Job Description

HelloFresh Group is on a mission to change the way people eat, forever. From our 2011 founding in Europe’s vibrant tech hub Berlin, we’re evolving from the world’s leading meal kit company to the world's leading food solutions group. In ANZ, we are home to HelloFresh and EveryPlate, our meal kit brands; Youfoodz, our ready-to-heat brand; and Be Cool, our national refrigerated courier service.

As a Product Optimisation Specialist, you are the voice of the customer, you will have passion for understanding of our customers and transforming sentiment and data points relating to the product into action.

Driving insights into the Youfoodz operational teams decisions making across culinary, development, product lifecycle management, menu planning, operational execution. You will build tools and dashboards to support our, run self-service analyses, and conduct regular and systematic analyses to improve our recipe performance and product offering. We are looking for a data-driven foodie who will make HelloFresh Group better by playing an important role in changing the way people eat, forever.

This role is based in Karawatha, Brisbane and reporting to the Associate Director of Product Operations.

You will…

• Apply data, transformation and analytics, confidently working across databricks, and tableau and innovatively utilising tools to push data into reports that will inform strategic thinking. 
• Tracking and trending data building dashboards to inform strategic decisions to support self-service insights into Culinary & Menu performance.
• Interpret meal performance and customer trends to deliver actionable insights for New Product Development (NPD) and existing product improvements (EPD).
• You are the voice of the customer- working with the CX team and drawing analysis from customer sentiment and net promoter insights and product metrics to drive customer centric decisions. 
• Championing the customer across key stakeholders ensure we are all aligned on the product led improvements. Uphold the customer feedback into actions. 
• Create and maintain tools and dashboards in Tableau or Excel Extract and analyse data and draw actionable insights to enable decision making on the key questions facing all areas of Culinary performance and operations.
• Translate recipe related data into compelling stories in order to drive change in the team and business.

You have…

• 2+ years experience in an analyst role. .
• A deep understanding of numbers and analytics as well as a strong business sense.
• Excellent hands-on knowledge of Excel/Google Sheets, Tableau and SQL.
• Excellent attention to detail.
• The ability to document analyses and learnings in a clear and concise way, and present them to key a broad group of vested stakeholders.

You are…

• Passionate about the ability of data to change a business and how numbers can be transformed into key product insight.
• A data-driven "foodie" who thrives in a fast-moving, data-led decision-making environment and have a interest in food. 
• Highly collaborative, with the ability to interface across global strategy, CX, and data teams.
• Efficient and proactive in identifying opportunities for automation and scalability.
• A clear communicator capable of delivering insights that drive customer-led decision-making.

What you’ll get in return… 

• The chance to have a significant impact in a leading global food technology company
• Flexible working arrangements 
• Egoless environment, constant learning with room for personal growth
• Free access to Headspace
• Internal learning & development 
• A diverse and vibrant international environment, with offices in 18 countries
• Company discount - 70% off HelloFresh & 40% Youfoodz
• Onsite gym at the facility

Start Date: Immediately available - Can wait a notice period

Duration: Permanent full time role

Location: Karawatha, Brisbane 

Salary: Competitive salary & employee benefits

#youfoodz

Position Summary:

ultradedicated – Your biggest challenges yield rare possibilities

The Senior Director, FP&A will be a key business partner to Ultragenyx’s Development organization, with primary responsibility for strengthening financial governance, budget transparency, and accrual rigor across development activities. The position supports the Chief Medical Officer and senior Development leadership by enabling a clear, consistent understanding of spend to date, remaining budget, and forward‑looking financial exposure across clinical and non‑clinical functions. The role combines hands‑on analytical execution with executive‑level financial storytelling to improve confidence, decision‑making, and stewardship across the development portfolio. 

Work Model: 

Flex: This role will typically require onsite work 2-3 days each week, or more depending on business needs. In many locations, the business will set certain days each week that Flex employees are required to be onsite.

Responsibilities:

1. Establish and maintain strong working relationships with Development leadership and operational stakeholders, serving as a trusted finance partner embedded in clinical study governance, financial oversight, and execution forums.  
2. Provide hands‑on financial support to Program Teams and Development functions by reviewing invoices, tracking actual spend, and identifying total and remaining budget at the study, program, and functional levels.  
3. Lead clinical trial cost modeling, including scenario planning and sensitivity analyses, clearly explaining cost drivers related to study design, timelines, enrollment assumptions, and execution strategies.  
4. Perform regular budget‑to‑actual analyses across clinical and non‑clinical Development activities, synthesizing account‑level, vendor‑level, and study‑level variances into concise, decision‑oriented insights.  
5. Deliver clear, actionable financial updates on spend, forecast changes, risks, and opportunities to minimize surprises and strengthen confidence in Development financial outlooks.  
6. Partner with Accounting and operational teams to support Development accrual processes, ensuring assumptions are timely, well‑documented, and aligned with underlying operational activity.  
7. Lead financial communications related to clinical trials and broader Development spend, including inputs to executive‑level readouts, portfolio reviews, and CMO‑level presentations.  
8. Support annual planning and in‑year reforecasting cycles by reviewing business‑generated forecasts, assessing reasonableness, and providing Development‑wide financial context and challenge.  
9. Design, implement, and continuously improve financial tools, reporting, and processes that enhance budget visibility, accrual understanding, and financial fluency across Development teams.  
10. Balance near‑term execution and stewardship of existing processes with a longer‑term focus on strengthening governance frameworks, standardization, and transparency across Development financial management. 

