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            "title": "Staff Machine Learning Engineer, Voice AI",
            "description": "<p>Staff Machine Learning Engineer, Voice AI at Together AI - San Francisco - Staff Machine Learning Engineer, Voice AI San Francisco About the Role Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications - serving speech-to-text and text-to-speech models with best-in-class latency and reliability. We&#39;re looking for a Staff ML Engineer to drive the model serving layer for voice workloads. You&#39;ll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro - pushing latency and throughput to the frontier. You&#39;ll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly. This is a foundational hire on a small, high-impact team. Voice inference has unique challenges - streaming audio, tokenization, real-time latency budgets - that require dedicated ML engineering focus. You&#39;ll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech. - Own the model serving stack that powers Together&#39;s voice platform across STT, TTS, and speech-to-speech. - Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference. - Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together&#39;s infrastructure. - Build quality evaluation frameworks that guide model selection for customers and inform the roadmap. - Join a small, early-stage team with outsized impact on a fast-growing product area. Responsibilities - Own the voice inference roadmap end-to-end -</p>",
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            "description": "<p>AI Infrastructure Engineer at Together AI - San Francisco - AI Infrastructure Engineer San Francisco As an AI Infrastructure Engineer at Together, you are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase. You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems. Responsibilities - Participate in on-call rotation (Pagerduty) to respond to production incidents - Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users - Build monitoring systems to ensure the highest quality service for our customers - Design and implement operational processes (such as deployments and upgrades) - Debug production issues across all services and levels of the stack - Identify improvements for the product architecture from the reliability, performance and availability perspectives - Plan the growth of Together AI&#39;s infrastructure Requirements - 5+ years of professional AI Infra or related experience - Bachelor&#39;s degree in Computer Science or a related field or equivalent work experience - Knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes - Proficiency in programming/scripting languages - Direct experience in monitoring and observability practices - Knowledge of cloud services - Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts About Together AI Together AI is a research-driven artificial intelligence company. We believe</p>",
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            "description": "<p>Infrastructure Design Engineer at Together AI - San Francisco - Infrastructure Design Engineer San Francisco About The Role Together AI is building its infrastructure footprint at scale, and this role is central to making that happen. As an Infrastructure Design Engineer, you will own the design, planning, and technical execution of whitespace environments (where servers, storage, and network equipment are deployed) across our AI data center portfolio. You are the in-house expert who ensures that rack layouts, power distribution, cooling strategy, structured cabling, and physical infrastructure design are all built to support the density, redundancy, network and reliability requirements of large-scale AI GPU clusters. You will serve as the lead engineer across our DC portfolio, creating white space designs, reviewing partner and contractor designs, and ensuring plans are executed to spec. You will work closely with the Infrastructure Strategy, Infrastructure Engineering, and Operations teams, as well as external MEP consultants, general contractors, and data center partners. This is a technical role on a small, high-accountability team where your judgment directly shapes our ability to bring capacity online on time and to spec. Responsibilities - Architect HPC clusters by designing whitespace layouts, including rack placement, aisle configuration, hot/cold aisle containment, equipment density, and airflow strategy for high-density GPU deployments - Collaborate with electrical and mechanical engineers to integrate power and cooling infrastructure into whitespace environments - Collaborate with Network Engineering to define and validate physical layer requirements (structured cabling, pathway planning, port density) for high-speed AI cluster interconnects, ensuring design compatibility with both physical and logical network architectures. - Advise Data</p>",
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            "description": "<p>Sr. Revenue Accountant at Together AI - San Francisco - Sr. Revenue Accountant San Francisco About the Role Together AI is looking for a Senior Revenue Accountant to join our Revenue Accounting team and help scale our revenue operations as we grow. This role will own three core areas: end-to-end accounts receivable, invoicing, and collections, as well as revenue recognition in compliance with ASC 606. You will partner closely with FP&amp;A, Sales, Customer Success, and Commerce Engineering to ensure revenue is recorded accurately, in compliance with US GAAP. The ideal candidate is detail-oriented and collaborative, with a strong foundation in revenue accounting and hands-on experience across the full order-to-cash cycle. If you thrive in a fast-paced environment with the opportunity to lead, influence, and innovate across both day-to-day operations and high-impact accounting policy decisions, we want to talk to you. Responsibilities - Prepare monthly and quarterly journal entries for revenue, deferred revenue, and AR; lead close workstreams including reconciliations, roll-forwards, and flux analysis. - Reconcile revenue accounts, AR aging, deferred revenue balances, and other revenue-related accounts on a monthly basis; support revenue disclosures for management reporting and audits. - Own the end-to-end AR process: invoice generation, cash application, aging management, and collections follow-up; monitor overdue accounts and drive timely resolution. - Partner with Customer Success and Sales to resolve billing disputes, credits, and customer-specific payment terms; maintain AR KPIs including DSO and collections effectiveness. - Ensure invoices are issued accurately and in alignment with executed contracts; review order forms to validate billing terms, pricing, and revenue treatment prior to invoicing.</p>",
