Developer Relations Jobs

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries fo

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

About the Role This role will serve as a key execution partner to the GenAI Customer Compliance Manager, with a strong focus on supporting GenAI delivery workflows through embedded compliance operations and Legal coordination. The GenAI Compliance Operations & Programs Associate will sit at the intersection of Delivery, Ops, and Legal, ensuring that compliance considerations are integrated early in the project lifecycle, risks are clearly identified and prioritized, and Legal is engaged with the right context at the right time. By owning execution, coordination, and delivery integration, this role frees the Customer Compliance Manager to focus on strategy, governance, and risk frameworks. The role requires strong operational ownership, comfort with ambiguity, and the ability to drive alignment across fast-moving, cross-functional teams. Key Responsibilities Compliance Review Operations & Legal Coordination Manage end-to-end compliance review workflows for GenAI projects — from early-stage intake through review, approval, launch, and verification — in close partnership with Engagement Management and Delivery. Evaluate incoming work for compliance risk signals (e.g., data sensitivity, copyright exposure, privacy concerns); triage and prioritize requests for Legal based on risk, scope, and delivery timelines. Partner with Engagement Management to translate and execute risk mitigation at both the project and customer level, gather operational input to develop and prioritize systematic compliance controls, and train/educate Ops stakeholders on common or emerging compliance risks. Ensure Legal receives clear, structured, and actionable context; coordinate reviewers across Legal and internal teams to support SLA adherence. Identify workflow friction points and contribute to improving processes, templates, and prioritization frameworks. Maintain dashboards to track throughput, bottlenecks, SLAs, and risk trends. Risk Mitigation Solutions & Monitoring Support Eng

Role Summary The Support Team Manager is responsible for the day-to-day leadership and performance of a team of Support Specialists, serving as the primary connection between frontline agents and broader operational leadership. This role balances hands-on people management with operational oversight, including but not limited to coaching team members, driving performance outcomes, managing escalations, and ensuring contributors receive consistent, high-quality support experiences. The ideal candidate leads with curiosity, communicates proactively, and holds themselves and their team to a high standard of accountability, quality, and continuous improvement. Success in this role requires strong judgment, a people-first mindset, and the ability to thrive in a fast-paced, evolving environment. Key Responsibilities Team Leadership & Coaching: Lead, coach, and develop a team of Support Specialists (Tier 1-3) through regular 1:1s, structured feedback, and performance conversations. Foster a collaborative, accountable, and high-performing team culture. Recognize strong performance and address performance concerns in a timely and constructive manner. Performance Management: Monitor and evaluate team performance across quality, productivity, CSAT, SLA attainment, and adherence metrics. Identify trends, surface insights, and create action plans to drive continuous improvement at both the individual and team levels. Operational Oversight: Manage day-to-day team operations including ticket queue health, schedule adherence, coverage coordination, and shift handoffs. Ensure workflows, policies, and documentation are consistently followed and updated as processes evolve. Escalation Management: Serve as the primary escalation point for complex or unresolved contributor issues. Support agents with difficult tickets, providing guidance and decision-making to ensure timely, high-quality resolutions with complete documentation. Reporting & Analytics: Track and report on team per

As a member of our operations team, you will be accountable for driving revenue by ensuring that Scale AI meets customer commitments in a timely manner while maintaining the highest quality standards. You will manage our supply operation funnel by building and running solutions, tools, and processes by working with a cross-functional team including Customer Operations, Product Operations, Product Managers, and many others. You will be solving problems no one has solved before, and you will need to be relentless in driving stellar results, running pilots, tests, and experiments. You’ll come up with creative solutions to bottlenecks. The blend of operations and ownership of our most important outcomes make this a unique and exciting role at the heart of Scale’s daily operations.The ideal candidate is scrappy, analytical, empathetic, outcome focused, and above all someone who drives and inspires results. You will: Build and drive some of our most critical operational processes Own the day-to-day delivery of customer commitments Create an effective feedback loop between the front line, product, strategy, and customers Collaborate with stakeholders to improve processes for new and existing customers Ideally you'd have: Advanced English skills Industry experience (+2) in an operational role and/or a top-tier consulting firm An undergraduate degree with an analytics heavy major (e.g., Engineering or Economics) and/or a graduate degree in Engineering, Economics, or Business An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results Analytical, planning, and process improvement capability Experience with reading SQL, or have demonstrated analytical skills PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems

Role Summary The Support Enablement Manager builds and scales the training, onboarding, and quality-assurance programs that power a high-performing contributor-support team. The role owns the full enablement lifecycle — from designing and delivering onboarding curricula to formalizing QA frameworks that drive measurable improvement across the support organization. Enablement priorities are set in partnership with the Regional Manager; the Manager owns execution end to end within that scope and brings recommendations when scope needs to change. This is a hands-on leadership role: assess the landscape, prioritize, build the plan, lead a small team, and deliver results, working cross-functionally with Regional Managers, Team Managers, SMEs, and WFM. Key Responsibilities Own the enablement function end to end — assess gaps, prioritize initiatives, and drive them to completion within scope agreed with the Regional Manager; surface recommendations when scope should change. Onboarding & curriculum — own the end-to-end onboarding for new Support Specialists; design, build, and continuously improve structured training that reflects current workflows, tools, and contributor-experience standards, so agents ramp quickly and confidently. Coaching & development — build and maintain ongoing training across all tiers; partner with Team Managers to close skill gaps with targeted interventions that translate into performance improvement. Quality assurance — own the QA program: scorecard design, calibration, audits, and reporting; keep QA consistent, fair, and actionable, and require that quality feedback cite a current source document. Knowledge base / SSOT — own the support knowledge base and its review cadence so guides stay accurate and current, and retire stale content. Team leadership — lead, develop, and manage a small team of Enablement & QA Specialists; set priorities, coach, and keep the team unblocked and accountable to high-quality output. Cross-functional part

