Build, maintain, and optimize scalable data infrastructure for AI/ML features.
Partner with ML Engineers, Data Scientists, and Software Engineers to transform healthcare data into high-quality datasets.
Contribute to data pipelines, improve data quality, and ensure reliable, performant, and well-governed data for AI systems.
Tebra is the only all-in-one EHR+ platform built exclusively for independent healthcare practices. More than 42,000 private practices trust Tebra to streamline operations, increase revenue, and reduce burnout, with a culture that values starting with the customer, keeping it simple, staying entrepreneurial, being better together, and celebrating success.
Own productization of Alt's pricing and underwriting models from research through production, keeping them accurate and fast at scale.
Optimize pricing models to reduce infrastructure costs while improving accuracy, especially for high-value assets.
Lead the full ML lifecycle from model training and feature generation to production deployment and monitoring.
Alt unlocks the value of alternative assets, starting with the $5B trading-card market, offering a platform for collectors to buy, sell, vault, and finance their cards. Backed by leaders at Stripe, Coinbase, Seven Seven Six, and pro athletes, the company is at an inflection point with its pricing intelligence infrastructure as a competitive moat.
Builds and maintains feature pipelines, training datasets, and forecast workflows for revenue, demand, and operational planning.
Operationalizes forecasting and ML models through repeatable training, evaluation, deployment, and monitoring in Databricks.
Implements model performance tracking, drift monitoring, and traceability from source data to prediction output.
Sonny's Enterprises is the world's largest manufacturer of conveyorized car wash equipment, parts, and supplies. The company is the industry leader with a culture focused on innovation and growing its people.
Design and maintain ML model productionization infrastructure for high-visibility product features.
Collaborate with data science to streamline model training, validation, and deployment.
Implement robust monitoring and alerting for model performance, drift, and data quality.
The Athletic is a sports media company powered by one of the largest global newsrooms in sports, delivering in-depth coverage of professional and college teams across North America and Europe. With over 500 full-time staff, they foster a collaborative culture focused on high-quality journalism and data-driven innovation.
Design and implement robust, scalable data ingestion and transformation pipelines using Databricks, PySpark, and distributed processing.
Implement Delta Lake principles focusing on CDC and schema evolution, and integrate data quality frameworks within CI/CD pipelines.
Develop and optimize complex SQL and Python scripts, handling diverse data sources and supporting data governance solutions.
Mobile Wave Solutions is a professional services company specializing in software development as a service. With a team of over 120 engineers, we deliver scalable, high-quality software that empowers our global clients to innovate and grow.
Define clear business-value metrics alongside technical performance targets for engagements.
Lead technical scoping, feasibility assessments, and solution design for proposals and client pitches.
Design scalable, end-to-end ML pipelines spanning data analysis, model training, deployment, and MLOps.
Lovelytics helps complex enterprises modernize their data and put AI to work in production. It has grown from 85 to 500+ people across the Americas, maintaining a technically excellent, low-ego culture.
Lead the design and operation of production machine learning systems for batch and online use cases with a focus on reliability and scalability.
Build and improve ML lifecycle infrastructure including training pipelines, inference workflows, monitoring, and automation.
Partner with cross-functional teams to translate business problems into ML solutions and guide prototypes to robust production systems.
Included Health is a healthcare company delivering integrated virtual care and navigation, aiming to raise the standard of healthcare for everyone. They are a remote-first organization offering comprehensive benefits and fostering a culture of inclusion.
Own the Airflow codebase end-to-end, building reusable templates and enforcing standards.
Build and extend large-scale Spark pipelines on AWS Glue and support migration to Databricks.
Drive data model improvements around commercial pharma data with focus on structure and lineage.
Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. As one of the fastest-growing SaaS companies in history, it surpassed $3B in revenue and values doing the right thing, customer success, employee success, and speed.
Build integrations with healthcare and financial systems
Automate end-to-end data ingestion and delivery pipelines
Design high-throughput, low-latency systems where performance is a mission-critical requirement
Anomaly uses AI and healthcare transaction data to decode complex payer behavior and close the knowledge gap between providers and payers. Founded in 2020, it is a small, remote-friendly team with a hacker mindset.
Design, build, and deploy production-grade machine learning and AI systems for customer-facing analytics and automation.
Develop and operationalize end-to-end ML workflows from data preparation to model monitoring.
Collaborate with Product and Engineering teams to identify high-impact use cases and deliver AI-powered data products.
Boulevard provides a client experience platform for appointment-based self-care businesses, empowering customers to give clients magical moments. The company values diversity, experimentation, and simplicity, and celebrates diverse backgrounds.
Design, develop, and maintain resilient, scalable, end-to-end data pipelines with Snowflake and Python.