Requirements:

1. Bachelor’s degree in finance, Accounting, Economics, or a related discipline; MBA, CPA, or advanced degree preferred.  
2. Minimum of 12 years of progressive experience in FP&A, finance, or financial management supporting R&D or development organizations within the biotechnology, pharmaceutical, or life sciences industry.  
3. Demonstrated experience partnering with Development teams, including Clinical Operations and non‑clinical functions such as Regulatory, Pharmacovigilance, Biostatistics, and Statistical Programming.  
4. Deep expertise in clinical trial financial modeling, including cost drivers, scenario planning, and sensitivity analysis, with the ability to translate operational assumptions into credible forecasts.  
5. Strong background in financial governance, including budget oversight, variance analysis, accrual support, and spend‑to‑date transparency.  
6. Proven ability to influence without formal authority and partner effectively with senior leaders, program teams, and functional stakeholders.  
7. Ability to operate seamlessly between strategic and detailed perspectives, including hands‑on engagement with invoices, actuals, and accrual drivers, as well as executive‑level synthesis.  
8. Demonstrated success leading process improvement initiatives that improve budget visibility, accrual rigor, and financial fluency within business teams.  
9. Strong communication skills, with the ability to deliver clear, concise summaries of variances, forecast changes, and drivers to audiences ranging from study teams to executives.  
10. Advanced proficiency in financial modeling, forecasting, and analytics tools (e.g., Excel, Adaptive Insights, and enterprise planning systems) 

#LI-CK1 #LI-Hybrid

Role

The Software & Data Science team at Vivodyne tackles some of the hardest problems at the intersection of human biology, large-scale data, and machine learning using uniquely rich imaging and multi-omics datasets from lab-grown human tissues.

We are expanding our capabilities to generate high-throughput -omics data across automated human tissue models, with a primary focus on single-cell and bulk transcriptomics, secretomics, and proteomics. We're looking for a Bioinformatician who can develop new analytical methods and build robust infrastructure to support them at scale.

You will define how we process, store, integrate, and interpret biological datasets, making foundational decisions that shape the long-term utility of our data for internal research, AI/ML model development, and external partners. This means owning both the science (what question does this analysis answer, and how defensible is the conclusion?) and the engineering (does this pipeline run reliably at scale, and can someone else extend it?).

This is a high-impact, cross-functional role. You'll sit within the Software & Data Science organization and collaborate daily with experimental biologists, AI/ML researchers, software engineers, and client-facing teams.

This is a full-time, onsite role in San Francisco.

Responsibilities

Develop and Own Analytical Methods

• Design, implement, and critically evaluate computational approaches for scRNA-seq, bulk RNA-seq, secretomics, and proteomics data including QC, normalization, batch correction, dimensionality reduction, clustering, differential expression, trajectory analysis, and multi-dataset integration.
• Go beyond applying standard tools: develop or adapt methods for perturbation modeling, causal inference, network reconstruction, ligand-receptor inference, and multi-omics integration as the science demands.
• Select and standardize tooling based on rigorous benchmarking, not convention. Challenge default choices when the data or use-case warrants it.

Build Scalable, Production-Grade Pipelines

• Architect end-to-end analysis workflows in Python and/or R using modern workflow orchestration (Nextflow, Snakemake, or equivalent) that are reproducible, version-controlled, and designed to run at the scale of tens to hundreds of thousands of samples.
• Partner with software and data engineers to productionize pipelines, ensure robust data ingestion and storage, and contribute to decisions on biological data architecture (storage formats, schema design, long-term data usability).
• Write well-documented, testable code that other engineers and scientists can run, review, and extend.

Drive Biological Insight and Interpretation

• Own dataset analysis to answer biological and client-driven questions with rigor. Ground conclusions in the limits of the data and clearly communicate what can and cannot be concluded with confidence.
• Partner with experimental biologists to frame the most relevant biological questions, design analyses, and recommend experiments and data-generation strategies to fill key gaps.
• Produce publication-quality figures, internal reports, and partner-facing deliverables that are decision-useful.

Shape Data Strategy

• Help define benchmarking strategies for internal tissue model development.
• Proactively identify opportunities to leverage internal and public datasets to accelerate scientific progress.
• Contribute to decisions around data standards, comparability, and the integration of omics features into downstream ML models and AI workflows.

Communicate Across Functions

• Translate complex multi-omic analyses into clear insights for biologists, AI/ML researchers, software engineers, and non-technical stakeholders.
• Tailor depth and framing to the audience while maintaining scientific rigor.

