Runware

Role Description Join Runware as a Senior Machine Learning Engineer and be at the forefront of developing innovative AI solutions across various media modalities including text, image, video, 3D, and audio. We're building a powerful AI media creation platform designed to revolutionize how content is generated. As a Senior Machine Learning Engineer, you’ll take the lead on critical projects, guiding the end-to-end lifecycle from research and experimentation to production deployment and performance monitoring. Your work will help shape the capabilities of our platform and enhance the experiences of users who rely on our cutting-edge AI technologies. What You'll Be Doing - Integrate open-source and third-party models into our inference platform - Lead fine-tuning initiatives (LoRA, adapters, PEFT, domain adaptation) - Optimise inference workloads for latency, batching, memory efficiency, and throughput - Benchmark model quality vs cost vs performance across modalities - Improve inference startup times and stability under high load - Build evaluation frameworks and internal tooling for model validation - Work closely with Infrastructure and Backend teams on scalable serving systems - Monitor production performance and drive continuous optimisation - Mentor engineers and help raise the ML engineering bar across the team Qualifications - Proven experience delivering ML systems to production environments - Strong, low-level Python skills and deep hands-on experience with PyTorch - Experience working with diffusion models, LLMs, or multimodal architectures - Practical experience fine-tuning large models (LoRA, PEFT, adapters, etc.) - Experience optimizing inference workloads in GPU environments - Strong understanding of model evaluation, experimentation, and monitoring - Ability to debug performance, memory, and reliability issues in production - Strong systems thinking understanding how ML decisions impact infrastructure - High ownership and comfort operating in a fast-paced startup environment Requirements - Experience with vLLM or custom inference servers - Experience with Kubernetes or containerised ML workloads - Experience working in high-throughput distributed systems - Background in AI media generation (image, video, audio) - Experience building internal ML tooling or developer-facing APIs - Experience with kernels in CUDA/C++ Benefits - Generous paid time off – vacation, sick days, public holidays - Meaningful stock options – share in the upside you create - Remote-first setup – work from home anywhere we can employ you - Flexible hours – own your schedule outside core collaboration blocks - Family leave – paid maternity, paternity, and caregiver time - Company retreats – twice-yearly gatherings in inspiring locations

• Own and negotiate strategic model-provider relationships: Manage and deepen relationships with the leading generative media model providers - spanning frontier labs, generative media model creators, open-source communities, audio and 3D model providers, and inference infrastructure partners. Our current ecosystem includes partners such as Google, OpenAI, Black Forest Labs, ElevenLabs, Luma AI, ByteDance, Runway, and Ideogram, among many others across image, video, audio, and 3D modalities. You will own the full commercial relationship end-to-end and maintain strong visibility into partner roadmaps, launches, pricing changes, model capabilities, and strategic opportunities. • Negotiate best-in-market commercial terms: Lead negotiations on pricing, volume commitments, credits, preferred access, support levels, SLAs, roadmap visibility, co-marketing, launch support, enterprise terms, and non-standard strategic deal structures. • Turn partnerships into business value: Identify and execute opportunities that improve product capabilities, reduce costs, improve margins, accelerate model launches, enhance customer experience, or differentiate Runware in the market. • Coordinate across internal teams: Act as the connective tissue between model providers and Product, Engineering, Sales, Marketing, Finance, Legal, and leadership. Coordinate product evaluation, integration handoffs with Product and Engineering, customer messaging, sales enablement, finance modeling, and legal/commercial review. • Maintain AI market intelligence: Track new model releases, benchmark shifts, pricing changes, context-window improvements, multimodal capabilities, latency and reliability tradeoffs, enterprise terms, ecosystem moves, and competitor access. Convert this information into clear internal updates and recommendations. • Drive partner-led launches on the commercial side: Coordinate timing with model creators, secure preferred or exclusive access, align launch narratives across Marketing and Sales, partner with Product and Engineering on the integration build, and ensure launches translate into measurable pipeline impact. • Support GTM and customer communication: Help Sales and Marketing translate model-provider updates into customer-facing value, launch narratives, partner comparison notes, competitive positioning, sales enablement, and customer-ready messaging. • Build a scalable partnership operating rhythm: Create and maintain partner account plans, executive relationship maps, QBRs, negotiation trackers, pricing and terms databases, launch calendars, model-update summaries, escalation paths, and partnership performance reporting.

