Architect and develop robust, end-to-end machine learning solutions, managing the complete ML lifecycle from development to production.
Collaborate closely with data engineers and data scientists to create highly scalable solutions and integrate them across the software development life cycle.
Evaluate cloud solutions for performance and cost-efficiency, and communicate technical concepts clearly to stakeholders and teams.
Coderio designs and delivers scalable digital solutions for global companies, combining strong technical expertise with a product mindset to lead complex software initiatives end-to-end. They work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.
Lead design and implementation of data science initiatives from problem definition to production deployment.
Develop, evaluate, and optimize machine learning models on AWS, owning the full data science lifecycle.
Mentor data professionals and partner with stakeholders to drive measurable business value.
The company is a partner of Jobgether, providing data science and machine learning solutions for complex business challenges. It offers a collaborative remote environment with experienced professionals and strong autonomy.
Drive the technical and product roadmap by contributing innovative ideas and estimating effort for high-velocity execution.
Collaborate with product managers and engineers to translate abstract business needs into scalable technical implementations.
Own end-to-end responsibility for complex initiatives, from scoping with stakeholders to production deployment and maintenance.
TrueML is a mission-driven financial software company that uses machine learning to create better digital experiences for distressed borrowers. The team includes inspired data scientists, financial services experts, and customer experience fanatics building technology to ensure nobody gets locked out of the financial system.
Drive and continuously improve MLOps practices across the machine learning environment.
Build, optimize, and maintain CI/CD pipelines using GitLab for reliable ML delivery.
Productionize and maintain machine learning models using AWS, with a focus on SageMaker.
The company operates a globally deployed recommender system and focuses on machine learning infrastructure. The team is collaborative and supportive, with an emphasis on knowledge sharing and professional development.
Lead the design and implementation of data science initiatives, defining methodologies and best practices.
Develop, evaluate, and optimize machine learning models to solve complex business problems.
Own the complete data science lifecycle from data exploration to deployment and monitoring.
Coderio designs and delivers scalable digital solutions for global companies. We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end, working with international clients and building long-term partnerships through technical excellence.
Own the ML/AI platform, including training infrastructure, model serving, inference pipelines, and production integrations.
Set technical direction for ML/AI architecture, tooling, standards, and strategy in partnership with data science and engineering.
Drive GenAI and LLM engineering, including RAG, prompt engineering, fine-tuning, and agentic workflows.
This company builds AI/ML infrastructure for financial technology products used by over 1,600 financial institutions. It operates as a globally distributed team with a focus on innovation and collaboration.
Design, develop, and maintain MLOps pipelines on AWS to automate and operationalize machine learning models.
Collaborate with Data Scientists to deploy, monitor, and scale ML solutions in production environments.
Architect cloud-based systems, integrate APIs, and build web applications and LLM-powered agents.
The company is a partner of Jobgether, specializing in cloud and AI solutions. It fosters a collaborative, innovation-driven environment with a focus on professional development and employee well-being.
Design, develop, and deploy foundational AI and ML models, building robust, scalable pipelines for advanced analytics.
Champion top-tier coding, testing, and MLOps practices, navigating ambiguity to refine pipelines and elevate workflows.
Partner with cross-functional stakeholders to convert strategic needs into technical specs and embed ML features into live applications.
Wave helps small businesses thrive so the heart of our communities beats stronger. They create an environment buzzing with creative energy and inspiration, valuing boldness, quick learning, and generous knowledge sharing.
Build and deploy production-grade LLM inference systems from scratch, owning the pipeline from query to response.
Optimize inference workloads for latency, throughput, and cost using tools like vLLM, SGLang, and TensorRT-LLM.
Collaborate with the CTO and Product to define the technical roadmap for inference infrastructure as the organization scales.
The company is an open-source-oriented startup building production-grade inference infrastructure for large language models. It is a remote-first, globally distributed team that values engineering ownership, speed, and customer impact.
Develop and deploy production-ready AI solutions using Python, Azure, and LLMs.
Collaborate with cross-functional teams to translate business challenges into scalable applications.
Manage MLOps, CI/CD pipelines, and containerized deployments in an Agile environment.