Requirements and Expectations

Technical Expertise

• Ph.D. in Computational Biology, Bioinformatics, Genomics, Systems Biology, Biostatistics, or a related quantitative field with deep focus on transcriptomics and/or proteomics.
• 2–5 years of post-PhD experience; some industry experience strongly preferred.
• Strong, hands-on proficiency in Python for bioinformatics (Scanpy and the broader scverse ecosystem in particular) with the judgment to know when existing tools are insufficient and the skill to build alternatives. Familiarity with R-based workflows (Seurat, Bioconductor, Monocle) is valued as evidence of breadth, but Python is the production language.
• Deep experience with scRNA-seq datasets and workflows, including QC, batch correction, clustering, differential expression, annotation, and integration across experiments.
• Experience with proteomics or secretomics analysis (Olink or similar high-dimensional panels), including normalization and cross-modality integration with transcriptomic profiles.
• Comfort in a Unix/Linux environment with standard dev tools (git, containers, CI/CD); experience with cloud environments (AWS) and workflow managers is a strong plus.
• Familiarity with data infrastructure for large-scale biological data (e.g., AnnData/H5AD, TileDB-SOMA, or similar) is a plus.

Problem Solving & Ownership

• Ability to independently structure and execute complex analytical projects from ambiguous initial questions to concrete, reviewable outputs.
• Strong biological intuition for distinguishing meaningful signal from artifact and the discipline to validate before interpreting.
• Comfortable navigating ambiguity in a fast-moving startup; can prioritize, make trade-offs, and hit agreed timelines.

Collaboration & Communication

• Excellent written and verbal communication; able to explain computational methods and biological implications to biologists, engineers, and non-technical stakeholders.
• Proven ability to collaborate across disciplines.

Innovation & Leadership

• Track record of taking omics analyses from raw data to figures/tables suitable for publications, reports, or decision meetings.
• Demonstrated ability to manage multiple analyses in parallel and ship work on predictable timelines.
• History of method development or meaningful adaptation of existing methods to novel data types or experimental designs.

Preferred Qualifications

• Experience with multi-modal data integration (e.g., combining imaging, transcriptomics, and proteomics features).
• Background in drug discovery, toxicology, or translational research where multi-omic data inform therapeutic decisions.
• Experience with representation learning or ML for biological data (embeddings for cells, genes, or proteins), especially in collaboration with ML specialists.
• Familiarity with organoids, primary tissues, or organ-on-chip systems.

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.

About this opportunity:

At Freenome, we are seeking a Senior Manager, Product Marketing - Blood Testing Portfolio to help grow the Freenome Marketing team. In this role, you will be instrumental in helping us launch our first products and driving adoption in the clinic. This position is responsible for architecting and executing marketing strategies that resonate across a complex healthcare ecosystem, inspiring action among providers and the patients they serve. The work centers on championing our pipeline of blood-based screening tests—including our lung cancer screening solution and future indications—ensuring our customers are empowered and informed by the next generation of early detection technology. This role is a vital pillar in Freenome’s mission to redefine the patient-provider experience and fundamentally shift the landscape of cancer through the power of multi-cancer screening.

The role reports to the Director, Product Marketing. This role will be a Remote role.

What you’ll do:

• You’ll be the Marketing lead for Freenome’s portfolio of cancer screening blood tests, developing and leading marketing strategies that ensure our tests are effectively communicated and resonate with providers and patients.
• Leverage voice of customer to develop and optimize the core value proposition and messaging for Freenome’s blood tests and ensure messaging, creative and tactics are maximized for impact.
• Collaborate cross-functionally with team members, including our our Product team on defining the patient experience for pipeline and in-market tests, and our sales teams as they engage directly with customers.
• Develop high-impact sales enablement resources to prepare field teams for upcoming product introductions.
• Drive customer insights through KOLs and advisory board meetings.
• Monitor the landscape of cancer screening blood test competitors and industry trends to ensure Freenome’s positioning remains differentiated in the space.
• Manage external creative and digital agencies to deliver compelling, differentiated, and on-brand marketing campaigns.
• Analyze market trends and campaign performance data to refine marketing strategies and drive future product growth.
  

Must haves:

• 7+ years of relevant experience and Bachelor’s degree in an analytical, technical, or scientific field; MBA strongly preferred.
• Experience marketing to providers and patients, ideally with a focus on primary care, preventative health and/or oncology.
• Experience marketing regulated or centralized laboratory-developed products and leveraging Med-Legal-Regulatory review process.
• Deep understanding of diagnostics and healthcare technology markets.
• Exceptional storyteller and communicator capable of explaining complex data science, machine learning, and clinical concepts in simple terms.
• Strong cross-functional leadership skills with proven experience managing complex projects through influence.
• An entrepreneurial mindset; comfortable with ambiguity, takes initiative, and possesses strong problem-solving skills.
• Experience building marketing collateral from scratch with little to no existing materials.
  

Nice to haves:

• Experience in marketing cancer screening, primary care, or preventive health products.
• Experience with CRM and digital marketing tools to enhance customer engagement.
  

Benefits and additional information:

The US target range of our base salary for new hires is $161,925 - $232,575. 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

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:

Are you passionate about advancing quantum materials theory and computational modeling? As a Quantum Materials Theorist, you will join an interdisciplinary team at the forefront of computational physics, materials science, machine learning, and quantum technologies. This role offers the opportunity to develop and refine theoretical and computational approaches for understanding and predicting material properties, contributing to next-generation technologies.

