Вакансии

Location: San Francisco; Toronto; New York; Montreal; Seattle Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Voice is becoming the internet’s next interface, but a production-grade Voice AI system is "hard to build" https://greylock.com/greymatter/voice-agents-easy-to-use-hard-to-build/. You’ll join a small founding team of Baseten Voice AI, focused on bringing state-of-the-art open source models into production for Voice AI customers across productivity, customer service, clinical conversation, creator tools, education, and more. You’ll make a meaningful impact on people’s daily lives and help reshape these industries. This is a high-impact, high-ownership role. You will be the primary owner of Baseten Voice AI - our in-house inference stack to power Voice AI models - from product roadmap through engineering implementation. You’ll partner closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams to push the boundaries of Voice AI. EXAMPLE INITIATIVES - Develop world-class model serving stack for state-of-the-art open-source voice models - reduce end-to-end and tail latency (p95/p99), increase throughput, and improve GPU efficiency via profiling, runtime tuning, and server-level optimizations. - Build large-scale, real-time infrastructure for multi-model voice agents - orchestrate STT, TTS, and agent components with streaming I/O to meet customer SLOs. - Design tight training and inference iteration loops for voice model customization - enable fast evaluation, safe rollout, and rapid experimentation for custom voice model development. - Past projects: - Baseten leads Coval’s voice AI benchmark https://www.baseten.co/blog/baseten-leads-covals-voice-ai-benchmark/ - How Notion achieved 2-3x lower latency with AI Meeting Notes https://www.baseten.co/resources/customers/how-notion-acheived-2-3x-lower-latency-with-ai-meeting-notes/ - Cost-efficient, high-performance TTS with Qwen3-TTS https://www.baseten.co/blog/cost-efficient-high-performance-qwen3-tts/ - Fine-tuning Qwen3-TTS for high-quality voice cloning https://www.baseten.co/blog/fine-tuning-qwen3-tts-for-high-quality-voice-cloning/ - The fastest Whisper — with streaming and diarization https://www.baseten.co/blog/the-fastest-whisper-transcription-with-streaming-and-diarization/ - NVIDIA Nemotron 3 Diarization: real-time speaker labels at a cent per audio hour https://www.baseten.co/blog/nvidia-nemotron-3-diarization/ RESPONSIBILITIES - Own and lead Voice AI product areas end-to-end - from architecture and system design through implementation, rollout, and long-term production operations. - Design, build, and operate real-time, large-scale, high-performance model serving systems for STT, TTS, and voice agent workloads for mission-critical customer deployments - Drive cross-team collaboration with sister engineering teams to solve full-stack technical problems, align on priorities, and coordinate end-to-end delivery across the product surface area - Mentor teammates through code reviews, design docs, and technical leadership. REQUIREMENTS - Bachelor's degree or higher in Computer Science or related field - Proven track record owning production-grade real-time, large-scale systems where tail latency (p99) matters. - Proficient coding abilities in one or more popular programming or scripting languages; Python proficiency is a plus. - Good taste in product, particularly developer-oriented tools - Interest in ML/AI infrastructure and willingness to learn - Strong collaboration and communication skills - Comfortable using AI coding assistants (e.g., Claude Code, Codex, Cursor) as a daily productivity multiplier — as an AI-native company, we see this as a must-have skill. NICE TO HAVE - Experience implementing pipeline-level model runtime optimizations such as dynamic batching, async scheduling, or decode-side throughput improvements. - Experience building developer platforms: SDKs, CLIs, APIs, and self-serve workflows for ML or infrastructure products. - Experience with containerization and orchestration technologies (Docker, Kubernetes), service meshes, or distributed scheduling. - Familiarity with speech/audio ML models (STT, TTS, speech-to-speech) - Familiarity with model-serving runtimes (vLLM, TensorRT, ONNX). - Familiarity with systems-level performance profiling across host-device boundaries (e.g. PyTorch Profiler), diagnosing GPU utilization issues - Exposure to customer-facing engineering: pre-sales prototyping, technical discovery, or working directly with customers to ship solutions. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

165 000 – 330 000 $

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Product at Baseten is a nascent function. Our company today has a strong engineering culture, is heavily customer-obsessed, and moves fast. We're building the product function now, and you'd be one of the people who defines it. You'll work directly with our founders and with some of the best systems and AI engineers, and you'll set the standard for what product looks like here. PMs at Baseten don't sit above engineers. You earn ownership by being technical, finding the truth in front of customers, building great cross-functional relationships, and shipping great product experiences. Once a model is deployed, keeping it fast, reliable, and economical at scale is where production inference is won or lost. You'll own the surface that makes that happen: how deployments autoscale, how