Midjourney

<h3>What you’ll do</h3><ol><li><p>Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy.</p></li><li><p>Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements.</p></li><li><p>Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks.</p></li><li><p>Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation.</p></li><li><p>Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes.</p></li></ol><h3>What we’re looking for</h3><ul><li><p>Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains.</p></li><li><p>Ability to move fluidly between research prototypes and production-quality systems.</p></li><li><p>Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility.</p></li><li><p>A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.)</p></li></ul><h3>Useful experience</h3><ul><li><p>ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints.</p></li><li><p>Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts.</p></li><li><p>A background in computational physics or scientific computing.</p></li><li><p>Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging.</p></li><li><p>Experience in Agentic-SciML is a plus.</p></li><li><p>Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines.</p></li><li><p>Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).</p></li></ul>

Principal Machine Learning Engineer (Reconstruction / Quantitative Imaging)

<h3>What you’ll do</h3><ol><li><p>Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably.</p></li><li><p>Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls.</p></li><li><p>Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility.</p></li><li><p>Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews.</p></li><li><p>Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet.</p></li></ol><h3>What we’re looking for</h3><ul><li><p>Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability.</p></li><li><p>Experience shipping production systems that handle large data volumes and failure-prone networks.</p></li><li><p>Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments.</p></li></ul><h3>Useful experience</h3><ul><li><p>Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability.</p></li><li><p>Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails.</p></li><li><p>Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks.</p></li><li><p>Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.</p></li></ul>

Midjourney

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Principal Machine Learning Engineer (Reconstruction / Quantitative Imaging)

Senior Cloud / Data Engineer (Data / Reconstruction / HIPAA)

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