Role Description Runware is looking for a Senior Partnerships Manager to own and scale our strategic relationships with the world’s leading AI model providers. This person will ensure we have the strongest possible commercial terms, roadmap visibility, product access, market insights, and strategic value from our model-provider ecosystem. They will be the central owner for model-provider partnerships and will work closely with Product, Engineering, Sales, Marketing, Finance, and Legal to turn external AI partnerships into measurable business value. This is a senior, cross-functional commercial role for someone who is an excellent negotiator, a trusted relationship-builder, and a fast learner in a rapidly changing AI market. The ideal candidate can build deep relationships externally, negotiate hard commercially, and translate model-provider capabilities into internal product decisions, customer-facing value, and improved unit economics. What You’ll Do - Own and negotiate strategic model-provider relationships: Manage and deepen relationships with leading generative media model providers, including Google, OpenAI, Black Forest Labs, ElevenLabs, Luma AI, ByteDance, Runway, and Ideogram. - Negotiate best-in-market commercial terms: Lead negotiations on pricing, volume commitments, credits, preferred access, support levels, SLAs, roadmap visibility, co-marketing, launch support, enterprise terms, and non-standard strategic deal structures. - Turn partnerships into business value: Identify and execute opportunities that improve product capabilities, reduce costs, improve margins, accelerate model launches, enhance customer experience, or differentiate Runware in the market. - Coordinate across internal teams: Act as the connective tissue between model providers and Product, Engineering, Sales, Marketing, Finance, Legal, and leadership. - Maintain AI market intelligence: Track new model releases, benchmark shifts, pricing changes, context-window improvements, multimodal capabilities, latency and reliability tradeoffs, enterprise terms, ecosystem moves, and competitor access. - Drive partner-led launches on the commercial side: Coordinate timing with model creators, secure preferred or exclusive access, align launch narratives across Marketing and Sales, and partner with Product and Engineering on the integration build. - Support GTM and customer communication: Help Sales and Marketing translate model-provider updates into customer-facing value, launch narratives, partner comparison notes, competitive positioning, sales enablement, and customer-ready messaging. - Build a scalable partnership operating rhythm: Create and maintain partner account plans, executive relationship maps, QBRs, negotiation trackers, pricing and terms databases, launch calendars, model-update summaries, escalation paths, and partnership performance reporting. Qualifications - 7+ years of experience in strategic partnerships, business development, partner management, commercial strategy, enterprise sales, vendor management, or a related role. - Strong track record negotiating complex commercial agreements with strategic partners, vendors, platforms, infrastructure providers, SaaS companies, cloud providers, API companies, or technology ecosystems. - Excellent commercial judgment, including the ability to evaluate pricing, usage commitments, deal structures, margin impact, and long-term strategic value. - Proven ability to work cross-functionally with Product, Engineering, Sales, Marketing, Finance, Legal, and executive stakeholders. - Strong communication skills, with the ability to simplify complex technical and commercial information for different audiences. - High ownership, strong follow-through, structured execution, and comfort operating in a fast-moving, ambiguous market. Requirements - Experience in AI, machine learning, cloud infrastructure, developer platforms, API businesses, SaaS, data infrastructure, or enterprise software. - Understanding of the AI model ecosystem: frontier labs, open-source models, inference providers, multimodal models, model pricing, latency, context windows, enterprise deployment needs, and AI application architecture. - Technical fluency sufficient to discuss model performance, API capabilities, inference requirements, context windows, multimodality, fine-tuning, evaluation, latency, reliability, and model launches. - Prior experience negotiating with large technology vendors, cloud providers, platform partners, or strategic ecosystem partners. - Experience building partner programs, partner operating cadences, QBRs, partner scorecards, or executive-level relationship maps. Benefits - Generous paid time off – vacation, sick days, public holidays. - Meaningful stock options – share in the upside you create. - Remote-first setup – work from home anywhere we can employ you. - Flexible hours – own your schedule outside core collaboration blocks. - Family leave – paid maternity, paternity, and caregiver time. - Company retreats – twice-yearly gatherings in inspiring locations.

• Act as the primary technical escalation point for customer support issues related to API usage, model behavior, performance, and reliability. • Troubleshoot complex technical problems across the full request lifecycle (client → API → model provider → response). • Investigate logs, metrics, and error traces to identify root causes and reproduce issues where needed. • Coordinate closely with engineering during incidents, bugs, or performance degradations. • Communicate clearly and calmly with customers during incidents, including status updates and resolution summaries. • Help customers understand platform behavior, limitations, and best practices. • Contribute to support documentation, troubleshooting guides, and internal playbooks. • Identify recurring issues, perform root-cause analysis, and proactively propose improvements to tooling, processes, documentation, or (where appropriate) contribute small fixes to reduce repeat issues. • Stay up to date on supported models, provider changes, and platform capabilities to guide customers appropriately. • Work closely with Engineering, Product, Customer Success, and Partnerships to resolve issues and translate customer feedback into actionable technical insights.

