Design and deliver near real-time data solutions for the analytics platform.
Analyze business needs, optimize data models, and identify slow queries for performance improvement.
Write clean, scalable code using Scala, Python, and SQL while mentoring team members.
Aircall is an AI-powered customer communications platform used by 22,000+ companies worldwide. It is a unicorn startup with offices across multiple countries and a focus on innovation and collaboration.
Design, build, and operate the online feature store serving ML features to production models with low latency and high reliability.
Build and maintain data pipelines (batch and streaming) that compute, validate, and publish features from source systems.
Act as a technical leader for feature store infrastructure, partnering with Data Science and Engineering teams to drive quality and scalability.
Forward Financing is a financial technology company on a mission to unlock capital for small businesses across America. The company has provided over $3.5 billion in funding to 71,000+ small businesses and is recognized as a Best Place to Work, with a culture focused on employee investment and customer experience.
Collaborate with data scientists and engineers to build scalable ML pipelines, troubleshoot infrastructure issues from Linux to Kubernetes, and optimize model performance.
Drive high engineering standards, design on-premises MLOps solutions, and maintain tools for deployment and monitoring.
Refine CI/CD workflows, incorporate ML model training and evaluation into testing, and ensure seamless handover between research and production.
Learneo is a platform of builder-driven businesses, including Course Hero, CliffsNotes, LitCharts, Quillbot, Symbolab, and Scribbr, focused on supercharging productivity and learning. The company supports high-growth businesses with centralized corporate operations and has a virtual-first culture with employees across multiple countries.
Design, build, and maintain robust, scalable batch and streaming data processing, storage, and integration pipelines.
Take full ownership of building features from the ground up, mentoring and leading your team to deliver the right solutions.
Partner with data scientists and engineers to create semantic data models and integrate applications across Shift5 componentry.
Shift5 is building the data platform for onboard operational technology (OT), delivering cybersecurity, predictive maintenance, and compliance capabilities for defense and commercial fleets. They are a growing company with a team-based environment, committed to building an inclusive culture and embracing diversity.
Build and maintain data pipelines for analytics, ML, and product applications.
Design scalable data infrastructure with a focus on quality and observability.
Collaborate with cross-functional teams to understand data needs and implement solutions.
Prolific builds human data infrastructure to power the next wave of AI innovation. They are a remote-first company focused on ethical data collection and mission-driven culture.
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.
Develop highly scalable and reliable data systems on AWS cloud platform for data-centric products.
Collaborate with Data Science teams to incorporate Machine Learning algorithms using Python and data engineering tools.
Lead and mentor team members, contribute to Agile cycles, and ensure timely delivery of documented software.
Experian is a global data and technology company that powers opportunities for people and businesses worldwide. With 22,500 employees across 32 countries, they foster a culture of innovation and data-driven solutions.
Build ML infrastructure for low-latency model deployment, distributed inference pipelines, and real-time telemetry.
Scale ranking systems by moving models from experimentation to production, optimizing latency and cost trade-offs.
Implement model CI/CD for automated versioning, canary releases, hot-swappable container rollouts, and zero-downtime rollbacks.
Sequen provides an integrated platform that pairs cutting-edge frontier ranking models with infrastructure to run them in production at sub-10ms latency and enterprise scale. They are a small, highly technical, early-stage team focused on turning recent AI advances into production-grade systems.
Collaborate with data scientists and software engineers to build scalable data pipelines and ML deployment systems.
Troubleshoot issues across the ML infrastructure stack, from Linux and Docker to Kubernetes and model serving.
Drive high engineering standards through code reviews, testing, and CI/CD enhancements.
Quillbot helps students and professionals strengthen their writing with AI-powered tools. We serve over 56 million users globally and foster a collaborative, virtual-first culture.
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, 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.
Drive migration of legacy Hadoop/Spark/Impala data pipelines to a modern Databricks-centric stack.
Design and build scalable Airflow DAGs and Databricks Jobs for large-scale data pipelines.
Implement robust validation strategies to ensure data parity and quality between legacy and modern systems.
LivePerson is a leader in trusted enterprise conversational AI and digital transformation. Named the #1 Most Innovative AI Company by Fast Company, we power nearly a billion conversational interactions every month for top global brands.
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.
Design and maintain scalable ML infrastructure including data pipelines, training workflows, and model deployment systems.
Own end-to-end ML lifecycle operations, ensuring reliable delivery of models into production at scale.
Implement monitoring, telemetry, and feedback loops for ML models running across large-scale device fleets.
Our partner company develops ML systems for connected hardware products used by customers worldwide. They operate in a fast-paced, product-driven environment with a collaborative and technically ambitious culture focused on real-world ML impact.
Design, deploy, and optimize production-grade machine learning systems for the full ML lifecycle.
Build scalable MLOps platforms, CI/CD workflows, and model serving infrastructure.
Collaborate with engineering teams to improve platform scalability, security, and operational best practices.
They build scalable MLOps infrastructure for enterprise AI solutions. They foster a collaborative, remote-first culture focused on innovation and professional growth.
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.
Design and develop scalable batch and streaming data pipelines for customer experience analytics.
Build and optimize production-grade ETL/ELT workflows and data warehouse architectures.
Enable AI and machine learning analytics by developing curated datasets and feature pipelines.
itD is a consulting and software development company that blends diversity, innovation, and integrity. The company is woman- and minority-led and empowers employees to deliver great results.
Collaborate with Data Science, Product Managers, and Software Engineers to build robust ETL pipelines for user-facing features.
Contribute to architecture decisions, observability tooling, and data quality initiatives to keep the platform robust.
Enforce engineering best practices across the AI/ML org, including code quality, testing, and documentation.
Federato is an AI-native platform for insurance, enabling insurers to provide affordable coverage for climate, cyber, and social inflation risks. It is a small, well-funded company backed by the investors behind Salesforce, Veeva, and Zoom, with a culture focused on first principles, learning, and fun.
Assist TSD with data products by providing expertise on data engineering methods and best practices.
Design, implement, and maintain efficient data architecture and ELT/ETL pipelines in Azure Synapse and Azure Machine Learning.
Incorporate source control, quality controls, and documentation for all pipelines and data assets.
Integres, LLC is a Service-Disabled Veteran Owned Small Business providing IT solutions. They cultivate a corporate family culture emphasizing work/life balance and servant-leadership.
Design, build, and maintain scalable data and ML pipelines for analytics and AI systems.
Build and optimize workflows for structured and unstructured data, enabling semantic search and RAG use cases.
Manage and optimize vector databases and indexing strategies for efficient retrieval and AI-powered search.
This is a partner company seeking a Data & Machine Learning Engineer based in Brazil. They operate in a highly technical and global environment with strong emphasis on scalability, performance, and innovation.