8377;10,000.00 per monthWork Location: In person

ML Engineer (Quantum)

Join DGi WORX and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

DGi WORX

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ML Engineer (Quantum)