traffic is routed, how the system fails over, and how workloads scale across clusters and regions. You'll own these as products end to end, both how they work under the hood and how customers configure and observe them, and you'll set the roadmap that infrastructure and product teams alike can build toward. This space is still evolving. Think cloud infrastructure in the mid-2000s. Your job is to make it 10x easier to reliably scale and serve AI models in production, and to set the market standard. This role is a great fit if you love getting deep in the technical details, and if you'd rather do whatever it takes to ship for customers than stay in the strategy, UX, or docs layer. You're drawn to platforms, systems, GPUs, models, and scaling infrastructure more than to applied AI, and you find real satisfaction in the foundational, sometimes unglamorous work that makes AI systems reliable and scalable at the infrastructure level. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Product and Infrastructure teams: - How we built Multi-cloud Capacity Management (MCM) https://www.baseten.co/blog/how-we-built-multi-cloud-capacity-management/ - How the Baseten Delivery Network (BDN) makes cold starts fast https://www.baseten.co/blog/how-the-baseten-delivery-network-bdn-makes-cold-starts-fast/ - Baseten brings AI video to life on Nebius https://www.baseten.co/blog/ai-video-nebius-baseten-inference-stack/ RESPONSIBILITIES - Own how workloads scale and where they land, from autoscaling to demand (up under load, down to zero when idle) to a single placement policy that expresses region, compliance regime, and capacity preference. - Give compliance-bound workloads right-of-way on sensitive capacity. - Make production inference reliable by default, so every request reaches a healthy replica and rolling deploys never drop traffic. - Define region-aware routing, with multi-region and active-active failover as first-class policy, plus health-aware recovery from stuck or bad replicas. - Build the release engine beneath safe rollouts: the traffic-shifting that powers canary, shadow, and A/B, along with warm-ups, drain, and probes. - Push the cost and performance frontier for serving AI at scale across latency, throughput, uptime, and cost efficiency. - Drive a measurable decline in MTTR through self-serve incident management. - Set the roadmap that infrastructure and product teams build toward, and own each capability end to end, from backend behavior through the customer-facing configuration and observability surface. REQUIREMENTS - 8+ years in product management, including deep experience with infrastructure, distributed systems, or ML serving. - Fluency reasoning about scaling, routing, failover, and the cost/performance frontier, at a level that earns the respect of staff engineers. - Experience owning capabilities end to end, backend through UX, rather than a single slice. - Track record driving cross-team roadmaps and the dependencies beneath them. - Comfort defining a category that doesn't fully exist yet. NICE TO HAVE - Hands-on experience with GPU infrastructure. - Experience with Kubernetes. - Experience with serving frameworks like vLLM, TensorRT-LLM, or SGLang. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Toronto; San Francisco; New York; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! WHY THIS ROLE? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for a Site Reliability Engineer to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. As a Site Reliability Engineer you will: - Build self-service systems that automate managing, deploying and operating services. - This includes our custom Kubernetes operators that support language model deployments. - Automate environment observability and resilience. Enable all developers to troubleshoot and resolve problems. - Take steps required to ensure we hit defined SLOs, including participation in an on-call rotation. - Build strong relationships with internal developers and influence the Infrastructure team’s roadmap based on their feedback. - Develop our team through knowledge sharing and an active review process. You may be a good fit if you have: - 5+ years of engineering experience running production infrastructure at a large scale - Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters - Experience with Kubernetes dev and production coding and support - Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving - Experience in designing, deploying, supporting, and troubleshooting in complex Linux-based computing environments - Experience in compute/storage/network resource and cost management - Excellent collaboration and troubleshooting skills to build mission-critical systems, and ensure smooth operations and efficient teamwork - The grit and adaptability to solve complex technical challenges that evolve day to day - Familiarity with computational characteristics of accelerators (GPUs, TPUs, and/or custom accelerators), especially how they influence latency and throughput of inference. - Strong understanding or working experience with distributed systems. - Experience in Golang, C++ or other languages designed for high-performance scalable servers). FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: San Francisco; New York; Toronto; Montreal Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! WHY THIS ROLE? