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.
Design, build, and optimize data workflows for Machine Learning and GenAI solutions in cloud environments.
Develop and deploy Machine Learning and Generative AI models using AWS SageMaker.
Create and manage data and model pipelines to improve the efficiency of AI and machine learning systems.
Netrix Global provides the people, processes, and technology to run and scale modern data-driven businesses. It is a top system integrator with a culture focused on ownership, teamwork, and respect.
You will experiment with emerging technologies and contribute to building new models and systems.
You will implement prototypes in Python and focus on delivering solutions to production.
You will partner with the platform engineering team to streamline MLOps workflows and maintain high code quality.
Verve creates a more efficient and privacy-focused way to buy and monetize advertising by fusing data, media, and technology. With 30 offices globally, they serve top advertisers and publishers and foster a collaborative, fun culture.
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.
Design and maintain scalable data pipelines for ingestion, transformation, and delivery into data warehouses, feature stores, and ML/AI systems.
Build workflows for processing unstructured data and develop semantic representations to enable advanced search, retrieval, and LLM-powered applications.
Collaborate with stakeholders to translate business requirements into scalable data and ML solutions.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. They use technology to review applications and share top-fitting candidates directly with employers, ensuring a fair and efficient hiring process.
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 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.
Own the ML serving API and deploy models to production with CI/CD and infrastructure as code.
Build monitoring, alerting, and reliability for NBA models and LLM agents.
Drive architectural decisions and mentor engineers on MLOps patterns.
Clutch is a vertical SaaS company backed by Andreessen Horowitz, revolutionizing how credit unions engage with members via fintech lending software. The company is small and ambitious, with a lean data team of five that values pragmatism and fast shipping.
Design, build, and automate enterprise-grade AWS SageMaker environments to support scalable machine learning initiatives.
Develop and implement DevOps automation for SageMaker Unified Studio and related cloud infrastructure.
Build and optimize CI/CD pipelines for deploying custom Docker images, kernels, and machine learning workloads.
This role is listed on behalf of a partner company that builds and optimizes enterprise-scale machine learning infrastructure. They operate with a collaborative international team and modern engineering practices.
Build end-to-end Machine Learning pipelines, including data preparation, code optimization, automated model training, and prediction workflows.
Provide technical leadership in MLOps processes, establishing best practices for development, deployment, and maintenance.
Design and implement cloud-based architectures for AI and data solutions using platforms such as GCP, AWS, or Azure.
A technology company specializing in data-driven solutions for consumers, leveraging AI and cloud technologies to transform data into insights. The company fosters a dynamic, innovation-driven culture with a remote-first approach, collaborating across multidisciplinary teams.
Build models and data products that go from prototype to production, including generative models and subscriber-behavior predictions.
Dig into large, messy datasets to uncover trends and patterns, and contribute to the core Python data science library.
Build LLM-powered pipelines and agents, with comprehensive evals to validate model responses.
DevSavant is an operating partner for startups and growth-stage companies, helping them turn ambition into execution. With over 8 years in venture-backed ecosystems, they are trusted to accelerate delivery and scale teams efficiently.
Drive end-to-end ML development for customer-facing SaaS products, from pipelines to production deployment and monitoring.
Design evaluation strategies and A/B tests to prove ML features improve customer outcomes and business impact.
Influence product roadmap by communicating ML capabilities and trade-offs to cross-functional teams.
WorkWave provides field service and logistics software solutions that help businesses manage their operations and serve their customers. They are a global company with a remote-first culture, recognized as a Best Place to Work and named among the top software companies worldwide.
Design, build, and maintain scalable machine learning infrastructure on AWS, including training and deployment pipelines.
Develop and deploy ML models for recommendation systems, fraud detection, credit risk, and personalization use cases.
Implement monitoring, logging, and alerting systems to ensure model performance, stability, and reliability in production.
Our partner is a fast-growing, innovation-driven company where machine learning and AI systems directly power large-scale fintech and commerce experiences. They foster a highly dynamic environment with strong emphasis on experimentation, rapid iteration, and measurable business impact.
Lead data initiatives using machine learning and AI to optimize ad delivery and platform performance.
Design, build, and maintain scalable AWS data pipelines for ML tooling and high-velocity ad systems.
Productionize forecasting and optimization models with robust backtesting, monitoring, and guardrail systems.
AdsByNimbus is a leader in Publisher-first mobile AdTech. The team is lean, highly capable, and deeply collaborative, offering high levels of project ownership and autonomy.
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 own architectural evolution of data pipelines and platform components using AWS and Snowflake.
Build and maintain robust ingestion pipelines with AWS DMS, AppFlow, and EventBridge.
Optimize analytics datasets in dbt Cloud with dimensional modeling and SCD Type 2 logic.
CodeRoad provides end-to-end software development services, helping businesses scale with ideal infrastructure solutions. It is a nearshore technology services company that empowers businesses to thrive in the digital landscape.
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.
Lead end-to-end AI project delivery, ensuring governance, stakeholder communication, and reliable execution.
Design and build robust RAG systems, agentic frameworks, and LLM-powered solutions for production environments.
Mentor junior engineers and contribute to proposals, solution design, and new business initiatives.
Blend is a premier AI services provider that co-creates meaningful impact for clients through data science, AI, technology, and people. With a mission to fuel bold visions, the company aligns human expertise with artificial intelligence, fostering innovation and value for its clients.
Build and maintain end-to-end deployment pipelines for AI-powered applications, including artifact builds, environment promotion, rollback, and observability hooks.
Stand up and operate the runtime and lifecycle infrastructure for production agents, including deployment, versioning, monitoring, rate-limiting, and retirement.
Design and build the shared developer harness that every AI-powered service uses: prompt management, model routing, retries, tracing, eval hooks, and policy enforcement.
RxSense is a healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. As a leader in SaaS technology for healthcare, the company offers innovative solutions with integrated intelligence on a single enterprise platform, connecting the pharmacy ecosystem.
Design and develop machine learning models for localization workflows, including machine translation and LLM finetuning.
Implement and optimize models using Python, TensorFlow, and deploy via Docker and AWS services.
Evaluate and select ML techniques, perform statistical analysis, and maintain clear documentation.
Welo Global is a leader in multilingual AI, technology, and content solutions serving over 2,000 clients in 300 languages. The company combines globally scaled multilingual infrastructure with a network of over 500,000 linguists and domain experts, backed by seven ISO certifications.