Leads secondary analysis algorithm development for Sequencing by Expansion (SBX) data on the AXELIOS platform, bridging rapid R&D prototyping with production-grade bioinformatics tools across oncology, genetic disease, and infectious disease.
Compensation
The expected salary range for this position based on the primary location of California is $47.00-$52.00 per hour.
Responsibilities
Algorithm Development
Benchmarking
Software development
Presenting results to stakeholders
Requirements
PhD (enrolled student)
Nice to have: Record of publications or preprints describing novel algorithms or methods for variant detection and genotyping
Nice to have: Research experience focused on difficult-to-map regions of the genome
Nice to have: Publications or documented contributions involving Repeat-variant detection or genotyping
Nice to have: Haplotype phasing and reconstruction
Perform complex research, design, and software development assignments within a software functional area or product line, and provide direct input to project plans, schedules, and methodology in the development of cross-functional software products.
Compensation
$126,964.93 to $141,600.00/year + standard company benefits
Responsibilities
Perform software design across multiple systems
Mentor more-junior members of the team
Translate user/customer requests into solutions
Write and review detailed specifications for complex system components
Complete complex bug fixes
Requirements
Bachelor’s degree in Computer Science, Software Engineering, Physics, Mathematics, or a related field
Shape how we understand our customers and the products they rely on every day by building models, experiments, and AI-enabled tooling that turn product data into actionable business decisions.
Compensation
Base Pay Range:
198,240.00 - 272,580.00 USD Annual
This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation.
Responsibilities
Lead, coach, and scale a distributed team of analytics engineers, data scientists, and researchers
Drive a proactive insight agenda for product and engineering leadership
Measure the business impact of feature rollouts, customer programs, and platform AI features using robust experimentation and causal inference techniques
Deliver clear, executive-ready recommendations backed by empirical data to product, engineering, and customer success leadership
Develop and deploy production machine learning models for customer health scoring, cost forecasting, predicted time-to-value, and entity intelligence
Requirements
Bachelor’s degree in computer science, statistics, economics, or a related quantitative field
Nice to have: Databricks (Spark, Delta Lake, Unity Catalog)
Develop and execute data strategies, perform complex data analysis, design and optimize scalable data pipelines, and build robust infrastructure for big data integration within the Hospital Patient Monitoring Artificial Intelligence Journey.
Compensation
The pay range for this position in Nashville, TN is $115,000 to $183,000.
Responsibilities
Develop and execute data strategies that align with evolving business needs
Perform complex data analysis and queries using advanced techniques to deliver actionable insights
Ensure data integrity and compliance by implementing rigorous validation processes
Design and optimize scalable data pipelines to support Post Market Analytics
Build robust infrastructure for big data integration across diverse sources
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field
Master’s degree in Computer Science, Engineering, or a related field
Design, build and ship safeguards in the agent harness for prompt injection, single and multi-turn jailbreaks, toxicity and sensitive topics, and sensitive data exposure.
Compensation
For positions in this location, we offer a base pay of $201,300 - $352,300, plus equity (when applicable), variable/incentive compensation and benefits.
Responsibilities
Design, build and ship safeguards in the agent harness for prompt injection, single and multi-turn jailbreaks, toxicity and sensitive topics, and sensitive data exposure
Build evals that measure safeguard efficacy on both false and true positives, using datasets from customer reports, adversarial testing and production traffic
Work closely with our Security team: turn their adversarial findings into eval cases and fixes, and build mitigations together that hold when detection misses
Select, integrate and fine-tune detection models within a stack shared by our commercial and government environments
Balance quality, latency and cost for controls that run in the request path
A key privacy engineer writing code and shaping the architecture and protections across products, focusing on sensitive data detection, masking, and assessing privacy risks of ML models.
Compensation
For positions in this location, we offer a base pay of $201,300 - $352,300, plus equity (when applicable), variable/incentive compensation and benefits.
Responsibilities
Assess, benchmark and select ML models and techniques that meet privacy requirements
Own the implementation of models from prototype through production
Build and deploy sensitive data detection, masking, redaction and tokenization
Build privacy evaluations for ML models (memorization, training-data extraction, membership inference)
Write and maintain code enforcing customer requirements for data use, access, retention and deletion
Requirements
Nice to have: Differential Privacy
Nice to have: Privacy-enhancing technologies
Nice to have: Privacy engineering for agentic systems
Lead the development of pricing, credit-risk and portfolio-management solutions across Business and Commercial Banking, combining quantitative modelling with modern software-development practices.
Compensation
£95,418 to £106,020
Responsibilities
Own the methodology and lead the software implementation of Return on Risk Adjusted Capital models supporting the origination and pricing of commercial lending products.
Build production-quality solutions for loan pricing, portfolio management, capital allocation, forecasting and credit-risk analytics.
Develop reusable, well-documented and tested analytical code, applying version control, peer review and robust model-development standards.
Use Python, C#, and SQL to work with large datasets, automate analytical processes and improve the efficiency and control of existing tools.
Lead the application of advanced statistical and machine-learning techniques to identify growth opportunities, support client acquisition and deepen client relationships.
Requirements
Postgraduate qualification, or equivalent experience, in mathematics, statistics, physics, quantitative finance or another highly quantitative discipline
Join a small, fast-moving AI pod to build and deploy generative and agentic AI solutions directly with business users, working hands-on with LLMs, SLMs, agentic frameworks and AWS.
Compensation
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
Responsibilities
Build and ship generative AI and agentic AI applications end to end, from prototype to production
Develop agentic workflows, including tool-using agents and multi-agent collaboration
Contribute to autonomous AI capabilities with appropriate guardrails and controls
Implement orchestration and retrieval-augmented generation (RAG) pipelines, integrating AI solutions with internal systems
Build and run model and agent evaluations to maintain high-quality outcomes
Requirements
Formal training or certification on software engineering concepts
Seeking architects, engineers, and BIM professionals to support hyperscale data center programs, turning design models into structured information for program-level decisions.
Locations (2)
San Francisco, California, United States
Golden, Colorado, United States
Compensation
San Francisco, California: $80,000 to $140,000 annually
Golden, Colorado: $70,000 to $115,000 annually
Responsibilities
Develop and apply work breakdown structures and classification mappings with the client, connecting model elements and building systems to defined scopes, work packages, and relevant cost and schedule structures.
Define and maintain model metadata requirements, including parameters, identifiers, system assignments, and classification values that enable consistent analysis across disciplines and projects.
Extract, organize, and validate model data to produce structured datasets, quantities, and component inventories that remain traceable to their source.
Assess model health through information completeness, classification coverage, consistency, and quantity checks, identifying gaps that affect confidence in downstream analysis.
Compare model revisions and design configurations to identify changes in quantities, systems, and scope, distinguishing design changes from modeling or metadata discrepancies.
Requirements
Bachelor's degree in architecture, engineering, construction management, design technology, or a related field
Nice to have: Building systems knowledge
Nice to have: Interpreting drawings and specifications
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