Design, build, and productionize machine learning and agentic AI functionality.
Partner with product engineering squads to embed AI capabilities into Arkestro's product.
Contribute to AI/ML architecture decisions and own evals and ground truth for your projects.
Arkestro's Predictive Procurement Platform applies AI, game theory, and behavioral science to enterprise negotiations, helping teams move from reactive supplier bidding to data-driven offers. It is a hyper-growth, remote-first startup with a collaborative culture focused on meaningful work and significant impact.
Design and own core components of the AWS environment supporting data science products, setting standards for infrastructure changes and AI agent interactions.
Build self-service CI/CD pipelines and automated triggers so scientists can ship models to production without hand-holding.
Maintain security, compliance, and reliability of cloud environments while shaping the platform roadmap to unblock scientists.
Penguin Random House is the leading trade book publisher in North America, the UK, and many other regions, publishing across all genres and age groups. It operates nearly 300 publishing brands and imprints, fostering a diverse and innovative global community.
Design, build, and operate AWS infrastructure supporting ML models, AI tools, and event-driven integrations.
Build reliable CDC pipelines and event-driven integrations with third-party systems like Salesforce and Braze.
Implement observability, secure operations, and model monitoring for production ML and LLM systems.
National Debt Relief helps consumers resolve debt and has settled over $10 billion for 450,000 clients. It is a certified Great Place to Work known for a team-oriented culture and employee growth.
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.
Build and ship statistical, ML, and hybrid LLM models on real claims data.
Design evaluations and gold datasets with subject matter experts to continuously measure product impact.
Collaborate with a small senior team to turn model results into product decisions for auto casualty.
CCC Intelligent Solutions is a leading cloud platform for the insurance economy, connecting insurers, repairers, automakers, and part suppliers. Empowering 35,000 businesses, the company fosters a culture of innovation, integrity, inclusion, and connection.
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.
Set technical vision and strategy for foundational model and user understanding roadmap.
Collaborate cross-functionally with vertical customer, horizontal signal, and infrastructure teams.
Lead and mentor a high-performing ML team, driving technical execution from ideation to deployment.
Reddit is a community of communities built on shared interests, passion, and trust, hosting open and authentic conversations. With 100,000+ active communities and approximately 130 million daily active unique visitors, it is one of the internet's largest sources of information.
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 the full ML lifecycle for Misdirected Email detection, from data wrangling to deployment and monitoring.
Run rigorous experiments and A/B tests, set thresholds, and conduct error analysis to prevent regressions.
Partner with product and engineering stakeholders to align deliverables and ensure successful GA launches.
Abnormal protects the humans behind the world's most critical organizations from AI-powered cybercrime. 5,000 enterprises trust our behavioral AI platform.
Build and maintain automated, tested ML/data pipelines to take data science models from notebooks to production.
Optimize CI/CD, workflow orchestration, and observability to keep match data reliable at scale.
Partner with data science to maintain feature pipelines, run EDA, and apply AI tools across workflows.
PAR Technology is a leader in restaurant technology, providing software and hardware that help brands create guest connections and drive growth. Serving over 100,000 restaurants in 110+ countries, it fosters a collaborative 'Better Together' culture within its growing SaaS organization.
Design and implement Python solutions using the full suite of AWS cloud computing capabilities.
Develop and iterate on AI and LLM-based workflows to reduce customer time-to-outcome.
Operate in a collaborative, agile remote environment, sharing knowledge and participating in peer code reviews.
Two Six Technologies builds, deploys, and implements innovative products that solve complex challenges, particularly in the information operations space for US government and Fortune 50 clients. The company emphasizes collaboration, trust, and pushing boundaries to empower its team and support customers in building a safer global future.
Lead design and deployment of enterprise-scale AI and data solutions.
Architect LLM and agentic AI workflows using frameworks like LangChain and n8n.
Partner with teams to deliver secure, compliant, and innovative solutions.
U.S. Financial Technology operates the largest mortgage securitization platform in the world, supporting Fannie Mae and Freddie Mac's Uniform Mortgage-Backed Security. The company supports 70% of mortgage-backed securities and combines financial services expertise with leading technologists.
Own and evolve AWS infrastructure powering real-time AI voice and workflow automation systems.
Drive reliability, scalability, and operational rigor across the multi-agent runtime.
Mentor engineers and design secure, compliant platform foundations for rapid product expansion.
Liberate builds AI agents to automate manual tasks for the $2.7T insurance industry, starting with voice and expanding into workflow automation. The fast-growing startup has raised $72M, including a $50M Series B in October 2025.
Design multi-step LLM systems for reasoning, retrieval, planning, and tool use.
Own evaluation from offline benchmarks to online experiments and model-graded review.
Set quality, latency, and cost targets, and mentor senior engineers.
They build enterprise AI systems, specifically agent systems for large customers. As a late-stage, venture-backed company, they focus on shipping reliable AI to enterprise clients.
Design, build, and deploy production ML and LLM-based systems for enterprise clients
Own technical delivery end-to-end, from architecture to deployment and monitoring
Mentor junior ML engineers and shape internal best practices and tooling
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, fast-growing team that values autonomy, open communication, and continuous learning.
Lead and support a senior team of Data Scientists and Machine Learning Engineers, driving career development and growth.
Partner with Product Management and Decision Science to shape the product roadmap and define success metrics.
Design, build, and deploy machine-learning pipelines for modeling jobseeker behavior and marketplace dynamics.
ZipRecruiter is a leading online employment marketplace powered by AI-driven smart matching technology. The company actively connects millions of businesses and job seekers through innovative mobile, web, and email services, with the #1 rated job search app.
Build machine learning models to personalize the product and connect users with suitable insurance policies.
Collaborate with cross-functional stakeholders, write production code, and perform peer reviews.
Analyze product data, design experiments, and explore causal measurement and ML platform improvements.
The Zebra provides online tools and licensed agents to simplify car and home insurance shopping. The company has helped customers compare over 74 million quotes since 2012 and was named an Austin Business Journal's 2026 Best Place to Work, with a culture that values diversity and inclusion.
Own the outcome from customer need to shipped agent, improving quality, coverage, and experience.
Build production agents and tools on Amazon Bedrock, turning serving layers into capabilities.
Measure groundedness, adoption, and impact, then diagnose and iterate to ship reliable answers.
WorkWave builds AI-powered software, including the in-product assistant AskWaive, to help customers make better decisions. They offer a flexible, collaborative remote environment and value trust, inclusion, and impact.
Develop, train, and optimize machine learning models using Python and common ML libraries.
Support data preprocessing, feature engineering, and CI/CD integration for scalable ML solutions.
Collaborate with data engineers and stakeholders in an Agile environment to align ML solutions with business needs.
Makpar is a professional and technical solutions provider for the Federal government, specializing in cloud engineering, data management, cybersecurity, and emerging technologies. The company's connected and engaged workforce is dedicated to delivering success for clients and the American people.