About Gusto At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff—like payroll, health insurance, 401(k)s, and HR—so owners can focus on their craft and customers. With teams in Denver, San Francisco, and New York, we’re proud to support more than 400,000 small businesses across the country, and we’re building a workplace that represents and celebrates the customers we serve. Learn more about our Total Rewards philosophy. About the Role: Gusto’s Data team leverages Gusto’s rich dataset to guide product direction and decision-making by building the right AI/ML solutions at scale. For this role, we are looking for a technical leader (an individual contributor) to drive the scale and optimization of our customer experience and customer journey via building AI and ML enabled experiences and services. In this role you will build and optimize AI/ML solutions and infrastructure that power our customer journey related products. You’ll be working with a strong AI/ML team and seasoned leaders in Engineering, Product, Design, Data Science, Marketing, and Sales. In this role, you’ll work cross functionally to build Platforms that span the entire breadth of the unified service platform stack using machine learning and AI to personalize world class content for our customers and enhance customer experience. Here’s what you’ll do day-to-day: - Design and develop scalable, production-grade AI and machine learning models for solving complex business problems. - Lead and mentor teams of ML engineers, fostering a culture of technical excellence and innovation. - Collaborate cross-functionally with product, engineering, and business stakeholders to identify AI opportunities and translate them into actionable solutions. - Stay current with latest AI research; prototype and implement new algorithms and advancements from academia and industry. - Oversee model validation, deployment, evaluation, and lifecycle management, ensuring robust monitoring, explainability, and performance. - Guide technical strategy, roadmap, and architectural decisions for the ML/AI function. - Communicate findings, roadmaps, and performance results clearly to executives and non-technical partners. Here’s what we're looking for: - 8+ years’ hands-on experience building and deploying end-to-end ML/AI systems in industry or academia. - Deep expertise in one or more advanced ML methods (supervised, unsupervised, reinforcement learning, deep learning, NLP, LLMs, RAG, etc.). - Proven track record of delivering large, impactful ML/AI projects into production environments. - Proficient in modern ML frameworks (TensorFlow, PyTorch, HuggingFace, etc.) and cloud computing platforms (AWS, GCP, or Azure). - Strong programming skills in Python and familiarity with best engineering practices (CI/CD, testing, code review). - Demonstrated leadership in cross-disciplinary teams and ability to mentor scientists and engineers. - Excellent communication skills and business acumen. - Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field is a plus. Our cash compensation amount for this role is targeted at $230k-280k for San Francisco, New York, and Seattle $205k - 255k in Los Angeles, $185k-234k in Denver, and 200k-250k CAD for Toronto. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale. Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas. When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees. Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto. Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you. Gusto takes security and protection of your personal information very seriously. Please review our Fraudulent Activity Disclaimer. Personal information collected and processed as part of your Gusto application will be subject to Gusto's Applicant Privacy Notice.