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. You may be a good fit if you have: - 5+ years of engineering experience running production infrastructure at a large scale - Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters - Experience with Kubernetes dev and production coding and support - Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving - Experience in designing, deploying, supporting, and troubleshooting in complex Linux-based computing environments - Experience in compute/storage/network resource and cost management - Excellent collaboration and troubleshooting skills to build mission-critical systems, and ensure smooth operations and efficient teamwork - The grit and adaptability to solve complex technical challenges that evolve day to day - Familiarity with computational characteristics of accelerators (GPUs, TPUs, and/or custom accelerators), especially how they influence latency and throughput of inference. - Strong understanding or working experience with distributed systems. - Experience in Golang, C++ or other languages designed for high-performance scalable servers). FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: New York; San Francisco; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Our team is a fast-growing group of committed researchers and engineers. The mission of the team is to build reliable machine learning systems and optimize audio inference serving efficiency using innovative techniques. As an engineer on this team, you will work on advancing core audio model serving metrics, including latency, throughput, and quality by diving deep into our systems, identifying bottlenecks, and delivering creative solutions for audio processing and streaming workloads. You’ll collaborate closely with both the training and serving infrastructure teams to ensure seamless integration between model development and deployment, with a special focus on real-time and streaming audio inference. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Qualifications: - Significant experience developing high-performance audio or machine learning inference systems. - Proficiency with programming languages such as C++ and Python. - Hands-on experience with deep learning models for audio, speech, or language applications. - A bias for action and a strong results-oriented mindset. It is a big plus if you also have considerable experience with: - GPU programming, low-level system optimization, model parallelization techniques over multiple GPUs - Have experience with duplex real-time streaming architectures. - Internals of machine learning frameworks for audio (such as PyTorch, TensorFlow, or specialized audio libraries). - Have experience with inference framework like vLLM, SGLang, Tensort-LLM, or custom distributed inference systems - Sequence modeling (e.g., transformers for audio/speech) and end-to-end audio pipeline optimization Working location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: San Francisco; Toronto; New York; Montreal; Seattle Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As an Engineer on the Dedicated Inference team, you'll shape the state-of-the-art developer experience for deploying and operating AI workloads in production. From the CLI and SDKs to APIs, observability, and debugging workflows, you'll build the tools customers rely on every day to manage mission-critical inference deployments. Few teams at Baseten have as much breadth and visibility as Dedicated Inference. The team is often at the forefront of new product development, giving engineers the opportunity to shape the experience of some of our most important customers. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Dedicated Inference team: - Chains for multi-component workflows https://www.baseten.co/blog/baseten-chains-explained/ - Asynchronous inference https://www.baseten.co/blog/using-asynchronous-inference-in-production/ - Model APIs for frontier models https://www.baseten.co/products/model-apis/ - Model training built for production inference https://www.baseten.co/products/training/ RESPONSIBILITIES - Implement new features and products for the team - Design ergonomic APIs and abstractions to solve customer problems - Fix bugs and resolve customer issues with urgency - Work across the stack - regardless of where you start, you’ll end up touching both React Components and Kubernetes Pods - Work closely with the product and forward deployed engineering teams to develop and drive new product ideas REQUIREMENTS - Bachelor's degree or higher in Computer Science or related field - Proficient coding abilities in one or more popular programming or scripting languages; Python, Go, or JavaScript proficiency is a plus - Familiarity with web applications & databases - Good taste in product, particularly developer-oriented tools - Interest in ML/AI infrastructure and willingness to learn - Strong collaboration and communication skills BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Lambda is looking for a Staff Product Manager Storage and Networking to define, launch, price, and improve cloud data and connectivity products.

291 000 – 430 000 $

— Разрабатывать и поддерживать реализованные рекомендательные решения. — Искать новые гипотезы для улучшения пайплайнов обучения моделей и добавления новых признаков.

Зарплата не указана

As Head of Product you own product direction and priorities for the cloud platform: which problems deserve our attention, what success looks like, and what we should stop doing.