- Define and execute Runware’s **hardware and compute infrastructure strategy**. - Own the **GPU procurement and supply strategy**, including relationships with vendors and hosting providers. - Design and optimize **server and datacenter infrastructure** supporting AI inference workloads. - Evaluate and negotiate partnerships with **datacenter providers, GPU vendors, and infrastructure partners**. - Work closely with engineering teams to ensure infrastructure supports evolving product and model requirements. - Drive **cost/performance optimization** across hardware deployments. - Lead **capacity planning** to support rapid company growth and global infrastructure expansion. - Monitor industry trends across **GPU hardware, AI infrastructure, and datacenter innovation**. - Support the deployment of infrastructure across multiple regions and providers. - Help build the long-term roadmap for Runware’s **global compute platform**.

• Build and maintain E2E inference time tracking (global and per-model). • Monitor how implementation changes impact total request latency. • Detect regressions introduced by suboptimal code paths. • Provide automated alerts & historical trends. • Build dashboards for internal use (engineering, product, leadership). • Provide client-facing usage dashboards (requests, errors, success rate, performance). • Support clients who need visibility to debug their integrations. • Track model-level usage, API endpoints usage, adoption metrics, etc. • Implement metrics, logs, and traces that help the entire platform scale smoothly. • Work closely with DevOps & backend teams to improve system observability. • Provide insights that guide infra decisions (GPU allocation, autoscaling, caching, batching, etc.). • Select and maintain tooling (e.g., Prometheus/Grafana, Datadog, OpenTelemetry, ELK, BigQuery, etc.). • Ensure data pipelines are reliable, accessible, and always up-to-date. • Build simple, easy-to-read dashboards for both technical and non-technical teams.

• Lead, mentor, and grow a team of engineers in a fast-scaling environment • Create a culture of ownership, accountability, and continuous improvement • Support individual growth through regular 1:1s, feedback, and coaching • Participate in hiring, onboarding, and performance management • Own team execution: planning, prioritization, and delivery of engineering work • Ensure projects are delivered on time, with high quality and clear ownership • Identify risks early and proactively remove blockers • Balance speed, reliability, and technical debt in a pragmatic way • Act as a technical sounding board on system design, architecture, and trade-offs • Ensure backend systems are scalable, reliable, and performant • Promote best practices around code quality, testing, observability, and security • Partner closely with other teams like DevOps and Product to align technical direction • Work closely with Product, DevOps, ML and other teams to ensure strong alignment • Translate business and product goals into clear engineering execution plans • Communicate clearly and proactively in a fully remote environment

Customer Ownership & Adoption - Own a portfolio of customers after onboarding and act as their main point of contact - Guide customers through technical adoption, usage patterns, and scaling - Help customers understand and adopt new models, features, and releases - Maintain clear communication across Slack, email, and calls with technical and non-technical stakeholders Support, Incidents & Coordination - Monitor usage, performance, and health signals - Help troubleshoot issues, coordinate with engineering, and manage incidents calmly and clearly - Ensure issues are communicated transparently and followed through to resolution Customer Feedback & Internal Alignment - Collect and share customer feedback with product and engineering teams - Translate customer needs into actionable insights for internal teams - Act as a point of coordination between customers and internal stakeholders Commercial Support - Support conversations around pricing, usage, renewals, and expansions - Help customers understand how usage and pricing models work

• Design intuitive user experiences for the Runware website, web app and developer platform • Translate complex AI and infrastructure concepts into powerful workflows and interfaces • Design dashboards, onboarding flows, model exploration tools, and developer-facing product surfaces • Create wireframes, user flows, prototypes, and high-fidelity product designs • Collaborate closely with product managers and engineers to bring new features to life • Improve usability across existing interfaces based on developer feedback and product insights • Help evolve our design system and ensure visual and interaction consistency across the platform • Work on early-stage product concepts and prototypes for new capabilities • Contribute to improving developer onboarding and time-to-first-success • Identify UX friction points and propose solutions that improve clarity and adoption

• Design, build, and maintain **schemas and data models** • Optimize table layout, partitioning, indexing, and compression for high-volume data • Ensure fast, efficient querying for logs, requests, metrics, and performance traces • Maintain ingestion pipelines for billions of records • Build robust pipelines for: - API logs - Model inference logs - Error events - Usage & integration events - GPU & system metrics • Implement ETL/ELT workflows to transform raw data into analytics-ready structures • Ensure quality, reliability, and real-time availability of data sources • Build tooling to support large-scale **log analysis** • Enable deep investigation into latency, throughput, errors, and bottlenecks • Provide the raw data foundation for E2E inference-time monitoring • Help debug production issues using logs and traces • Work closely with DevOps, ML, and backend engineering • Integrate pipelines with monitoring tools (Prometheus, Grafana, Datadog, OpenTelemetry) • Automate ingestion and cleanup tasks • Build internal libraries or utilities to support monitoring and debugging workflows • Provide clean data interfaces for the Data Expert (dashboards, monitoring, analytics) • Support engineering teams by exposing the right logs and metrics • Contribute to debugging, RCA (root cause analysis), and performance optimization initiatives