You will bring expertise in electronic structure theory, many-body physics, and computational methods to explore complex quantum materials and emergent phenomena. Your work will involve integrating conventional and emerging computational approaches, incorporating insights from machine learning, high-performance computing (HPC), and quantum computing to drive innovation in materials discovery and design.

This position provides the opportunity to engage in high-impact, collaborative research, working alongside specialists in quantum algorithms, materials informatics, computational physics, chemistry, and condensed matter modeling. If you thrive in an intellectually stimulating environment and enjoy tackling fundamental and computational challenges in quantum materials science, we encourage you to apply.

This position requires a PhD in computational physics (or a closely related field), preferably with postdoctoral research experience (although postdoc experience is not mandatory). We are looking for a curious, creative, and interdisciplinary thinker with a comprehensive understanding of various computational physics, chemistry, and machine learning methodologies. The ideal candidate should be an avid reader of scientific literature, have expert-level hands-on coding experience (e.g., Python, Fortran, or C++), and possess deep expertise and skills in methodology development, which may include contributions to open-source atomistic simulation software packages. While prior knowledge of quantum information and fault-tolerant quantum computing is highly preferred, it is not required.

Responsibilities:

• Conduct theoretical and computational research in materials theory and simulations, advancing methodologies for modeling electronic structure, strongly correlated systems, and emergent quantum phenomena.
• Develop computational workflows that integrate established and emerging techniques, leveraging advances in high-performance computing (HPC), machine learning, and quantum computing.
• Collaborate with quantum algorithm developers, computational physicists, and materials scientists to explore new frontiers in quantum materials modeling.
• Contribute expertise in electronic structure theory and many-body physics to research efforts focused on understanding and predicting material properties.
• Stay at the forefront of developments in computational materials science, incorporating state-of-the-art approaches into research projects.
• Serve as a technical leader in interdisciplinary collaborations, working with internal and external teams on innovative solutions in quantum materials research.
• Engage in external partnerships, scientific discussions, and technical communication to support the broader research and application of advanced computational materials methodologies.
• Document research progress effectively and contribute to publications and external-facing materials that highlight advances in the field.

Experience/Qualifications:

Required:

• Ph.D. in theoretical or computational physics or chemistry or a closely related field, with a focus on electronic structure and many-body physics.
• Strong foundation in electronic structure theory, band structure calculations, and computational modeling.
• Expertise in methodology development within density functional theory (DFT).
• Proficiency in scientific programming and algorithm development, with experience in Python, Fortran, or C++.
• Familiarity with high-performance computing (HPC) environments and large-scale simulations.
• Enthusiasm for interdisciplinary collaboration, working across physics, chemistry, materials science, machine learning, and computational research teams.
• Strong peer-reviewed publication record.

Preferred:

• Experience with machine learning and data-driven approaches in computational modeling.
• Experience with quantum algorithms, particularly their application to materials modeling and electronic structure problems.
• Familiarity with wave function based computational chemistry methodologies, including coupled-cluster, configuration interaction (CI), and multi reference methods.
• Expertise in many-body and strongly correlated systems, including Fermi-Hubbard models, tensor networks, and embedding theories.
• Hands-on coding experience with Wannier function calculations.

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

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, and the ability to thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, 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 the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
• Build models that achieve high accuracy and that generalize robustly to new data.
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration.
• Take a mindful, transparent, and humane approach to your work.

Must haves:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modeling.
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks.
• Practical and theoretical understanding of DL models like large language models or other foundation models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
• A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
• Experience in NGS data analysis and bioinformatic pipelines.
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.

Benefits and additional information:

The US target range of our base salary/hourly rate for new hires is $173,775 - $246,750. 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

About this opportunity:

Freenome is seeking a highly analytical and systems-savvy Senior People Systems and Data Analyst to elevate our People data capabilities and drive insight-led decision-making. This role will own the development of dashboards, analytics, and reporting that provide visibility into workforce trends and inform hiring, retention, engagement, and organizational planning strategies. This individual will transform People data into actionable insights through advanced analytics, scalable dashboards, and strong data storytelling. While the role maintains ownership of People systems and data integrity, its primary focus is generating insights that enable better business decisions.

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

What you’ll do:

• Develop, analyze, and interpret workforce data to identify trends, risks, and opportunities across recruiting, retention, performance, and engagement.
• Conduct deep-dive analyses (attrition trends, hiring funnel performance, compensation insights, engagement drivers).
• Build statistical and trend analyses across the employee lifecycle to proactively surface insights that influence People and business decisions.
• Deliver actionable quarterly reporting that translates complex datasets into clear, executive-ready insights and recommendations.
• Design, build, and maintain scalable and automated dashboards.
• Establish consistent KPI definitions and reporting standards.
• Improve data visualization practices to ensure clarity, usability, and impact.
• Replace manual reporting processes with automated, real-time reporting solutions.
• Ensure high levels of data accuracy, integrity, and trust.
• Serve as primary People data and HRIS reporting expert.
• Partner with IT and vendors to implement and manage integrations, evaluate new features, and identify opportunities to automate data workflows.
• Manage data governance standards to ensure compliance and data privacy best practices.
• Identify process improvements that enhance efficiency, data structure and accessibility.
• Enable tier-zero employee and manager self-service for policies, processes, and data through systems and chatbots, reducing reliance on People team members and ticket systems.
• Champion system education to drive employee and manager self-service adoption and data and systems utilization.
• Drive AI initiatives such as deploying LLMs for job descriptions and ML to forecast attrition, ensuring tools are trained and continuously refined to be fit-for-purpose and remain within ethical and legal guardrails.
  