Зарплата не указана

решать продуктовые задачи с помощью ML: от постановки гипотезы и исследования данных до запуска решения в production и оценки бизнес-эффекта; развивать ML-модели, влияющие на клиентский опыт и бизнес-метрики продукта.

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Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We are seeking a strategic and creative Partnerships Product Marketing Manager to drive the success of our partner ecosystem. In this role, you will work closely with our partnerships team and with leading technology companies including NVIDIA, Cloud Hyperscalers, Neocloud providers, and emerging ecosystem players, to bring differentiated joint solutions to market. You will be responsible for shaping partner narratives, creating impactful content, and enabling joint go-to-market programs that amplify our reach. The ideal candidate combines storytelling skills, technical acumen, and the ability to collaborate across partner and internal teams. RESPONSIBILITIES - Partner Storytelling & Content - Develop compelling blog posts, white papers, solution briefs, and customer success stories highlighting the value of joint solutions. - Translate technical integrations into clear, differentiated messaging for both technical and business audiences. - Enablement & Training - Build and deliver enablement programs to arm partner sales teams with the tools, messaging, and collateral they need to position and sell our solutions. - Create sales playbooks and battlecards tailored to each partner’s ecosystem. - Joint Go-to-Market Campaigns - Plan and execute co-marketing campaigns with partners, including webinars, events, solution launches, and demand-generation activities. - Manage partner marketing calendars and ensure alignment with key product milestones. - Cross-Functional Collaboration - Work closely with product marketing, product management, DevRel, and growth marketing, events and sales to align messaging and GTM initiatives. - Serve as the marketing point-of-contact for the partnerships team. REQUIREMENTS - 6-10 years of experience in product marketing, partner marketing, or related roles in B2B technology. - Experience with NVIDIA technology and ecosystem or Cloud Providers technology - Track record of working with cloud providers, ISVs, or hardware partners in joint go-to-market programs is a plus. - Exceptional written and verbal communication skills; ability to create high-quality content across multiple formats. - Strong program management skills with the ability to handle multiple partners and campaigns simultaneously. - Technical curiosity and ability to quickly learn new technologies and ecosystems. - Comfortable working in a fast-paced, high-growth environment. NICE TO HAVE - Familiarity with developer ecosystems, APIs, and modern software development practices. - Knowledge of AI/ML infrastructure, model serving, and performance optimization concepts. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: New York Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. ABOUT THE ROLE: We’re looking for our first IT Lead to build and own the systems that enable everyone at Modal to work effectively and securely. You’ll own our employee technology environment end-to-end, including identity and access, devices, internal systems, SaaS applications, and day-to-day IT operations. You’ll work closely with Security and Engineering to build an environment that is secure by default, easy to operate, and scales with the company. This is initially a hands-on role. You’ll build systems, automate workflows, and solve problems directly. As Modal grows, you’ll define how the IT function should scale and eventually build a team around it. WHAT YOU’LL WORK ON: Identity & Access - Own employee identity and access across internal systems and SaaS applications - Build scalable onboarding, offboarding, and access lifecycle workflows - Improve SSO, MFA, least privilege, and access management in partnership with Security Devices & Endpoints - Own the lifecycle and security of employee devices - Build and maintain device management, configuration, patching, and endpoint security - Automate provisioning and make onboarding as close to zero-touch as possible Internal Systems & Automation - Own and improve the SaaS applications and internal systems we depend on - Build integrations and automate workflows across identity, HR, finance, and other business systems - Evaluate and deploy new internal capabilities, including AI tools and integrations - Use APIs, scripting, and internal tooling to solve problems that don’t fit neatly into off-the-shelf products IT Operations - Own employee support, hardware, asset management, procurement, and relevant vendor relationships - Build reliable, maintainable processes rather than scaling through manual work - Identify recurring problems and solve them at the system level Build the IT Function - Define the technical direction and operating model for IT at Modal - Establish the systems and processes we’ll need as the company grows - Determine when and where additional IT capacity is needed, and build the team over time WHAT WE’RE LOOKING FOR: - Experience owning IT or corporate technology in a fast-growing technology company - Strong understanding of identity, device management, SaaS administration, and endpoint security - Strong technical skills and comfort working with APIs, scripting, automation, and system integrations - Experience designing and automating employee lifecycle and access-management workflows - Good security judgment and experience working closely with Security and Engineering - Ability to independently identify problems, make pragmatic technical decisions, and drive them through implementation - Comfortable being hands-on today while building the systems and team needed as the company grows

