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.
Evolving the AI knowledge platform with retrieval, indexing, and synthesis for organization-wide use.
Architecting and operating agentic infrastructure on AWS with cost guardrails and observability.
Partnering with product engineering to define the AI platform API surface and building reference agent implementations.
ShiftKey is a healthcare workforce marketplace that connects facilities with licensed professionals to fill shifts, addressing staffing shortages. The company fosters an inclusive and collaborative culture, valuing diverse perspectives.
Design, build, and operate high-load distributed backend services powering the company's ML infrastructure.
Take end-to-end ownership of core ML services and data pipelines from design to deployment and continuous improvement.
Partner with ML and product teams to understand their needs and turn them into reliable, reusable platform capabilities.
Constructor is an AI-first e-commerce search and discovery platform that helps shoppers find products and enables brands to drive revenue. The company is fully remote, diverse, and values ownership and collaboration.
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.
Design, train, and ship ML systems for governance and security like anomaly detection and trust scoring.
Build data pipelines, model serving, evaluation frameworks, and feedback loops.
Set technical direction, own architecture, and help recruit and mentor as the team grows.
Docker provides developer tooling trusted by over 20 million monthly users and billions of container pulls. They are a globally distributed, remote-first team building tools for software delivery.
Develop, deploy, and maintain production-grade Machine Learning models in cloud environments.
Build, maintain, and optimize data pipelines and monitor model performance post-deployment.
Partner with engineering, data, and business stakeholders to translate goals into scalable ML solutions.
In All Media is a global technology and design firm building impactful digital solutions through remote, distributed teams across LATAM. They partner with international clients across industries, providing long-term technical expertise and team augmentation.
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, deploy, and optimize machine learning models that process large volumes of complex, unstructured data.
Develop and maintain scalable ML pipelines capable of supporting millions of documents and diverse customer requirements.
Lead technical initiatives from early experimentation through production implementation and ongoing improvement.
The company develops intelligent automation solutions using AI and machine learning for large-scale document processing. It offers a highly autonomous engineering environment with a focus on continuous improvement and innovation.
Design, develop, and deploy production-grade AI-powered backend systems integrating LLMs and traditional ML models.
Integrate and optimize vector databases for RAG pipelines, and write clean, well-structured Python code.
Debug complex cross-layer issues and collaborate with product and engineering teams to deliver cohesive solutions.
We are a fast-growing product company integrating cutting-edge AI capabilities into our core offering to deliver exceptional value to customers. Our small, fast-moving team works on practical, real-world AI applications with high autonomy.
Design, deploy, and maintain scalable ML infrastructure for model training, batch processing, and real-time inference.
Build and manage cloud-based infrastructure with AWS and Snowflake using Infrastructure-as-Code practices.
Develop CI/CD pipelines, automation frameworks, and monitoring for ML systems to improve reliability and governance.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. They operate with a team-oriented culture and offer remote work flexibility, focusing on efficient, unbiased recruitment.
Design and implement end-to-end document intelligence pipelines on AWS, including ML model development for document classification and field extraction.
Build scalable data processing systems handling PDFs up to 2000 pages, and own features from research through production deployment and monitoring.
Collaborate with subject matter experts to refine requirements, establish evaluation frameworks, and ensure extraction accuracy.
Exadel is an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients including HBO, Microsoft, Google, and Starbucks. Our culture is defined by ambitious, collaborative, and constantly evolving people who lead with trust, respect, and purpose.
Work directly with customer engineering teams to design and implement real-time applications on the LiveKit platform.
Architect scalable solutions for voice AI and developer platforms, building prototypes and reference implementations.
Debug production issues, lead technical workshops, and translate customer needs into product improvements.
LiveKit builds infrastructure for the agentic era of computing, enabling developers to build, test, deploy, and scale AI agents in production. Founded in 2021, the company powers voice and agentic AI for leading enterprises like OpenAI, Salesforce, and Meta, with a focus on innovation and collaboration.
Design, build, and deploy production ML and LLM-based systems (RAG, agentic workflows, fine-tuning, embeddings) for enterprise clients.
Own technical delivery end-to-end: from architecture and prototyping to deployment, monitoring, and iteration.
Mentor and support other ML engineers on the team with code reviews, technical guidance, and knowledge sharing.
TensorOps is a boutique AI consultancy that bridges strategy and execution, designing and shipping production-grade AI systems for enterprise clients. We are a 100% remote team of 11+ people, partnering with unicorns and NASDAQ-listed companies, and have a culture of autonomy, open communication, and continuous learning.
Evolving the AI knowledge platform with retrieval, indexing, and synthesis layer for organization-wide use.
Architecting and operating agentic infrastructure on AWS for multi-step AI systems.
Designing graph-based retrieval across data sources for multi-hop queries.
ShiftKey is a healthcare workforce marketplace that connects facilities with licensed professionals to fill shifts, mitigating staffing shortages. The company is in a high-growth phase with a friendly and engaging work environment.
Build AI platform and production systems supporting computer vision, perception, simulation, and mapping products.
Own critical parts of the AI platform, including orchestration, APIs, and deployment patterns.
Partner with data scientists and simulation engineers to reduce iteration friction and design production architecture.
HERE Technologies is a location data and technology platform company that empowers customers to achieve better outcomes. The company is an equal opportunity employer with a focus on innovation and inclusion.
Build and iterate on end-to-end ML solutions for misdirected email detection.
Collaborate cross-functionally to turn customer needs into product improvements.
Run rigorous experiments and evaluations to ensure reliable detection.
Abnormal protects organizations from AI-powered cybercrime using its behavioral AI platform. Trusted by 4,500+ enterprises, the company focuses on securing email, identity, and AI systems.
Own end-to-end Machine Learning (ML) system execution including data pipelines, training, and deployment.
Fine-tune and adapt models using state-of-the-art methods like LoRA and DPO.
Architect scalable inference systems and collaborate closely with application engineering.
This company develops advanced production-grade machine learning systems. The team is small and high-trust, with a culture of ownership and pragmatism.
Own end-to-end delivery quality for major engagements, translating ambiguous client needs into practical execution plans.
Lead solution architecture and technical decision-making, making pragmatic tradeoffs between speed, quality, and client value.
Build and ship production AI/ML systems using Python, ML frameworks, and cloud-native infrastructure while mentoring other engineers.
Eliza is a technology services company and Advanced-tier OpenAI partner that helps organizations build and deploy AI solutions, from generative AI to predictive analytics. They are a collaborative, mission-driven team focused on real-world AI impact.
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 solutions in Python using AWS cloud computing capabilities, including developing AI and LLM-based workflows.
Operate in a collaborative, agile environment with a focus on enabling team success and creating proofs-of-concept and production solutions.
Engage with peers to ensure maintainable solutions and share knowledge across the company.
Two Six Technologies builds, deploys, and implements innovative products that solve complex challenges for US government and Fortune 50 clients. The company fosters a culture of collaboration and trust, empowering its team to push boundaries and support customers in building a safer global future.