Partner with product owners and analysts to gather requirements and deliver data solutions aligned with business goals.
Act as a subject matter expert, mentor junior engineers, and champion DevOps practices including CI/CD and automated testing.
Privia Health is a technology-driven national physician enablement company that collaborates with medical groups and health systems to optimize practices and improve patient care through its cloud-based platform. The company is led by top industry talent and physician leadership, focusing on reducing healthcare costs and improving outcomes.
Design, build, and operate scalable Data & AI platform capabilities for analytics, data science, and Generative AI use cases.
Develop reusable frameworks, services, and workflows to standardize how teams build and manage data pipelines and data products.
Partner with Analytics, Applied-AI, and Engineering teams to deliver platform capabilities that support business and clinical decision-making.
Omada Health is on a mission to bend the curve of chronic disease by providing a virtual-first care model that combines human-led care teams, connected devices, and AI-enabled technology. They have served over two million members and are a publicly traded company with a culture of trust, context, boldness, results, and teamwork.
Lead the modernization of the data platform by migrating legacy Hadoop, Spark, and Impala pipelines to a scalable Databricks architecture.
Accelerate migration efforts using AI coding assistants like Claude and Codex to convert SQL and modernize ETL workflows.
Design and optimize scalable data pipelines with Airflow and Databricks, ensuring reliability, cost-efficiency, and data quality.
LivePerson is a leader in enterprise conversational AI and digital transformation, powering nearly a billion conversational interactions monthly. Fast Company named them the #1 Most Innovative AI Company, and they foster a remote-first, innovative culture.
Lead impactful customer technical projects by delivering production-grade systems spanning data engineering, AI, and application development.
Guide strategic customers in implementing end-to-end big data and AI projects, including architecture, design, build, and deployment.
Empower customers by providing architecture guidance and ensuring solutions are secure, scalable, and aligned with Databricks best practices.
Databricks is the data and AI company. More than 10,000 organizations worldwide, including Comcast and Condé Nast, rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. The company is headquartered in San Francisco and fosters a diverse, inclusive culture.
Build a cloud-native big data platform handling audience data for millions of attendees and billions of interactions.
Design and own ML infrastructure including feature stores, training pipelines, and model serving.
Own the full data pipeline from ingestion to business impact, ensuring reliability and performance.
Hive is a marketing platform that helps event marketers personalize and automate campaigns to sell out shows and engage fans. The company is a fully remote team located across Canada, fostering a work environment with strong work-life balance and a focus on impactful outcomes.
Own and evolve notebooks across the full medallion architecture, from raw ingestion through a fully modeled dimensional layer.
Design and implement dimensional modeling artifacts such as facts, dimensions, and slowly changing dimensions for downstream business intelligence.
Serve as the primary technical reference, reviewing pull requests, mentoring team members, and proposing architectural improvements.
CI&T helps large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions. With 30 years of experience and 8,000 employees across 25 countries, we foster a collaborative culture that accelerates innovation in Agentic SDLC, Application modernization, Data & AI, Martech, and Business strategy.
Design, build, and operate large-scale ML solutions for ad delivery performance.
Collaborate with cross-functional teams to deploy models into production.
Mentor peers and contribute to ML best practices and AI-native development.
The company is a technology firm focused on AI-driven advertising solutions. It operates in a remote-first environment with a collaborative and inclusive culture.
Design and build ingestion pipelines from enterprise source systems into the Databricks lakehouse using Delta Lake, owning Bronze-layer ingestion and building Silver-layer pipelines for cleansing and standardization.
Implement and maintain Databricks platform constructs for secure delivery, including catalogs, schemas, service principals, and job orchestration, and build CI/CD pipelines for data platform assets.
Apply data classification and segregation requirements within pipeline design, build data quality controls reflecting business meaning, and partner with teams to ensure reliable, governed data for downstream use.
Shield AI is a venture-backed defense-tech company founded in 2015 with the mission of protecting service members and civilians with intelligent systems, developing products like Hivemind autonomy software and V-BAT and X-BAT aircraft. The company has offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, and its technology actively supports operations worldwide.
Lead research and development of health trajectory models predicting member states and risks using real-world longitudinal data.
Design next-best-action algorithms that convert predicted trajectories into intervention decisions tailored to member context.
Serve as senior scientific lead for algorithmic rigor, mentoring scientists and collaborating with product and engineering teams.
Omada Health is a virtual-first healthcare company that combines human-led care teams, connected devices, and AI-enabled technology to deliver personalized care for chronic conditions like obesity and diabetes. They have served over two million members across 2,000+ employers and health plans, and have been certified as a Great Place to Work.