Jobgether is an AI-powered job platform that matches candidates with roles using objective, fair reviews. It processes applications and shares shortlists with hiring companies, supporting a global remote workforce.
Lead the architectural design and development of scalable AI/ML pipelines for enterprise initiatives.
Provide technical leadership and mentorship to AI/ML engineers and data scientists.
Deploy and manage advanced models including LLMs and Generative AI in production environments.
They are an organization focused on delivering enterprise AI and Machine Learning solutions. They offer a fully remote, flexible work environment with a strong emphasis on professional growth and collaboration.
Build and own the model serving infrastructure, real-time inference, feature retrieval, and the latency budget that governs both.
Build the deployment path for data scientists to ship models, including bring-your-own-model support.
Own models in production: monitoring, drift detection, retraining, incident response, and the on-call rotation.
Sardine is the leading agentic risk platform for fighting financial crime. We are a remote-first company with hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo, hiring talented individuals with extreme ownership and high growth orientation.
Build AI-powered tools and copilots across the SDLC to reduce cognitive load and eliminate manual steps.
Research and deploy GenAI solutions to improve delivery pipelines and system reliability.
Collaborate with Platform, SRE, and DevOps teams to integrate intelligent automation into the core engineering platform.
Coderio designs and delivers scalable digital solutions for global companies. They combine strong technical expertise with a product mindset and value autonomy and clear communication.
Design, build, and operate scalable backend services, APIs, and data pipelines for ML-driven personalization.
Improve reliability, performance, and observability of production ML systems, including model versioning and safe rollout.
Collaborate with data scientists and product engineers to translate business needs into robust technical solutions.
Hungryroot uses AI to build a consumer-centric food and wellness company, acting as a personal assistant for healthy living by recommending and delivering healthy groceries, recipes, and supplements. They are a distributed team across 28+ US states with a remote-first culture emphasizing collaboration, flexibility, and an annual company retreat.
Build and operate model and inference serving infrastructure, managing latency, throughput, autoscaling, and reliability for real-time and batch inference.
Own the ML deployment lifecycle: model registry, versioning, promotion workflows, rollout strategies, and safe rollback.
Operate agentic and LLM workloads in production, managing inference providers, gateways, quotas, guardrails, and graceful degradation under load.
ReadyOn is an AI-native Labor Operating System that redefines how enterprises manage frontline labor by matching workers to shifts in real time. Headquartered in San Francisco with over 100 employees, it grew revenue 8x year over year in 2025.
Design, build, deploy, and maintain scalable machine learning and AI systems in GCP to solve complex business problems and create new value.
Partner across teams to understand problem definitions, data needs, and solution approaches, and support model deployment with MLOps practices.
Take ownership of production issues, perform root cause analysis, and improve documentation and quality assurance processes for ML systems.
General Mills makes food the world loves, operating across 100+ markets. As a large company, it prioritizes being a force for good and fosters a culture of bold thinking and big hearts, where employees challenge each other and grow together.
Develop tools and automate manual processes to improve operational efficiency and accelerate experimentation.
Build, integrate, and monitor end-to-end lifecycles of large-scale distributed machine learning systems.
Enhance ML pipelines for forecasting platforms with automated retraining and deployment.
Apella applies computer vision and machine learning to improve the standard of care in surgery. They are a remote-first startup focused on building reliable ML solutions for healthcare.
Design, build, and operate production-grade reusable AI capabilities and services adopted by multiple engineering and product teams.
Build and evolve LLM gateways, proxies, model routing, and agentic workflows such as LangGraph and MCP.
Define standards for production AI adoption including automated testing, versioning, and incident response.
Coderio designs and delivers scalable digital solutions for global companies, combining technical expertise with a product mindset to lead complex software initiatives. They work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.
Operate and evolve AWS infrastructure for Data/AI platforms, ensuring security, scalability, and high availability.
Build CI/CD pipelines, automate provisioning with Terraform, and implement observability.
Collaborate with Data, AI, and Infrastructure teams, document standards, and drive platform improvements.
The partner company is building a modern Data Platform team focused on secure, scalable, and highly available infrastructure for Data and AI workloads. The culture emphasizes DevOps, automation, and continuous improvement, with close collaboration across Data, AI, and Infrastructure teams.