Must haves:

• Bachelor’s degree in Statistics, Data Science, Business Analytics, HR, Economics, or related field.
• 5–7 years of experience in People Analytics, Workforce Analytics, HRIS Analytics, or related analytical roles.
• Prior experience modifying, improving and/or implementing People systems (Greenhouse, Paylocity a bonus).
• Advanced proficiency in data visualization tools (Tableau, Power BI, Looker, or similar).
• Strong experience building executive dashboards from the ground up.
• Knowledge of data, statistical, and predictive analysis.
• Advanced Excel/Google Sheets skills.
• Experience working with large, complex datasets.
• Demonstrated ability to translate data into clear business insights and recommendations.
• Strong understanding of core People processes (recruiting, compensation, performance, engagement, workforce planning).
• Excellent verbal and written communication skills.
• Strong analytical and problem-solving skills.
• Passion for driving continuous improvement simplifying workflows, implementing automation, and driving self-service.
• Demonstrated interest in leveraging AI to enhance systems and analytics.
  

Nice to haves:

• Experience in a high-growth biotech or startup environment, with exposure to IPO preparation, public company reporting requirements, or SOX-compliant processes.
• Familiarity with Greenhouse, Paylocity, or other HRIS/ATS platforms.
• Exposure to predictive analytics or basic modeling techniques.
• SHRM-CP or SHRM-SCP certification.
  

Benefits and additional information:

The US target range of our base salary for new hires is $120,275 - $170,100. 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

About this opportunity:

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, the ability to drive independent research and thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, 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 the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
  
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
  
• Build models that achieve high accuracy and that generalize robustly to new data.
  
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
  
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration.
  
• Take a mindful, transparent, and humane approach to your work.
  

Must haves:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• 6+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise demonstrated by research publications or industry achievements, in driving independent research in applied machine learning, deep learning and complex data modeling.
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks, boosting and model aggregation.
• Practical and theoretical understanding of DL models like large language models or other foundation models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
• Proficient at productive cross-functional scientific communication and collaboration with software engineers and computational biologists.
• A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
  
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
  
• Experience in NGS data analysis and bioinformatic pipelines.
  
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
  
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.
  

Benefits and additional information:

The US target range of our base salary for new hires is $199,675.00 - $283,500.00. 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

Position Summary

The Head of Wealth Advisory is a senior executive leadership position responsible for overseeing the FPA wealth advisory function. This role has accountability to deliver revenue targets and growth ambitions for the business. It will drive the strategic direction, growth, and excellence of personalised wealth advisory services to high-net-worth (HNW)) and ultra-high-net-worth (UHNW) clients and their families.

The Head of Wealth Advisory leads an end-to-end team of wealth advisors, paraplanners, client service and operations professionals while ensuring fiduciary standards, regulatory compliance, exceptional client outcomes, and sustainable business growth. This individual serves as a key member of the senior leadership team, championing client-centric advice, innovation in financial planning & investment solutions, and the overall performance of the advisory platform.

This role can be located in Syndey, New South Wales, Australia; Brisbane, Queensland, Australia.

Primary Responsibilities

Strategic Leadership & Business Development

• Define and execute the long-term vision and strategy for the FPA Wealth Advisory team, aligning with overall business objectives and prioritising both organic and inorganic growth pathways.
• Drive organic growth in Net New Assets (NNA), revenue, and market share through new client acquisition, deepening existing relationships, expanding service offerings, and cultivating a robust referral ecosystem.
• Build and nurture high-value referral partnerships with external centers of influence (e.g., CPAs, Wills & Estates Lawyers, Consultants, and other professionals) to generate consistent, high-quality leads and enhance t
• he firm's reputation in target markets.
• Partnering with the President of Focus Partners Australia to identify, evaluate, and pursue strategic expansion opportunities through mergers and acquisitions (M&A), including assessing potential acquisition targets (e.g., complementary advisory practices or teams) and joint ventures.

Performance & Reporting

• Own P&L responsibility for the Wealth Advisory division.
• Monitor key performance indicators (KPIs) including NNA growth (organic and inorganic), revenue per advisor, referral-sourced new business, client acquisition/retention, fee realisation, profitability, and M&A pipeline/progress, process efficiency metrics (eg time saved through automation or AI adoption)
• Provide regular executive reporting and presentations to senior leadership on growth strategies, partnership outcomes, digital initiatives, M&A opportunities and operational efficiencies.