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Baseten has emerging co-sell relationships with multiple strategic marketplaces and clouds, including OpenAI https://www.baseten.co/talk-to-us/openai/?utm_source=google&utm_medium=paid_search&utm_campaign=acquisition_ICA-OpenAI-Partnership_2026-09-30&utm_term=baseten%20openai&utm_campaign=Search+-+Models&utm_source=adwords&utm_medium=ppc&utm_id=24316507588&hsa_acc=9990356727&hsa_cam=24316507588&hsa_grp=199416272086&hsa_ad=826599669780&hsa_src=g&hsa_tgt=kwd-2504168645905&hsa_kw=baseten%20openai&hsa_mt=e&hsa_net=adwords&hsa_ver=3&gad_source=1&gad_campaignid=24316507588&gbraid=0AAAAAqCKh1tZ-ESp-CbtgHnyoj6pkRZGL&gclid=CjwKCAjw56zWBhB0EiwAdPOQOTzW3Bhx_UxkJI6XA8gB1rqClDpNVWFQtTzWlO0RBCV5Xx_yB54yDxoCcd4QAvD_BwE, NVIDIA and other Hyperscalers, Model Labs, and Data Platforms. The task at hand is to enable and activate partner sellers and to ensure that our internal field teams are well-supported to work successful with partner teams. As Baseten’s Partner Enablement Lead, you'll turn each partnership into a repeatable field motion. You'll work out why a partner account executive should care about Baseten, which of their customers are a fit, and what joint execution looks like. Then you'll co-build what it takes for sellers on both sides to run that play: the value proposition, the account mapping, the talk tracks, the training, and the relationships with partner field leaders. As always, the work starts with earning partner attention. This is a strategic, hands-on role for an ecosystem GTM operator who peaks in enablement. Your work will include deep cross-functional collaboration, instructional design, content development, and training delivery. You won't own partner-sourced pipeline directly, but you will make those who do much more effective. Our partnerships span Hyperscalers, Model Labs, Semiconductors, Consulting and Systems Integrators, and Data Platforms. While much of what partner enablement looks will be in your hands to define, it will include getting in front of field sellers, developing co-sell opportunities, and driving adoption of marketplace incentives for customers to buy Baseten against the commitments they already have. You'll report to the Head of GTM Enablement & Productivity and work closely with our Partnerships, Sales, FDE, Marketing, and RevOps teams. WHAT YOU'LL DO Design the joint go-to-market motion with strategic partners - Build a working picture of each partner's field: seller roles, how they're paid and measured, what makes them bring in a third party, and what gets in the way. - Define joint value propositions, customer triggers, and target segments in partnership with our alliance leads and sales & revops leadership. - Turn those into co-sell plays with clear entry points, owners, and next steps for both sides. - Run account mapping with partner teams so the plays land on specific accounts, not just slides. Activate partner field teams - Activate partner sellers and their managers to be aware of Baseten, confident in when to pull us in, and motivated to do so. - Build relationships with partner field leaders, partner development managers, and ISV teams so enablement reaches the sellers who matter. - Plan and run activations by region and segment: field briefings, account planning sessions, joint office hours, and events alongside our partnerships team. - Teach both sides how marketplace and co-sell mechanics work, so those programs make deals simpler and faster to execute. Enable Baseten's own sellers on partner motions - Make sure our AEs, SAs, and FDEs know how to work a partner-sourced or co-sell deal: how to engage the partner rep, how attribution and credit work, and which plays to run. - Build or collate the playbooks, demos, and certifications our team needs, and keep them current as each partnership changes. - Bring partner content into our onboarding and GTM Academy so new hires learn the partner motion from day one. Measure and evolve programs - Define how we measure activation: trained and engaged partner sellers, joint account plans, co-sell opportunities registered, and partner-influenced pipeline. - Work with RevOps on the operational side of partner programs, including deal registration, marketplace private offers, and POC and MDF requests. - Report monthly to GTM leadership on what's working, what isn't, and advise on where to invest next. WHAT WE'RE LOOKING FOR - 5+ years in partner or alliance GTM, partner enablement, or field GTM at a cloud, data, AI, or infrastructure company. - Hands-on experience activating co-sell with at least one hyperscaler or major platform partner (Microsoft, AWS, Google Cloud, NVIDIA, or similar). - You think in pipeline and seller behavior as well as in curriculum. You can explain a joint motion end to end, from partner incentives to the first customer meeting. - Enough technical depth to be