As a member of our Frontier Tech Consultant team, you will play a critical role in advancing cutting-edge AI innovations by conducting high-impact experiments and ensuring seamless execution at the highest quality standards. Your work will directly contribute to Scale AI’s growth, shaping the future of artificial intelligence. In this role, you will be working on various types of projects, including but not limited to: research experiments, dataset generation, data quality improvements, and in-depth technical analysis. You will tackle complex, technical and operational challenges while collaborating closely with Scale’s ML research scientists and SPM team. The ideal candidate is analytical, detail-oriented, and results-driven, with strong problem-solving abilities and excellent communication skills. We are looking for someone who thrives in a fast-paced environment, is proactive in overcoming challenges, and is committed to delivering exceptional outcomes. If you are eager to contribute to the forefront of AI innovation, we encourage you to apply. You will be responsible for: Design and execute research experiments Build and evaluate frontier LLM datasets Develop training and testing material for frontier pipelines Improve quality of existing and new products Ideally you’d have: Strong machine learning knowledge, either by being in the final years of a ML PhD career or having already graduated Strong writing and verbal communication skills An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results Analytical, planning, and process improvement capability Experience working in a fast-paced, entrepreneurial environment Technical skills including familiarity with Python, GPU, AWS, API, LLM, ML, and SQL Pay: $60-80/hr Commitment: This is a fully remote, US-based part-time (10-20 hours per week), on-going contract position staffed via HireArt. HireArt values diversity and is an Equal Opportunity E

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

About Eudia: Eudia is redefining the future of legal work with AI-powered Augmented Intelligence, enabling Fortune 500 legal teams to move faster, manage risk more effectively, and unlock new business value. Backed by $105M in Series A funding led by General Catalyst, we’re building a category-defining platform that blends AI-driven automation with human expertise, transforming legal from a cost center into a strategic growth driver. At Eudia, we move fast. Unlike traditional enterprise software, our teams ship solutions in days, not months—delivering real impact for some of the world’s largest companies, including Cargill, Coherent, DHL, and Duracell. We’re solving one of the most complex, unsolved challenges in AI: bringing trust, accuracy, and security to legal automation. We’re a team of builders, operators, and problem-solvers who are passionate about reshaping an industry that has long been resistant to change. If you’re looking for a place where you’ll be challenged, take ownership from day one, and work alongside some of the brightest minds in AI and legal —we’d love to meet you. About the Role: Are you interested in building a high-performance Agentic AI driven legal workflow system that supports our current and future scale of platforms? If so, we are looking for you to join our growing team in India. This person will work from our Bangalore office and actively collaborate with the Palo Alto team. We are looking for a Lead Software Engineer that will help develop the most secure, enterprise-grade software using and innovating the latest in Generative AI. The opportunity to tackle challenges in creating cloud-agnostic solutions, maintaining stringent security and compliance standards, and building scalable, resilient platforms for enterprise applications, data, AI, and search also exist while you will be able to routinely innovate on behalf of our customers, collaborating with the world's top

OUR MISSION At Redwood, we empower our customers with lights-out automation for their mission-critical business processes. ABOUT US Redwood Software is the leader in full stack automation fabric solutions for mission-critical business processes. With the first SaaS-based composable automation platform specifically built for ERP, we believe in the transformative power of automation. Our unparalleled solutions empower you to orchestrate, manage and monitor your workflows across any application, service or server — in the cloud or on premises — with confidence and control. Redwood’s global team of automation experts and customer success engineers provide solutions and world-class support designed to give you the freedom and time to imagine and define your future. Get out of the weeds and see the forest, with Redwood Software. CORE VALUES One Team. One Redwood Make Your Own Weather Obsess over Customer Success Work the Problem Be Curious Own the Outcome Respect Each Other YOUR IMPACT The L1 Support Team Leader is an experienced people leader responsible for managing a team of L1 Support Representatives, ensuring operational excellence, driving team performance, and improving processes. This role handles complex leadership scenarios, contributes heavily to quality, training, and continuous improvement efforts, and acts as a key operational anchor for the L1 organization. Regularly addresses complex staffing, performance, customer escalation, and operational challenges with minimum guidance. Influences improvements beyond the immediate team and contributes meaningfully to Support-wide initiatives. Lead, coach, and develop a full team of L1 Support Representatives, including performance management. Conduct structured 1:1s, team meetings, and continuous coaching to improve overall team capability. Manage operational KPIs (SLA, CSAT, backlog, resolution speed, etc) and create action plans to maintain or improve performance.