Team Leadership & Talent Development

• Lead, motivate, and mentor a high-performing team of private wealth advisors, associate advisors, paraplanners, client service and operations professionals.
• Collaborate with People & Culture (P&C) to foster a culture of growth, excellence, collaboration, continuous learning, and client-first mindset.
• With P&C establish clear performance metrics, compensation structures (including incentives tied to referrals and growth initiatives), and development programs aligned with business goals.

Client Experience & Advisory Excellence

• Ensure delivery of highly personalised, comprehensive wealth advisory services including financial planning, investment portfolio construction, retirement & legacy planning, tax-efficient strategies, risk management, philanthropy, and intergenerational wealth transfer.
• Maintain ultimate accountability for the overall client experience with a focus on client satisfaction and retention.
• Champion the business’s regulatory obligations, best-in-class advice standards and seamless integration of digital experiences (e.g client portals, automated insights) with human led advice.
• Partner with Risk & Compliance, Service Design & CX and technology teams to proactively address regulatory changes, emerging risks, service challenges and opportunities for process automation.

Qualifications

• 10+ years of progressive experience in wealth management or financial advisory services in Australia, with at least 6–8 years in senior leadership roles (e.g., Head of Advice, Head of Sales etc)
• Proven track record of building and scaling high-performing advisory teams, driving consistent FUM & revenue growth through organic channels, referral networks, and inorganic initiatives (M&A, acquisitions, or integrations).
• Demonstrated success in leveraging technology (e.g., CRM systems, AI/analytics tools, portfolio platforms, automation workflows) to drive efficiency, adviser productivity, and client outcomes.
• Experience driving teams to deliver repeatable, scalable processes to automate routine tasks, streamline operations, and support business growth.
• Expertise in comprehensive wealth planning, portfolio construction, capital markets, alternative investments, tax/estate strategies, client relationship management, and business development via professional alliances.
• Full compliance with ASIC professional standards for relevant providers (including meeting the legislated education/qualifications standard as of 1 January 2026 or via experienced provider pathway, registration on the Financial Advisers Register (FAR), and ongoing CPD obligations).
• Bachelor’s degree in Finance, Commerce, Economics, Business Administration, or related field (Master’s degree, MBA, or equivalent strongly preferred).
• Strategic thinker with strong business acumen, commercial orientation, and experience in evaluating M&A opportunities, partnership structures, and digital transformation roadmaps.
• Exceptional leadership, coaching, and people-development capabilities, with a focus on building growth oriented, client focused advisory teams
• Outstanding interpersonal and communication skills; able to build trust with sophisticated clients, advisers, external referral sources, technology partners, and C-suite executives.
• Deep understanding of the current Australian regulatory environment (ASIC, Corporations Act, best interests duty, FAR), fiduciary best practices, integration considerations in M&A, and technology-enabled compliance/risk management.
• Analytical mindset with ability to interpret performance data, market trends, deal valuation/diligence, and efficiency metrics from automated systems.
• High degree of integrity, professionalism, and commitment to ethical standards.

#LI-SF1

Good people. Good work. Great opportunities.

McCullough Robertson is a commercially focused firm with a proud 100 year history, working with high-calibre national and international clients. We work on big matters in small teams, approaching each day with dedication and professionalism.      

We provide exceptional opportunities for our employees to perform, grow and succeed through extensive training and career development. Our teams work together and support one another to achieve individual, team and firm-wide goals.

Backed by a national team of over 400 staff located in Brisbane and Sydney, McCullough Robertson combines a century of experience with a modern, collaborative approach, making us a big firm, without the attitude.

The Team

Our Brisbane Construction and Infrastructure team is recognised for its expertise in complex infrastructure, energy and resources projects across Queensland and nationally. Led by highly experienced partners with decades of combined experience in Australia and internationally, the team advises government, developers, contractors and financiers on the structuring, procurement and delivery of major projects.

The team holds deep capability across transport, roads, water and waste, airports, education facilities, mining infrastructure, rail and port facilities, carbon and renewable energy projects. Trusted by government clients on procurement strategy, probity and contract administration, the team plays an active role in shaping industry standards.

The Role

We are seeking a talented and motivated front-end construction lawyer to join our leading Brisbane Construction and Infrastructure team. Working closely with our experienced partners and lawyers, you will provide practical and commercially focused advice to government and private sector clients on the procurement, structuring and delivery of major infrastructure, energy and resources projects.

This role offers exposure to complex and high-value projects from the outset, including transport, roads, water and waste, mining infrastructure, rail and port facilities, airports, education facilities and renewable energy developments. You will assist in drafting and negotiating sophisticated project agreements, advising on procurement strategies, risk allocation and contract administration, and supporting clients through all stages of project delivery.

You will join a highly collaborative and technically strong team where partners are hands-on and invested in mentoring junior lawyers. The role provides an exceptional opportunity to develop both technical expertise and commercial judgement, while building lasting relationships with clients on projects that shape Queensland’s infrastructure and energy landscape.

Experience

As the successful candidate, you will be a skilled and enthusiastic lawyer, with one or two years of post-admission experience. As well as having industry knowledge, you will be passionate about construction with a keen desire to develop a long-term career in this space.

You will be comfortable drafting and reviewing complex project agreements, negotiating contract terms, and providing practical, commercially focused advice. Your excellent communication skills will allow you to build strong relationships with both clients and colleagues, and you will thrive working autonomously while contributing effectively within a collaborative, high-performing team.

Benefits

At McCullough Robertson, we encourage a balanced work environment. Our teams enjoy having the opportunity to work in a supportive environment while having fun and achieving results.

We offer the following benefits for our employees:

• Dedicated Diversity committee with an innovative program focusing on all areas of diversity and inclusion;
• Attractive further education program and supportive learning and development opportunities throughout your whole career;
• Mentoring and sponsorship opportunities as well as coaching and leadership support;
• Holistic Health and Wellbeing program including subsidised gym membership and active social and sporting committees; and
• Inhouse barista and end-of-trip facilities.

Inclusion and Diversity

We are a leader in diversity and inclusion and are committed to creating an environment where our employees want to come to work.

Our commitment is to create an accessible and informed workplace, where we can collectively make a difference for everyone, including people with disability, to gain equal opportunities and grow their career at McR. This is our commitment to diversity and inclusion and how we bring to life our McR values.

An award-winning law firm, we have received the prestigious Employer of Choice for Gender Equality citation for the tenth consecutive year and have recently been awarded by Lawyers Weekly – Diversity Law Firm of the Year.

To apply for this position, please click on the "Apply for Job" button, and submit your application on-line. Alternatively, please contact Sophie Sims on 07 3914 8462 for a confidential discussion.

We're an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Good people. Good work. Great opportunities.

McCullough Robertson is a commercially focused firm, working with high-calibre national and international clients. We work on complex matters in small teams, approaching each day with dedication and professionalism.

We provide exceptional opportunities for our employees to perform, grow and succeed, through extensive training and career development. Our teams work together and support one another to achieve individual, team and firm-wide goals.

Backed by a national team of over 400 staff located in Brisbane and Sydney, McCullough Robertson is a big firm, without the attitude.

The Team 

McCullough Robertson’s Construction and Infrastructure team is recognised for its ability to effectively guide clients through every phase of a project. With extensive experience advising on risk allocation and the successful delivery of major developments across Australia, we act as a true extension of our clients’ teams—responsive, commercially minded, and solution-focused.

Our team provides end-to-end project support across a broad range of industries. We have played a key role in the delivery of mining and energy infrastructure, renewable energy projects, including solar farms, wind farms, and battery energy storage systems, essential utilities, such as pipelines, water and wastewater facilities, and electricity networks, as well as ports and airports, transport infrastructure including roads, rail, and major social infrastructure projects.

The Role

We are seeking a Senior Associate with strong construction dispute resolution experience to join our expanding team. Our practice covers all facets of contentious construction disputes, including litigation, domestic and international arbitrations, contractual dispute resolution processes, and Security of Payment adjudications. Additionally, we provide clients with strategic advice to support successful project delivery.

This role offers the opportunity to apply your advanced skills in drafting legal documents and delivering insightful advice that helps clients navigate complex disputes. You will collaborate directly with clients and partners based in both Brisbane and Sydney.

As a key member of a high-performing, experienced team, you will contribute your expertise in construction law across diverse industries. While based in Brisbane, you will support client matters on a national scale.

Experience

We are seeking a confident and capable newly promoted or intermediate Senior Associate to join our dynamic Construction team. The successful candidate will possess a deep understanding of the construction industry, coupled with a genuine passion for the sector and a clear dedication to building a long-term career in construction law.

You will bring excellent communication skills and sound commercial judgment, enabling you to manage complex matters independently while also thriving in a collaborative, supportive, and close-knit team environment. Your ability to engage effectively with clients and stakeholders, combined with your practical approach to problem-solving, will be key to your success.

In addition, you will demonstrate strong leadership capabilities, contributing to the development and mentorship of junior team members and supporting the growth of the practice. You will play an integral role in shaping project outcomes, driving strategic initiatives, and fostering a positive team culture that values excellence and innovation.

This is an exciting opportunity to advance your career in construction law within a respected and forward-thinking firm that values expertise, integrity, and collaboration.

Benefits

At McCullough Robertson, we encourage a balanced work environment. Our teams enjoy having the opportunity to work in a supportive environment while having fun and achieving results.

We offer the following benefits for our employees:

• Dedicated diversity committee with an innovative program focusing on all areas of diversity and inclusion;
• Attractive further education program and supportive learning and development opportunities throughout your whole career;
• Mentoring and sponsorship opportunities as well coaching and leadership support;
• Holistic Health and Wellbeing program including subsidised gym membership and active social and sporting committees; and
• In-house barista and end-of-trip facilities.

Inclusion and Diversity

We are a leader in diversity and inclusion, and are committed to creating an inclusive environment for all employees.

Our commitment is to create an accessible, inclusive and informed workplace, where we can collectively make a difference for everyone, including people with disability, to gain equal opportunities and grow their career at McR. This is our commitment to diversity and inclusion and how we bring to life our McR values.

An award-winning law firm, we have received the prestigious Employer of Choice for Gender Equality citation for the tenth consecutive year and have recently been awarded by Lawyers Weekly – Diversity Law Firm of the Year.

To apply for this position, please click on the "Apply for Job" button, and submit your application online. Alternatively, please contact Sophie Sims on 07 3914 8462 for a confidential discussion.

We're an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Role

The AI Team at Vivodyne tackles some of the hardest and most interesting challenges in science and engineering. With access to extraordinarily feature-rich and massive-scale Vivodyne human tissue imagery, we are advancing the frontiers of artificial intelligence and its applications in biology. We are building a portfolio of AI technologies to automate the discovery, development, and de-risking of novel therapies using our unique technology platform, including single-cell 3D phenomics/machine vision, multimodal (multi-omic) translation, and reinforcement learning for robotic planning & study design, among others.

As an AI Senior Scientist, you will leverage your deep expertise in developing large-scale models (including Transformer, Diffusion, and hybrid architectures) and Generative AI solutions to help turn our state-of-the-art imaging and multi-omics datasets into groundbreaking scientific insights. You will collaborate closely with biologists, engineers, and AI specialists to deliver robust, production-ready algorithms and models that power Vivodyne’s high-impact discoveries.

This role will be based on-site at our offices in Brisbane, California

Responsibilities

• Scientific Innovation — Work closely with internal and external stakeholders to understand their scientific objectives and innovate new approaches that utilize Vivodyne’s massive-scale imaging and multi-omics datasets.

• Model Development — Lead hands-on development of cutting-edge machine learning models (Transformers, Diffusion, hybrid architectures, etc.) with a focus on image processing, image enhancement, and Phenomap embeddings.

• Data Pipeline Optimization — Build and deploy pipelines capable of scaling to petabyte-scale data, ensuring robust MLOps practices on AWS or equivalent cloud platforms.

• Multimodal Integration — Explore and develop novel methods to incorporate multi-omics data into imaging-based Phenomaps, advancing the state of the art in multimodal phenotypic analysis.

• Collaboration & Communication — Partner with tissue engineers, microfluidics experts, and robotics engineers to refine data collection strategies, provide feedback on imaging system performance, and identify opportunities for improved AI-driven solutions.

• Scientific Rigor & Leadership — Uphold scientific excellence through peer reviews, proper documentation, and clear communication. Drive a culture of continuous improvement, best practices, and adherence to rigorous research methodologies.

• Scalability & Efficiency — Emphasize modularity, composability, and performance efficiency in designing and implementing high-throughput compute and analytics pipelines.

• Domain & Technical Growth — Remain current with the latest research trends in Generative AI, biomedical imaging, cloud computing, and data-intensive training. Proactively share knowledge and mentor teammates to foster overall organizational expertise.

Requirements and Expectations

• Scientific Excellence — Stay current with AI/ML research, especially in Generative AI, Transformers, Diffusion models, and multi-modal architectures. Apply rigorous, data-driven methods for sound outcomes.
• Hands-On Leadership — Set high standards for model development and code quality, mentoring team members and fostering innovation.
• Accountability — Own model and infrastructure development from concept to deployment, delivering reliable, scalable solutions aligned with Vivodyne’s mission.
• Problem Solving & Adaptability — Develop creative solutions to novel research challenges, thriving in a fast-paced, dynamic startup environment.
• Collaboration & Communication — Work cross-functionally to align AI strategies with business goals, ensuring clear communication and consensus-building.
• Delivering Results — Prioritize impactful research, using project management best practices to track progress, mitigate risks, and meet deadlines.
• Architecture & Coding — Design scalable, cost-effective systems and produce clean, well-documented code with continuous testing and governance compliance.
• Resource Optimization — Apply financial discipline to maximize the efficiency of compute, storage, and third-party services.
• Team & Thought Leadership — Foster an inclusive environment, mentoring future leaders and representing Vivodyne in AI research and industry discussions.

Qualifications

• Education & Experience

• PhD in Computer Science, Applied Mathematics, or a related field, or equivalent practical experience.
• Proven expertise developing and deploying advanced ML architectures (Transformers, Diffusion, multi-modal models) in Generative AI settings.
• Demonstrated history of success with image processing and large-scale model training.

• Technical Skills

• Strong knowledge of AWS or another major cloud provider for MLOps, big data processing, and scalable computing.
• Experience building models for petabyte-scale datasets and understanding the associated architectural and operational complexities.

• Domain Expertise (Preferred)

• Familiarity with biological or biomedical imaging; advanced knowledge in multi-modal Phenomaps, especially integrating imagery with multi-omics data, is a major plus.

• Additional Desired Skills

• Prior experience with HPC, GPU clusters, or distributed computing frameworks.
• Comfortable with container orchestration and open-source data engineering/ML frameworks.

• Soft Skills & Leadership

• Strong written and oral communication skills, with a proven ability to present complex technical topics to non-experts.
• Demonstrated ability to thrive in ambiguous environments, driving clarity and direction with minimal supervision.

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.