Senior Software Engineer - Instrument

Rivercell; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Equity package

Growth opportunities

Résumé du poste

Rivercell is building an instrument operating platform that controls hardware, executes protocols, and ensures traceable data capture. You will design and deliver production-grade software tightly integrated with hardware, sensors, and high-throughput imaging.

You will work with interdisciplinary teams across microfluidics, AI, computer vision, optics, and biology, shaping architecture, reliability, and scalable testable pipelines, with ownership from build to deployment and maintenance.

Qualifications

• 5+ years of relevant experience in software engineering and delivery of complex production systems.
• Experience building software that controls physical equipment or laboratory automation.
• Strong proficiency in Python, with focus on concurrency, packaging, testing, and reliability.

Responsabilités

• Define instrument-software architecture including device services, orchestration, and sensing.
• Write and review production code, own critical components, ensure quality and velocity.
• Design hardware-abstraction layers, state machines, and long-duration protocol execution.
• Coordinate with AI, computer vision, and lab-automation teams for integrated systems.
• Lead fault detection, recovery, observability, and complete traceability.

Connaissances

Python

Architecture design

Distributed systems

Computer vision

Outils

Docker

Linux

Description du poste

We are looking for a hands-on Senior Software Engineer to work on the architecture, development, integration, testing, and delivery of Rivercell's instrument operating platform—the software that controls the hardware, executes biological protocols, monitors device performance, manages failures, and ensures the traceable acquisition of experimental data.

The platform will integrate and orchestrate power and light sources, microscopes, cameras, temperature-control systems, sensors, projected-pattern systems, and other laboratory equipment. It will automate complex cell-biology protocols, provide engineering and operator interfaces, and manage high-throughput data acquisition, buffering, metadata, and transfer to downstream processing and storage systems.

Some of the engineering challenges you will address include:

• Thousands of droplets containing hundreds of thousands of human cells will be moved simultaneously through projected light and electrical excitation. They will be detected and tracked by computer vision, routed around each other without touching, imaged on a schedule, and accounted for from their creation until they leave the instrument.

• Between microfluidic operations, the platform will assess the status of the device, detect deviations such as abnormal droplet trajectories, volume changes, temperature excursions, impedance drift, or imaging defects, attempt automated recovery, and elevate unresolved issues to an operator. Instrument sensing and imaging may generate several terabytes of raw data per hour, requiring reliable acquisition and complete experimental traceability.

You will work hand-in-hand with an interdisciplinary team spanning microfluidics, genetic engineering, AI, computer vision, bio-laboratory automation, optics, electronics, mechanical engineering, and biology. You will be an integral part of an ambitious and exciting startup project from its inception.

• Help define the overall instrument-software architecture, including hardware abstraction, device services, orchestration, protocol execution, sensing, quality control, observability, testing, and operator applications

• Write and review production code, own critical shared components, and set the standard for development quality, simplicity, documentation, and velocity

• Design stable hardware-abstraction layers and versioned interfaces

• Design the state machines, workflow engine, scheduling systems, and configuration model required to execute long-duration biological protocols

• Synchronize projected patterns, electrical excitation, image acquisition, motion, sensing, and protocol events with the timing guarantees required by the instrument

• Define fault-detection, retry, recovery, safe-state, and operator-escalation strategies for hardware, software, and biological-process failures

• Ensure complete observability and traceability of device state, commands, sensor measurements, protocol steps, samples, droplets, generated data, and software configurations

• Design and deliver engineering tools and operator interfaces for hardware development, protocol configuration, live monitoring, diagnostics, quality control, and production testing

• Establish simulation, software-in-the-loop, and hardware-in-the-loop environments that allow protocols, device behavior, and failure modes to be tested without continuous access to the full physical instrument

• Build reliable high-throughput acquisition pipelines for images and sensor data, including buffering, metadata integrity, back-pressure management, and transfer to downstream storage and processing systems

• Define interfaces with computer-vision, scientific-data, AI, and laboratory-information systems, working with dedicated specialists on the underlying algorithms and data products

• Own the build, release, deployment, update, diagnostics, and rollback strategy for software running on development and production instruments

• Lead cross-functional root-cause analyses where software, optics, electronics, microfluidics, hardware, biology, or data systems interact

• Opportunity to work on a cutting-edge project in the field of biotech

• Opportunity to join an ambitious team and impactful startup among the first employees

• Competitive salary and equity package

• Exciting opportunities for personal and professional growth within the team

You have 5+ years of relevant experience in software engineering, including responsibility for the architecture and delivery of complex production systems. You have a track record of building software that controls physical equipment, such as scientific instruments, robotics, medical devices, semiconductor tools, industrial automation, or laboratory systems. You are deeply proficient in Python, including concurrency, process isolation, performance profiling, typing, packaging, testing, and the judgment not to be clever when reliability matters. You combine strong architectural judgment with a willingness to debug hardware interfaces, inspect logs, write test harnesses, and solve practical problems at the bench. When faced with a large system, you instinctively identify the smallest end-to-end architecture that can produce a useful working version within weeks, using simulation, reusable components, and AI-assisted development effectively. You are comfortable with ambiguity in a scientific environment: specifications will evolve as the biology and hardware teach us, and you know how to design systems that can evolve without becoming chaotic. You are autonomous, committed, enthusiastic, and comfortable working with a can-do, creative, and challenging mindset. You are rigorous in system design, testing, documentation, data interpretation, incident analysis, and communication of uncertainty. You have excellent communication skills and are fluent in English; professional proficiency in French is helpful but not required. You have previous experience or knowledge in one or more of the following areas: Event-driven, distributed, or service-oriented architectures for physical systems Workflow engines, state machines, complex orchestration, scheduling, or distributed control systems Real-time, near-real-time, deterministic, or safety-relevant control systems Device communication over serial, USB, Ethernet, SCPI or similar protocols Linux-based deployment, containers, observability, networking, remote diagnostics, and automated software updates Computer vision or image analysis at scale, particularly for microscopy, tracking, or closed-loop control High-throughput image, video, or sensor-data acquisition and transfer Simulation environments, digital twins, software-in-the-loop, or hardware-in-the-loop testing Operator interfaces and engineering applications for complex instruments