About this opportunity:

At Freenome, we are seeking a Senior Network Engineer with experience managing enterprise and data center network infrastructure. This person will be part of the team tasked with delivering the network infrastructure for Freenome’s HQ campus. Additionally, this person will be responsible to ensure Freenome’s network infrastructure is scalable and following industry best practices. The ideal candidate will have hands-on experience with enterprise network technologies, automation tools, and a background in managing secure network solutions.

The role reports to the Director, IT. This role will be a Hybrid role.

What you’ll do:

• Lead the architecture design and implementation of the network infrastructure; both on-prem and in Cloud.
• Lead Zero Trust implementation and maintenance.
• Work closely with engineering and laboratory teams to gather requirements, analyze, and propose infrastructure solutions.
• Contribute to the delivery of a global standard network infrastructure.
• Develop and maintain network documentation, including diagrams, policies, procedures, and best practices.
• Troubleshoot and remediate any events impacting the operations and availability of the global network infrastructure.

Must haves:

• A minimum of 5 years Network Engineering experience.
• A minimum of 3 years Firewall security experience.
• A minimum of 3 years experience with configuring and managing Palo Alto Network firewalls.
• Juniper Networks JNCIP-ENT certification or equivalent experience.
• Advanced understanding of network hardware, software, protocols, and technologies.
• Experience with enterprise wireless network solutions and deployments.
• Hands-on experience with SSL and IPsec VPNs.
• Experience with network monitoring, management, and troubleshooting tools.
• Ability to work individually, as well as in a dynamic team environment.
• Strong communication and problem-solving skills.
• Ability to prioritize and manage multiple tasks and projects simultaneously.
• Strong documentation skills.

Nice to haves:

• Experience working in Clinical Diagnostics or Pharmaceutical Manufacturing.
• Expert experience with Juniper Networks products and solutions.
• Expert experience with Palo Alto Network Firewalls, Prisma, and Panorama.
• Experience with efficient iP SOLIDserver DDI.
• Engineering networks in GCP or other cloud providers.

Benefits and additional information:

The US target range of our base salary for new hires is $156,750 - $200,025. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-HYBRID

PsiQuantum’s mission is to build the first useful quantum computers—machines capable of delivering the breakthroughs the field has long promised. Since our founding in 2016, our singular focus has been to build and deploy million-qubit, fault-tolerant quantum systems. 

Quantum computers harness the laws of quantum mechanics to solve problems that even the most advanced supercomputers or AI systems will never reach. Their impact will span energy, pharmaceuticals, finance, agriculture, transportation, materials, and other foundational industries. 

Our architecture and approach is based on silicon photonics. By leveraging the advanced semiconductor manufacturing industry—including partners like GlobalFoundries—we use the same high-volume processes that already produce billions of chips for telecom and consumer electronics. Photonics offers natural advantages for scale: photons don’t feel heat, are immune to electromagnetic interference, and integrate with existing cryogenic cooling and standard fiber-optic infrastructure. 

In 2024, PsiQuantum announced government-funded projects to support the build-out of our first utility-scale quantum computers in Brisbane, Australia, and Chicago, Illinois. These initiatives reflect a growing recognition that quantum computing will be strategically and economically defining—and that now is the time to scale. 

PsiQuantum also develops the algorithms and software needed to make these systems commercially valuable. Our application, software, and industry teams work directly with leading Fortune 500 companies—including Lockheed Martin, Mercedes-Benz, Boehringer Ingelheim, and Mitsubishi Chemical—to prepare quantum solutions for real-world impact. 

Quantum computing is not an extension of classical computing. It represents a fundamental shift—and a path to mastering challenges that cannot be solved any other way. The potential is enormous, and we have a clear path to make it real. 

Come join us. 

Job Summary:

PsiQuantum is rapidly scaling to build the world's first useful fault-tolerant quantum computer. At the forefront of this effort, we need a motivated physicist/engineer to join our new laboratory in Brisbane and help us test the limits of our beyond-state-of-the-art quantum photonic platform. This role will focus on the validation and high-performance operation of our quantum photonic systems, and the development and validation of related methodology. The successful candidate will be responsible for executing experiments—including data analysis and interpretation—to validate and calibrate quantum computer subsystems to fault-tolerant levels at high cadence. They will also assist with experimental design. They will identify physical processes that limit photonic quantum performance and feedback new understandings to improve designs and operations of future generation of quantum hardware, and new generations of validation methodologies. They will collaborate broadly with design and engineering teams across all of PsiQuantum’s technical disciplines, including optics, quantum optics, photonics, electronics, cryogenics, quantum architecture, and software to understand system performance and inform engineering models.

Responsibilities:

• Be part of a team pushing photonic quantum computing hardware to fault-tolerant quantum performance.
• Development of classical and non-classical measurements and procedures, and execution of these, to validate optical quantum computer systems performance.
• Develop and verify methods for calibration, self-test, and control of novel quantum photonic systems.
• Develop clear and quantitative metrics for quantum performance.
• Work with other teams to ensure that developed, defined, and documented validation objectives fit with the broader company mission and timeframes.
• Develop requirements for the software and electronics teams to implement procedures and manage data.
• Analyse, reduce, and deliver experimental data. Work with other engineering teams to ensure that the data informs engineering models for system performance.
• Debug complex systems and work with other engineering teams to conduct failure analysis and resolve design or manufacturing issues as appropriate.
• Communicate validation outcomes broadly to internal stakeholders and help guide corrective actions.
• Work on-site in the lab in Brisbane, Australia.

Experience/Qualifications:

• Ph.D or equivalent experience in experimental quantum optics/quantum physics, photonic/electrical engineering, or a related field, and a demonstrated track record of delivering high quality research outcomes.
• Demonstrated expertise in the design and execution of complex quantum experiments in a cross-functional environment.
• Broad technical knowledge with ability to dive deep into required technical areas of our systems including hardware, software, controls, precision measurement, photonics, and quantum information.
• Software development for instrumentation, controls, test equipment, and data analysis (python preferred).
• Proven team player with an ability to work effectively across departments, sites, time zones.
• Excellent verbal and written communication skills with an ability to communicate effectively to a variety of audiences including senior leadership and technical experts.
• Demonstrated interest in PsiQuantum’s mission and vision for quantum computing, with an ability to contribute within a fast-paced start-up environment consistent with PsiQuantum’s values of communication, collaboration, respect, results, and challenge.

PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, or any other basis protected by applicable laws.

Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to recruiting@psiquantum.com.

We are not accepting unsolicited resumes from employment agencies.

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine Learning Science (MLS) team, within the Computational Science department. The ideal candidate has a strong knowledge in designing and building deep learning (DL) pipelines, and expertise in creating reliable, scalable artificial intelligence/machine learning (AI/ML) systems in a cloud environment. 

The MLS team at Freenome develops DL models using massive-scale genomic data that presents significant challenges for current training paradigms. The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL pipelines, optimizing hardware utilization for efficient training, and performing model optimizations. As part of an interdisciplinary R&D team, they will work in close collaboration with machine learning scientists, computational biologists and software engineers to accelerate the development of state-of-the-art ML/AI models and help Freenome achieve its mission of reducing cancer mortality via accessible early detection.

The role reports to the Director of Machine Learning Science. This can be a hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Implement and refine DL pipelines on distributed computing platforms enhancing the speed and efficiency of DL operations including model training, data handling, model management, and inference.
• Collaborate closely with ML scientists and software engineers to understand current challenges and requirements and ensure that the DL model development pipelines you create are perfectly aligned with scientific goals and operational needs.
• Continuously monitor, evaluate, and optimize DL model training pipelines for performance and scalability.
• Stay up to date with the latest advancements in AI, ML, and related technologies, and quickly learn and adapt new tools and frameworks, if necessary.
• Develop and maintain robust and reproducible DL pipelines that guarantee that DL pipelines can be reliably executed, maintaining consistency and accuracy of results.
• Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation pipelines.
• Act as a bridge facilitating communication between the engineering and scientific teams, documenting and sharing best practices to foster a culture of learning and continuous improvement.

Must haves:

• MS or equivalent experience in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Software Engineering, with an emphasis on AI/ML theory and/or practical development.
• 5+ years of post-MS industry experience working on developing AI/ML software engineering pipelines.
• Proficiency in a general-purpose programming language: Python (preferred), Java, Julia, C, C++, etc.
• Strong knowledge of ML and DL fundamentals and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Jax or Scikit-learn.
• In-depth knowledge of scalable and distributed computing platforms that support complex model training (such as Ray or DeepSpeed) and their integration with ML developer tools like TensorBoard, Wandb, or MLflow.
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and how to deploy and manage AI/ML models and pipelines in a cloud environment.
• Understanding of containerization technologies (e.g., Docker) and computing resource orchestration tools (e.g., Kubernetes) for deploying scalable ML/AI solutions.
• Proven track record of developing and optimizing workflows for training DL models, large language models (LLMs), or similar for problems with high data complexity and volume.
• Experience managing large datasets, including data storage (such as HDFS or Parquet on S3), retrieval, and efficient data processing techniques (via libraries and executors such as PyArrow and Spark).
• Proficiency in version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) practices to maintain code quality and automate development workflows.
• Expertise in building and launching large-scale ML frameworks in a scientific environment that supports the needs of a research team.
• Excellent ability to work effectively with cross-functional teams and communicate across disciplines. 
  

Nice to haves:

• Experience working with large-scale genomics or biological datasets.
• Experience managing multimodal datasets, such as combinations of sequence, text, image, and other data.
• Experience GPU/Accelerator programming and kernel development (such as CUDA, Triton or XLA).
• Experience with infrastructure-as-code and configuration management.
• Experience cultivating MLOps and ML infrastructure best practices, especially around reliability, provisioning and monitoring.
• Strong track record of contributions to relevant DL projects, e.g. on github.
  

Benefits and additional information:

The US target range of our base salary for new hires is $161,925 - $227,325 You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-REMOTE

Role

As a Principal Mechanical Engineer at Vivodyne, you will be part of a multi-disciplinary team pushing the boundaries of automated, large-scale "organ-on-a-chip" robotics and related manufacturing systems. Your focus will be on developing and optimizing hardware and software that orchestrates robotic arms, embedded controllers, and microfluidic systems to enable high-throughput, high-precision biological workflows.

This role requires expertise across hardware and software, but primarily hardware.  From high-level motion control and machine vision to robotics programming and embedded firmware. You’ll work extensively with existing Python (less so with, C#, and C++) codebases, ensuring seamless system integration and performance.

You are a mechanical design expert.  Things like kinematic docking, 440 vs 316, FEA, and error budgets are very familiar to you.  Your friends include McMaster-Carr, Misumi, and Grainger. 

Collaboration is key—you’ll engage with mechanical engineers, biologists, immunologists, AI scientists, and process engineers to design and refine automation workflows that drive breakthroughs. We’re looking for a problem solver comfortable working across multiple domains, thriving in a fast-paced, high-innovation environment that values continuous learning and technical excellence.

This is a full-time, onsite role in San Francisco, where you’ll be designing, building, and testing some of the most advanced automation and high-throughput biology systems in the world.

Responsibilities

• Architect, design, and implement advanced automation systems, ranging from automated microfluidic manufacturing to high-precision mammalian cell culture platforms—all of which are mission-critical and highly visible both internally and externally.
• Develop hardware and software systems that acquire and process data reliably, ensuring smooth handoffs to production through rigorous documentation, data acquisition, and analysis.
• Embrace the dynamic nature of a rapidly growing startup, working across multiple projects and disciplines.
• Collaborate cross-functionally with Product leads, tissue engineers, microfluidics specialists, and AI researchers etc. to gather requirements, set technical objectives, and integrate new features into our robotics platforms.
• Design and implement resilience mechanisms to ensure system robustness, enabling fault detection, fault recovery, and minimal downtime, while maintaining data integrity.
• Proactively identify optimization opportunities, selecting priorities through engineering analysis and data-driven decision-making.
• Communicate progress and findings to internal stakeholders—including mechanical engineers, data scientists, and senior leadership—through data-laden presentations and technical reports.

Requirements and Expectations

Technical Expertise & Knowledge

• Bachelor’s degree (M.S. or Ph.D. preferred) in Mechanical Engineering, Chemical Engineering, or a related field with a focus on microfluidics, tissue engineering, or lab automation at least six years of directly relevant industry experience.
• Broad experience in hardware and, preferable, software design for automation, spanning off-the-shelf solutions and custom-built systems—you have developed complex automation workflows for production-level environments.
• Proficiency in key hardware and software tools, including SolidWorks (expert-level, CAM experience is a plus), and at some exposure to Python/Matlab/C++/C#/Javascript/etc.
• Hands-on experience with commonly used automation hardware, such as vision/camera systems (optics and/or optomechanical expertise is a plus), motion control, liquid handling, and pick-and-place robotics.
• Highly knowledgeable in various Manufacturing Technologies, you know how things are made and which approaches fit a particular application
• Industry-specific expertise is highly valued:
• Biotech/lab automation or semiconductor robotics experience is a strong advantage.
• Knowledge of microfluidics and fluid handling systems.
• Experience integrating robotics with high-content imaging and confocal microscopy systems, optimizing workflows for advanced imaging pipelines.
• Biology background or familiarity with cell and tissue engineering concepts is a significant plus, especially in handling biological samples.
• Bonus points for experience with:
• Electronics/PCBA design or basic knowledge (reading schematic, troubleshooting interconnects), statistical analysis/data collection to inform design performance rigorously

Problem Solving & Ownership

• You take an outcome-driven approach, translating project goals and technical challenges into systematic, resilient robotics solutions.
• Strong ownership mentality, ensuring the timely delivery of high-reliability features and improvements.
• Growth-oriented, continuously seeking ways to enhance automation processes, optimize robotic operations, and drive innovation.

Collaboration & Communication

• A team player, capable of working with engineers, scientists, and external stakeholders to define requirements, refine designs, and communicate project progress effectively.
• Clear communicator, able to explain complex robotics concepts to cross-functional teams, from software engineers to biologists.
• Interdisciplinary mindset, integrating feedback from various fields to develop thoughtful, iterative design improvements.

Innovation & Leadership Mindset

• Passionate about staying at the cutting edge of robotics, bringing fresh ideas from emerging technologies, best practices, and research to the team.
• Comfortable taking initiative in uncharted territories, whether it’s developing new motion-planning algorithms or integrating novel sensors and hardware.

Why Vivodyne?

• High-Impact Mission – Play a pivotal role in transforming drug discovery and human therapeutics through advanced robotics and automation.
• Multi-Disciplinary Exposure – Work alongside leading experts in robotics, AI, biology, and microfluidics, expanding your expertise in a truly collaborative setting.
• Growth Opportunities – A fast-growing startup environment with significant autonomy, ownership, and influence over best practices in the intersection of biotech and robotics.
• Innovative Culture – Join a team that prioritizes continuous learning, rigorous engineering and scientific standards, and bold problem-solving.

If you're excited about revolutionizing automation in organoid engineering and biotech—while pushing the boundaries of robotics, AI, and advanced systems—let’s connect! Please submit your resume and a brief statement of interest. We look forward to exploring the opportunity together.

Vivodyne, Inc. is an equal opportunity employer. Vivodyne complies with all laws respecting equal employment opportunity and does not discriminate against applicants with regard to any protected characteristic as defined by federal, state, and local law.