credible with SAs and engineers on both sides. You don't need to be an ML engineer, but you should be comfortable learning inference, model serving, and GPU and token economics quickly. - You want to build: the play, the deck, the training, the measurement plan. You don't stop at the framework. - Comfortable working across teams you don't control, inside Baseten and inside partner organizations much larger than ours. Strong candidates may come from a mix of backgrounds such as: - Cloud alliances or partner GTM at a data or infrastructure ISV that co-sells with the hyperscalers. - ISV, partner development, or marketplace roles inside a hyperscaler or NVIDIA. - Partner enablement leadership at a technical company, with a track record tied to pipeline rather than training volume. - A partner-facing SA or SE who moved into enablement or GTM strategy. NICE TO HAVE - Experience with Microsoft co-sell programs, Azure Marketplace, or NVIDIA's partner and ISV programs. - Experience at an AI infrastructure, model provider, or developer platform company. - Built a partner function or partner enablement program from scratch at a growth-stage company. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Container runtimes were designed for general-purpose software workloads. AI inference is not a general-purpose workload. Running large models at production scale exposes cracks in every layer of the container stack: runtimes unaware of GPU memory constraints, images that take minutes to pull when a model needs to scale to thousands of replicas, and isolation mechanisms that weren’t designed for the multi-tenant serving environments that production AI requires. The tools the industry has relied on for a decade weren’t built for this, and patching around those limitations at higher layers only goes so far. Baseten owns the entire pipeline, from the moment a developer pushes a model to the moment a request gets a response. That vertical ownership means we can fix these problems at the root. The Runtime Fabric team is doing exactly that: purpose-building the container runtime and storage layers for AI inference workloads, led by some of the world’s top containerd maintainers. As Engineering Manager for Storage Products on the Runtime Fabric team, you will lead the engineers who build and run the storage products behind that stack: the Baseten Delivery Network (BDN), which sits in the cold start path of every model on the platform, the snapshotters and filesystems that expose model weights and container images to a running container, and the storage that model deployment and training need next. The team is advancing the next generation of caching for inference workloads, from the origin tier to the GPU host. You will own reliability for the area as a measured outcome, report to the head of Runtime Fabric, and stay close to the code through design and code review. If you’ve managed systems engineers and have hands-on experience with caching, content-addressable storage, or distributed filesystems, we’d love to talk. EXAMPLE INITIATIVES - How the Baseten Delivery Network (BDN) makes cold starts fast https://www.baseten.co/blog/how-the-baseten-delivery-network-bdn-makes-cold-starts-fast/ - Extending BDN from model weights to container image layers, training checkpoints, and deployment artifacts - Lazy-loading snapshotters and block-level delivery (EROFS, FUSE, ublk) so a container can start before the full image or model has arrived RESPONSIBILITIES Team Leadership and Culture - Hire and grow a team of 5 to 10 systems engineers with storage, caching, and Linux expertise - Run the team’s planning and delivery: scope work against the Runtime Fabric roadmap, set priorities, and ship on a predictable cadence - Provide regular coaching, feedback, and career development support to your direct reports - Own on-call health for the team’s services, including escalation paths and follow-through on incidents Technical Direction - Guide the architecture and evolution of the Baseten Delivery Network: the tiered caching and weight delivery product that makes cold starts 2-3x faster and eliminates thundering herd failures during burst scaling events - Shape storage products tailored to Baseten’s workloads: extend BDN from model weights to container images, training checkpoints, and deployment artifacts, and define the interfaces that model deployment, training, and customers use to reach them - Oversee the on-host side of delivery: lazy-loading snapshotters, EROFS and overlayfs layouts, and block-level delivery (FUSE, ublk) for multi-gigabyte files - Own reliability of the delivery path as a measured outcome: end-to-end instrumentation from snapshotter initialization to first inference request, targets for cold start and cache behavior, tolerance for failing upstream registries and object stores, and safe rollout of changes to a path every customer depends on - Make the delivery path work across heterogeneous clusters and cloud providers, each with its own object store and network - Review designs and code across the area, and take on hands-on work where it unblocks the team - Champion the team’s contributions back to containerd and the snapshotter ecosystem alongside the maintainers on the Runtime Fabric team Cross-Functional Partnership - Act as the point of contact for storage across Baseten, ensuring model