Industry: Computers and Electronics Manufacturing
Company Size: 11-50 employees

Superlinear Computing

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Superlinear Computing · Palo Alto, CA · Full-time

Superlinear Computing is a quantum research and infrastructure company headquartered in Palo Alto. We design, deploy, and operate on-premises superconducting QPU systems, apply machine learning to characterize quantum system behavior, and translate those findings into specialized hardware products.

We work at the frontier of quantum hardware and real-world applications, giving researchers, enterprises, and government partners access to quantum capabilities that were previously out of reach. We believe the transition to quantum computing will be defined not just by the machines themselves, but by the infrastructure built around them.

**The Role **

This is the physics role at Superlinear Computing. You will own the physical understanding of every system we operate or build, including superconducting QPUs today, and of entropy sources spanning optical and semiconductor hardware, as our roadmap develops. You work alongside our electronics engineers, setting the physical parameters and theoretical foundations for their implementations. The role is senior, independent, and self-directed. The scope grows with the company.

- Own QPU performance across all systems: calibration, characterization, benchmarking, and diagnosis

- Investigate hardware at the physics level, coherence dynamics, noise sources, gate error mechanisms

- Design and validate entropy sources across hardware modalities: optical, semiconductor, and superconducting

- Define physical figures of merit and characterization targets for ML-driven analysis of quantum output streams

- Collaborate with electronics and software engineers on calibration automation and system integration

- Surface and pursue research directions that emerge from operating real hardware across all system types

**Required **

- PhD in experimental physics or quantum engineering

- Hands-on superconducting qubit characterization: spectroscopy, Rabi, Ramsey, T₁/T₂, randomized benchmarking, two-qubit gate tune-up

- Working knowledge of microwave measurement: IQ mixing, heterodyne readout, pulse shaping

**Preferred **

- Dilution refrigerator experience at the operator level

- Rigetti hardware, pyQuil, or equivalent gate-level SDK familiarity

- Exposure to automated calibration frameworks (QuantrolOx, QUAlibrate, Q-CTRL, or similar)

- Depth in TLS physics, flux noise, readout optimization, or crosstalk characterization

**What We Offer **

- Direct access to on-premises superconducting QPU hardware at the Illinois Quantum and Microelectronics Park, the kind of access most researchers only find at national labs

- Small, rigorous team, your technical judgment shapes outcomes directly

- Competitive salary, equity, and full benefits

- Travel to IQMP as needed for system operation and characterization

This is a senior individual contributor role with real strategic weight. The Principal Physicist is the translation layer between what Superlinear Computing envisions and where the boundaries of the physical world are still being drawn.

Principal Physicist

Empowering the world to visualize ideas through pioneering research and design. Try Dream Machine for free → lumalabs.ai/dream-machine

Industry: Software Development
Company Size: 11-50 employees

Luma AI

**About The Role**

This is a foundational opportunity to refine, personalize, and build the final capabilities and control interface of Luma’s foundation models and drive real-world value.

You’ll sit at the intersection of **research, product, and partnerships **, helping close the gap between ~~generalist capability ~~ and ~~production needs ~~. Your mission is to make our video foundation models more **expressive, controllable, and personalized **– solving the “last mile” challenges demanded by top-tier creative workflows.

**What You’ll Do**

You will work as a fullstack researcher across **modeling, data, systems, and evaluation ** to translate foundational capabilities into the personalized and high-fidelity tools required by top-tier creative production.

- Controllability and Features: You will use SFT, RL, distillation, and adapter-based methods to give Luma’s models precise control and creative capabilities for high-fidelity, partner-grade workflows.

- Personalization: You will use context management, PEFT, and preference learning to embed domain expertise and long-horizon memory into our models. You’ll ground our data engine in real-world workflows, translating usage into training and data insights that shape future models.

- End-User Quality: You will define and drive end-user quality – setting success metrics, building user-aligned evaluations, and iterating on the model/data/evals loop to meet strict fidelity and reliability targets in specific verticals.

- Cross-functional Collaboration: You will partner with Product and Design to turn creative intent and user feedback into clear specs and shippable model behaviors, delivering intuitive control and dependable capabilities for users and partners.

**Who You Are**

- Strong foundation in machine learning with deep experience in visual generative models (diffusion/transformers or related architectures). Ideal candidates also have a deep understanding of at least one: fine-tuning, personalization, domain adaptation, data curation, targeted distillation, interpretability, or human-feedback-driven refinement.

- You are a product-obsessed researcher/engineer. You treat end users and partners as collaborators and enjoy solving specific “last mile” problems – not just optimizing public metrics.

- Hands-on experience with PyTorch and large model training.

**Bonus Points**

- Contributions to state-of-the-art models in image/video generation.

- Experience collaborating with creative partners (VFX, animation, film, design tools).

- Track record building workflows/tools that materially improve iteration speed and evaluation rigor.

- Familiarity with large-scale training infrastructure and distributed systems (Ray, Slurm, Kubernetes).

Research Scientist / Engineer - Controllability, Personalization & Productization

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