Design, deploy, and optimize large-scale ML systems for retrieval, ranking, and LLM-powered features.
Lead ML projects from concept to production, improving answer relevance and user experience.
Collaborate with Product, Data Science, and Engineering teams to shape technical direction.
The hiring partner is a technology company focused on building advanced AI systems that help users discover relevant answers from large collections of online conversations. It values innovation, collaboration, and responsible AI development, offering a remote work environment within the United States.
Own end-to-end ML systems from data and training to evaluation, inference, and deployment.
Build and evolve training, fine-tuning, and inference infrastructure for large models.
Partner with research and application engineering to turn model capabilities into product improvements.
Next Step Systems is an IT recruiting and staffing agency that connects companies with machine learning and technology talent. They specialize in placing candidates in remote and on-site roles across the United States and emphasize a fast-paced, results-oriented culture.
Lead the end-to-end machine learning lifecycle, from data preparation and model training to evaluation, inference, and deployment.
Build and optimize scalable training, fine-tuning, and inference pipelines for large-scale models on GPU infrastructure.
Establish production best practices for model quality, reliability, safety, and measurable performance improvements.
This company builds production-grade machine learning systems and large-scale GPU-powered inference pipelines. It is a fully remote team that values technical rigor, collaboration, and hands-on engineering.
Own end-to-end performance optimization for production ML workloads, from bottleneck identification to rollout.
Diagnose ML performance bottlenecks across model execution, frameworks, runtimes, memory, and CPU/GPU utilization.
Design and implement improvements in inference execution, runtime behavior, batching, memory management, and precision.
Reddit is a community of communities, hosting open and authentic conversations across the internet. With over 100,000 active communities and approximately 130 million daily active users, it is one of the web's largest sources of information.
Build core machine learning systems that power a proactive, long-horizon AI product.
Own work end-to-end, from data preparation through training, evaluation, inference, and iteration.
Debug model failures using production signals and iterate quickly to ship reliable systems.
Gina's Tech Jobs is an IT recruiting and staffing agency that connects companies with technology professionals. They help organizations hire for roles such as machine learning engineers and other IT positions across the United States.
Build the component layer around our layout synthesis engine, including API contracts, services, and evaluation gates.
Turn model retraining into a one-command job with built-in benchmarks and readable results for the whole team.
Own latency and cost budgets for learned capabilities and partner with infrastructure engineers on MLOps and deployment.
Higharc is a VC-backed startup that is changing how new homes are designed and built using spatial AI and generative floor plan technology. The company is fully remote, has raised over $175M, and values flexibility, collaboration, and asynchronous deep work.
Run experiments that improve classification accuracy and ship winners to production.
Design and iterate on classifiers using prompting, retrieval, fine-tuning, and multi-model approaches.
Build evaluation sets and metrics; collaborate with clinical ops and legal teams.
Truemed enables health and wellness merchants to accept HSA/FSA funds by determining product eligibility for pretax spending. We are a Series A startup supporting brands like Peloton, focused on helping people invest in healthy habits.
Design and train advanced ML models (e.g., DNNs, transformers) to power Reddit Ads Ranking.
Develop and optimize features including embeddings, contextual signals, and cross-session behavior.
Mentor other MLEs and contribute to modeling best practices across the organization.
Reddit is a community of communities built on shared interests, passion, and trust. With over 100,000 active communities and approximately 130 million daily active unique visitors, it is one of the internet's largest sources of information and employs a flexible first workforce.
Design, build, and maintain scalable real-time ML services for ranking and personalization.
Analyze user behavior and run A/B tests to improve product discovery and engagement.
Collaborate with engineers, data specialists, and business stakeholders to drive measurable outcomes.
The company is an AI-driven e-commerce platform that uses machine learning to power smarter search, discovery, and shopping experiences. It maintains a collaborative, remote-first culture that values ownership, inclusion, and meaningful impact.
Own high-impact ranking models powering personalized feeds and digest emails.
Work across the full ML lifecycle, from data pipelines to production deployment.
Collaborate with a distributed engineering team on modern recommendation techniques.
They operate a large-scale knowledge-sharing platform. The company values autonomy, continuous learning, technical excellence, and thoughtful experimentation.