deployment, training, and platform teams have the integration support they need - Optimize requirements for the underlying storage platforms with the infrastructure team: object storage, local NVMe and block storage, and network bandwidth per cluster, so that capacity and provider decisions account for what the delivery path needs - Manage the team’s dependencies in both directions: sequence work that model deployment, training, and infrastructure teams block on, and negotiate interfaces and timelines with the teams and upstream projects the storage path depends on - Work with the head of Runtime Fabric and product stakeholders to prioritize storage investments based on customer impact and infrastructure reliability - Communicate team progress, technical trade-offs, and incidents clearly to the team and to leadership REQUIREMENTS - Experience managing a team of engineers in a systems, infrastructure, or storage context, including hiring and performance management [TODO: confirm whether a tech lead stepping into management qualifies] - Hands-on background in distributed storage systems, content-addressable storage, or large-scale caching infrastructure - Strong systems programming background in Go, Rust, and/or C/C++, with the ability to engage credibly in code reviews and architectural discussions - Working knowledge of the Linux storage stack: filesystems, the page cache, block devices, and mounts - Understanding of how container images are structured, stored, and delivered at scale - Strong written and verbal communication skills, with the ability to influence without authority across teams NICE TO HAVE - Contributions to containerd/containerd, snapshotter projects (stargz, soci, nydus, overlaybd), distribution/distribution, or closely related open-source projects - Familiarity with lazy-loading snapshotters or peer-to-peer image distribution - Experience with EROFS, FUSE, ublk, or io_uring - Experience building or operating CDN, object storage, or large-scale caching infrastructure - Experience running storage services on Kubernetes BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Stockholm ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collection over billions of objects. You'll work across the stack, from local disk and page cache to distributed blob storage and garbage collection and you'll help shape what storage becomes next as we push storage closer to workloads. REQUIREMENTS: - 5+ years of experience writing high-quality production code - Experience building high-performance distributed storage or caching systems at a large scale (the more challenges you've worked through, the better) - Strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - Strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - Willingness to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVES: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte-scale. - Prior experience with Rust KEY THINGS THE TEAM IS WORKING ON: - P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicating data across multiple blob storage providers - Automating garbage collection across hundreds of petabytes of data - Deploying colocated storage clusters to datacenters to accelerate high-throughput customer workloads

ElevenLabs is looking for a Marketing Data Scientist to measure offline marketing effectiveness and guide strategic marketing experiments.

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Location: Remote; New York, NY; San Francisco, CA Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. ABOUT THE ROLE Preferable to have someone near an office in NYC or San Francisco, but open to hiring around the world for the right candidate. Runway Creative is an all-in-one platform giving creators and businesses endless ways to generate and edit video, images, and audio. Our customers range from individual creators on self-serve plans to studios and enterprise marketing teams, and they generate with both Runway's own models and leading third-party models, all on one platform. We're hiring a Pricing & Packaging Lead to own how Runway creates and captures value across all of it. You'll partner closely with our Self-Serve Product Lead to evolve our plans and credits, build the path from self-serve to enterprise, and set the pricing for every model we launch and every third-party model we serve. You'll build the pricing framework the rest of the company uses, and you'll be accountable for revenue growth, gross margin, and customer trust in equal measure. WHAT YOU’LL DO - Own self-serve pricing & packaging: partner with the Self-Serve Product Lead on our plan ladder and credit design, including allowances, rollover, top-ups, annual vs. monthly, and regional pricing. Run a continuous program of pricing and packaging experiments with Growth and Data. - Build the path to enterprise: design the triggers, team and workspace constructs, seat and credit-pool models, and commit and consumption contracts that move customers from self-serve to enterprise. Equip Sales with pricing playbooks, discount bands, and deal guardrails. - Create a company-wide pricing framework: publish Runway's pricing principles, value metrics, and decision process so any product team can price new features and products with confidence. Run a regular pricing council with Product, Finance, Research, and GTM. - Price our models: set launch pricing for