Passionate about precision medicine and advancing the healthcare industry? Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time. We are seeking an experienced and highly skilled Staff Machine Learning Engineer with deep expertise in large-scale multimodal model systems engineering to join our dynamic AI team. You will play a pivotal role in designing, building, and optimizing the foundational data infrastructure that powers Tempus's most advanced generative AI models. Your work will directly enable the training and deployment of robust, production-ready multimodal systems that analyze complex data types (like genomics, pathology images, radiology scans, and clinical notes) to improve patient care, optimize clinical workflows, and accelerate life-saving medical research. This is a critical, high-impact position for driving the practical application of cutting-edge AI to revolutionize healthcare. Focus: Your primary focus will be to architect, build, and maintain the critical data infrastructure supporting our large multimodal generative models. This includes managing the entire lifecycle of vast datasets – from ingestion and processing of diverse training data to the integration and retrieval of extensive knowledge sources used to augment model capabilities. You will be building the data backbone that enables our AI to learn from Tempus's rich real-world evidence. Key Responsibilities: As a technical leader in this space, you will be: - Architect and build sophisticated data processing workflows responsible for ingesting, processing, and preparing multimodal training data that seamlessly integrate with large-scale distributed ML training frameworks and infrastructure (GPU clusters). - Develop strategies for efficient, compliant data ingestion from diverse sources, including internal databases, third-party APIs, public biomedical datasets, and Tempus's proprietary data ecosystem. - Utilize, optimize, and contribute to frameworks specialized for large-scale ML data loading and streaming (e.g., MosaicML Streaming, Ray Data, HF Datasets). - Collaborate closely with infrastructure and platform teams to leverage and optimize cloud-native services (primarily GCP) for performance, cost-efficiency, and security. - Engineer efficient connectors and data loaders for accessing and processing information from diverse knowledge sources, such as knowledge graphs, internal structured databases, biomedical literature repositories (e.g., PubMed), and curated ontologies. - Optimize data storage for efficient large scale training training and knowledge access. - Orchestrate, monitor, and troubleshoot complex data workflows using tools like Airflow, Kubeflow Pipelines.. - Establish robust monitoring, logging, and alerting systems for data pipeline health, data drift detection, and data quality assurance, providing feedback loops for continuous improvement. - Analyze and optimize data I/O performance bottlenecks considering storage systems, network bandwidth and compute resources. - Actively manage and seek optimizations for the costs associated with storing and processing massive datasets in the cloud. Required Skills and Experience: - Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. A strong academic background with a focus on AI data engineering. - Proven track record (8+ years of industry experience) in designing, building, and operating large-scale data pipelines and infrastructure in a production environment. - Strong experience working with massive, heterogeneous datasets (TBs+) and modern distributed data processing tools and frameworks such as Apache Spark, Ray, or Dask. - Strong, hands-on experience with tools and libraries specifically designed for large-scale ML data handling, such as Hugging Face Datasets, MosaicML Streaming, or similar frameworks (e.g., WebDataset, Petastorm). Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, SageMaker Pipelines). - Understanding of the data challenges specific to training large models (Foundation Models, LLMs, Multimodal Models). - Proficiency in programming languages like Python and experience with modern distributed data processing tools and frameworks. - Leadership and collaboration: - Proven ability to bring thought leadership to the product and engineering teams, influencing technical direction and data strategy. - Experience mentoring junior engineers and collaborating effectively with cross-functional teams (Research Scientists, ML Engineers, Platform Engineers, Product Managers, Clinicians). - Excellent communication skills, capable of explaining complex technical concepts to diverse audiences. - Strong bias-to-action and ability to thrive in a fast-paced, dynamic research and development environment. - A pragmatic approach focused on delivering rapid, iterative, and measurable progress towards impactful goals. Preferred Qualifications: - Advanced degree (PhD) in Computer Science, Engineering, Bioinformatics, or a related field. - Contributions to relevant open-source projects. - Direct experience working with clinical or biological data (EHR, genomics, medical imaging). #LI-SH1 New York Pay Range - $190,000 - $230,000 USD California Pay Range - $190,000 - $230,000 USD Illinois Pay Range - $170,000 - $210,000 USD Remote - USA Range - $170,000 - $210,000 USD The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position. Additionally, for remote roles open to individuals in unincorporated Los Angeles – including remote roles- Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

• Conduct end-to-end analyses, wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas. • Mentor and guide junior engineers, fostering a culture of learning and technical excellence. • Work with large and complex textual and visual datasets. • Support the development and deployment of projects involving machine learned models for offline, batch-based data products as well as models deployed to online, real-time services. • Work in the contributor and visual intelligence team on text and visual understanding, along with fine tuning transformer models to derive embeddings for multiple input types. • Productionize and automate model pipelines within Python services. • Drive and advocate adoption of best practices in ML development and operations, and mentor newer engineers in those practices.

About The Role: As a Senior Machine Learning Operations Engineer you’ll be embedded in a team of talented data scientists and software engineers to create sophisticated models that answer hard questions centered around improving our logistics network and user experiences. This role bridges between ML platform work and building on top of our platforms to create new models. You’ll create the infrastructure and tooling necessary to deploy, monitor, and scale our machine learning models in production. In close collaboration with data scientists you’ll own our production models, ensuring optimal performance and responding to production incidents. A great candidate: - Is an expert in their craft, creating high quality ML infrastructure and delivering impactful machine learning models to our stakeholders. - Works in close collaboration with the other Data Science team members and keeps the business value at the center of their work. Has a bias for action, balancing delivering impact in the short-term while building out the long term vision. - Applies their ML / MLOPS knowledge to suggest new patterns, tools, approaches to improve the team’s models What you’ll do: - Build reliable, efficient, and scalable infrastructure for our AI/ML capabilities - Create robust data pipelines to feed analyses and models - Enable forecasting, network orchestration, and live pricing systems - Ensure data quality and data integrity through best practices in data integration - Build out robust feature stores, model orchestration tooling, experimentation tooling, model performance monitoring. - Create standards and templates for model development and deployment across all Data Science teams. What You Bring: - Bachelor’s Degree plus at least 3 years of experience in machine learning engineering, or Master’s Degree plus at least 2 years in machine learning engineering - This experience should include: - Developing and optimizing MLOps pipelines for speed, reliability, and observability. - Utilizing statistical modeling or machine learning techniques to solve business problems. - Strong proficiency in Python and SQL. - Hands-on experience with open-source languages and tooling for large-scale ML (e.g., Ray, Flink, Feast). - Working with Data Warehouses (e.g., Redshift, Databricks, Snowflake). - Utilizing cloud-based (AWS Preferred) data engineering and data science tools. - Experience building ML systems in Startups is a plus - Experience with DS/ML in Logistics/Supply Chain is a plus. Compensation: $175,000-190,000 per year The pay range is subject to the discretion of the Company. Additionally, Veho offers a competitive equity package, comprehensive medical, dental, and vision coverage as well as other benefits such as 401k and generous PTO for full-time roles.