Build and operate production ML systems for recommendations, ranking, and personalized action selection across Stripe's Growth Platform.
Improve contextual bandit and policy-learning approaches, including exploration, reward design, and adaptive user feedback.
Develop reliable data and feature pipelines, reusable tooling, and online experiments to drive measurable business outcomes.
Stripe is a financial infrastructure platform for businesses of all sizes, enabling payments and revenue growth. With millions of companies as customers, Stripe fosters a culture of passion, grit, and integrity while working to increase the GDP of the internet.
Improve existing machine learning ranking models using core coding skills and ML knowledge.
Take end-to-end ownership of machine learning systems from data pipelines to production integration.
Identify new opportunities to apply machine learning to different parts of the Quora product.
Quora is a global knowledge sharing platform and Poe, a cloud workspace for AI agents. It is a privately held, remote-first company with a culture rooted in transparency, idea-sharing, and experimentation.
Build new functionality within a fast-moving product, taking ambiguous ideas from design to rigorous experimentation within weeks.
Conduct deep-dive research into state-of-the-art LLM orchestration, retrieval strategies, and data-driven personalization.
Build production-grade ML systems at Twilio scale, leveraging the latest AI development stacks to focus on core differentiation.
Twilio is a cloud communications platform that enables businesses to create personalized customer experiences through APIs and AI-driven solutions. The company is remote-first, serving hundreds of thousands of businesses, and fosters a culture of connection, inclusion, and innovation.
Design and build systems that improve the efficiency of ML training and inference workloads.
Develop tooling and benchmarking frameworks to help ML engineers debug, profile, optimize, and monitor model performance.
Partner with ML teams to optimize distributed training, reduce costs, and drive technical strategy for scalability and reliability.
Reddit is a community of communities where users share interests and authentic conversations. With 100,000+ communities and ~130 million daily visitors, it has a flexible-first culture supporting remote work.
Lead exploration and application of Large Language Models and Generative AI into core product lines.
Translate the latest research into high-performing systems that enhance customer experiences.
Collaborate with cross-functional teams to set strategy and deploy ML solutions with real business impact.
Replicant is the industry leader in voice AI for customer service, providing automated phone bots for enterprises like AAA and Fanatics. Founded in 2017, the company is backed by top-tier Silicon Valley investors, has offices in the SF Bay Area, Toronto, and New York, and maintains a distributed team across the US and Canada.
Develop deep understanding of customer problems and map them to Cohere solutions as a trusted technical advisor.
Lead design and deployment of customer pilots, owning the technical narrative from discovery to business case.
Collaborate with Product and Engineering teams and partners to scale solutions and gather customer feedback.
Cohere is a leading security-first enterprise AI company building cutting-edge foundation AI models and products for real-world business problems. It is a global team of researchers, engineers, and designers headquartered in Toronto with offices worldwide, committed to driving AI adoption.
Build inference systems powering RL research, scaling toward 1–3T parameter models on NVL72 clusters.
Optimize rollout throughput, multi-node MoE inference, and weight-update overhead for long-horizon agents.
Collaborate with model researchers on architecture choices balancing model quality and execution cost.
Prime Intellect is building the open superintelligence stack, unifying compute, environments, and deployment for frontier-scale AI post-training. Backed by $150M in funding, the team is mission-driven and hard-working, focused on accelerating open AI research.
Design, train, and deploy ML models for text classification, entity extraction, and topic detection.
Build LLM-powered features including RAG, prompt design, and agentic workflows.
Collaborate daily with US-based engineers and productionize models as monitored services.
Tech Holding is a full-service consulting firm that delivers predictable outcomes and high-quality solutions to clients from startups to Fortune 50 companies. The culture is built on deep expertise, integrity, transparency, and dependability, with a team of experienced industry professionals.
Build and extend pretraining code to scale experiments into full training runs.
Evaluate model architecture changes and optimize training throughput and resilience.
Run controlled ablations and collaborate with data and evaluation researchers.
Prime Intellect is building an open superintelligence stack, providing the infrastructure and platform for frontier AI training and deployment. The company has raised $150M from top investors and boasts a mission-driven team working to decentralize AI.