every Runway model release, working with Research and Infrastructure on cost-to-serve. Define how model pricing evolves from launch through deprecation as inference costs change. - Own third-party model economics: set credit pricing and target margins for the partner models we serve, monitor competitive pricing, and work with Partnerships on vendor terms. Make per-model margin visible to the whole company. - Keep pricing changes trustworthy: own how we communicate every pricing change, from advance notice and in-product usage visibility to spend controls and customer FAQs. Changes should land as clearly as they were designed. - Build the team: hire and lead a small pricing team over time, and partner closely with billing engineering to turn decisions into systems. WHAT YOU’LL NEED - 10+ years across pricing, monetization, strategy, or strategic finance, with 5+ years directly owning pricing and packaging decisions. A track record of moving revenue, conversion, and margin, not just producing recommendations. - Deep experience with usage, credit, or consumption-based pricing. You can build a cost-to-serve and margin model from compute and inference inputs, and you understand how hybrid seat + usage models behave in the wild. - Experience across self-serve and sales-led motions. You've shipped pricing changes for PLG subscription products and designed the contracts and guardrails that support enterprise expansion. - Rigorous and experimental. You're fluent in pricing experiments, willingness-to-pay research, and cohort analysis, and comfortable in SQL and financial models. - You thrive in an environment with rapid pace and a high accountability culture. You make decisions with incomplete information and know when a pricing call needs more data and when it needs to ship. - Excellent written and verbal communication. You can drive a decision across Product, Finance, Research, and Sales, and explain a pricing change to customers in a way that builds trust. - Bonus: pricing experience at an AI lab, AI-native product, API or developer platform, or creative tools company; experience pricing third-party or marketplace offerings. Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Location: United Kingdom; Brazil; Ireland; Peru; Costa Rica; Latvia; Argentina; Romania; Cyprus; Portugal; Slovenia; South Africa; Czech Republic; Panama; Estonia; Canada; Hungary; Mexico; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. Before you apply, we encourage you to explore our culture page https://www.kraken.com/culture to understand what drives us and how we work. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The AI Infrastructure team builds and operates the production systems that power intelligent agents at scale. This team sits at the foundation of the agent platform, ensuring that model inference, orchestration, and execution layers are reliable, observable, and performant under real-world load. Working closely with the Agent Systems team and broader infrastructure partners, this group owns the core primitives that enable agents to safely operate across internal systems. The environment is high-scale and high-stakes — systems serve millions of users and must meet strict reliability, latency, and correctness standards. This is a deeply production-oriented team. Engineers here combine strong systems thinking with applied ML infrastructure experience, building in Rust and operating services where performance and failure modes matter.   THE OPPORTUNITY - Design and build the infrastructure layer powering AI agent systems in production - Develop high-performance Rust services that handle model inference, orchestration, and execution - Architect scalable systems capable of supporting millions of users and high request throughput - Build reliable ML infrastructure and MLOps patterns for model deployment, evaluation, and monitoring - Define guardrails, observability, and failure handling for agent-driven workflows - Optimize latency, throughput, and cost across inference and orchestration layers - Partner closely with the Agent Systems team to translate experimental prototypes into hardened production systems - Contribute to foundational infrastructure decisions in a high-scale, high-impact environment   WHAT YOU BRING - 5+ years of experience building and operating high-scale production systems - Strong proficiency in Rust and systems-level programming - Deep understanding of distributed systems, reliability engineering, and performance optimization - Experience operating services serving millions of users or high-throughput workloads - Familiarity with ML infrastructure, model serving, or MLOps in production environments - Experience designing observability, monitoring, and failure recovery systems - Strong collaboration skills working across infrastructure and applied engineering teams - High ownership mindset in high-stakes production environment   NICE TO HAVES - Experience building infrastructure for agent-based or LLM-powered systems - Background in high-performance networking, async systems, or low-latency architectures - Experience with container orchestration and cloud-native infrastructure - Familiarity with evaluation frameworks and model performance monitoring at scale - Experience working in fast-moving 0→1 or platform-building teams Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice