About this opportunity:

At Freenome, we are seeking a Senior Software Engineer II to join our innovative Engineering team. The ideal candidate is an experienced backend engineer with a strong background in developing scalable and reliable software solutions. You will play a crucial role in designing, building, and maintaining backend services that support our mission to detect cancer early. This position requires a collaborative mindset, as you will work closely with an interdisciplinary team of engineers, scientists, and product managers to deliver high-quality software solutions. You are passionate about software development best practices and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to our engineering management team. This role will be a Remote role. 

What you’ll do:

• Design, develop, and deploy reliable, maintainable, scalable, and fault-tolerant backend services that power both our internal and external systems.
• Collaborate with interdisciplinary teams, including scientists, product managers, and other engineers, to solve complex problems and deliver high-quality software solutions.
• Mentor and guide junior engineers, fostering their growth and enhancing the team's technical expertise.
• Lead code and design reviews, champion engineering best practices and promote a culture of quality and collaboration.
• Contribute to the development of data infrastructure for machine learning applications, ensuring efficient data processing and integration.
• Drive the implementation of engineering hygiene practices, ensuring the reliability and maintainability of our systems.
• Advocate for and implement innovative software development methodologies and tools to improve team efficiency and product quality.
  

Must haves:

• Bachelor of Science in Computer Science, Engineering, or related field or equivalent training, fellowship, and/or work experience.
• At least 8 years of experience as part of a software development team successfully shipping software products, including leading projects from end-to-end and mentoring others.
• Proficiency in Python and experience with backend development in a team production environment.
• Strong experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform.
• Proven experience in designing and implementing scalable backend systems, with a focus on reliability and performance.
• Excellent written and verbal communication skills, with a mindful and transparent approach to collaboration.
  

Nice to haves:

• Understanding of statistical and machine learning methods, with practical experience in applying them to real-world problems.
• Expertise in developing ETL or data pipelines that run at scale, utilizing common workflow management systems like Flyte, Airflow, or similar.
• Domain-specific experience in computational biology, genomics, bioinformatics, or a related field.
• Experience working in an FDA regulated environment, with a strong understanding of compliance requirements and best practices.
  

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

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.