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            "description": "<p>Infrastructure Accounting Manager at Together AI - San Francisco - Infrastructure Accounting Manager San Francisco About the Role Together AI is looking for an Infrastructure Accounting Manager to help shape the future of the department by building scalable and reliable accounting processes for our rapidly growing capital asset and lease portfolios. This position will report to the Director of FinOps and Accounting and will own end-to-end accounting for Together AI&#39;s fixed assets, construction-in-progress (CIP), and lease obligations supporting our AI infrastructure. The ideal candidate is a highly skilled, detail-oriented professional with deep technical accounting expertise and a proactive, cross-functional mindset. If you thrive in a fast-paced environment with the opportunity to lead, influence, and innovate across both day-to-day operations and high-impact accounting policy decisions, we want to talk to you. Responsibilities - Own end-to-end accounting for Together AI&#39;s fixed asset portfolio, including GPU infrastructure, networking equipment, racks, and related data center assets; help build and maintain capitalization policy and asset classification guidelines, including useful life determinations, in accordance with ASC 360. - Review and approve asset additions, transfers, disposals, and retirements; ensure accurate depreciation calculations and subledger-to-GL reconciliations; maintain and continuously improve capitalization policies and related internal controls. - Manage accounting for Construction in Progress (CIP) related to GPU infrastructure deployments and data center buildouts, tracking asset commissioning and ensuring timely capitalization once assets are placed into service. - Partner with engineering, infrastructure, and business operation teams to validate deployment milestones, cost allocations, and in-service dates; monitor CIP aging and ensure appropriate classification and capitalization timing. - Manage accounting and</p>",
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            "title": "Forward Deployed Engineer (Inference & Post-Training)",
            "description": "<p>Forward Deployed Engineer (Inference &amp; Post-Training) at Together AI - San Francisco - Forward Deployed Engineer (Inference &amp; Post-Training) San Francisco About the role As a Forward Deployed Engineer (FDE) focused on Inference &amp; Post-Training, you will be a hands-on technical partner to our most strategic customers - production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts - directly impacting customer success, company growth, and the hardening of our core platform. Responsibilities - Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile - Configuration &amp; Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets. - Post-Training &amp; Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production. - Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts - monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones.</p>",
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            "description": "<p>Technical Account Manager (TAM), GPU Cluster at Together AI - San Francisco - Technical Account Manager (TAM), GPU Cluster San Francisco About the role As a TAM at Together AI, you will serve as the named technical owner for one of our most strategic customer relationships. You will be the primary technical point of contact across all infrastructure domains - compute, networking, storage, and facilities - ensuring flawless delivery and operational health of large-scale GPU deployments. This role sits at the intersection of deep infrastructure expertise and high-stakes customer partnership, making you a critical driver of both customer success and company growth. Responsibilities - Serve as the named technical point of contact for a dedicated strategic customer, owning the end-to-end technical relationship across compute, networking, storage, and facilities - Drive structured engagement through regular cadences including status reporting, technical steering meetings, and executive business reviews - Translate customer operational feedback into actionable input for Engineering, Product, and Infrastructure roadmaps - Lead issue lifecycle management, escalation, and RCA authorship across all infrastructure domains in partnership with Support, SRE, DC Ops, and Engineering teams - Own end-to-end RMA coordination and hardware lifecycle management, including acceptance testing, spare inventory management, and hardware health reporting for large-scale GPU deployments - Maintain deep technical expertise across the customer&#39;s infrastructure stack - GPU compute, high-speed fabric, and large-scale storage systems - advising on configuration, operational best practices, and incident resolution - Own the observability strategy for the customer estate, including alert policy definition, dashboard development, and proactive health management across all infrastructure layers - Coordinate DC operations and facilities</p>",
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            "description": "<p>Finance Analytics Engineer at Together AI - San Francisco - Finance Analytics Engineer San Francisco About the Role This is the first dedicated data hire on Together AI&#39;s Finance team. You will own the data layer that Finance runs on - building from scratch the models, pipelines, and reporting infrastructure that allow Strategic Finance, FP&amp;A, and Accounting teams to get reliable answers quickly. The person in this role will have direct exposure to every part of the Finance organization and a real opportunity to shape how data-driven decision-making develops here as the company scales. A significant portion of your work will touch the data behind the economics of Together&#39;s infrastructure, which sits behind nearly every financial question we ask. You will work closely with Together&#39;s Data and Commerce engineering team, which owns the underlying billing pipelines and data warehouse. Your job is to define and build the modeling and reporting layer that turns raw operational data into finance-grade datasets - aligning on data contracts, representing Finance&#39;s requirements in data design decisions, and ensuring the metrics Finance depends on are correct, documented, and trusted. Responsibilities - Own and evolve the dbt transformation layer for Finance: design, build, test, document, and maintain models covering billing, financial performance, compute unit economics, and operational metrics - Author and maintain Airflow DAGs (Astronomer-managed) that orchestrate Finance dbt runs, data quality checks, and downstream dependencies reliably - Deliver dashboards and reporting in Hex for the executive team covering financial performance, utilization, and key operating metrics - Partner with Strategic Finance, FP&amp;A, and Accounting teams on the</p>",
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            "description": "<p>Staff Backend Engineer - Commerce at Together AI - San Francisco - Staff Backend Engineer - Commerce San Francisco About the Role Together AI is seeking a Staff Backend Engineer to own the technical vision, architecture, and execution of the commerce platform powering Together&#39;s Cloud products. As a staff engineer on the Commerce Engineering team, you will set the engineering direction for mission-critical capabilities - including usage-based billing, payment processing, customer-facing analytics, and product entitlements - while raising the bar for the engineers around you. This role is ideal for a seasoned engineer who can operate at multiple altitudes: driving system design and long-term architecture decisions while staying hands-on in code. You&#39;ll be the connective tissue between engineering, product, finance, and go-to-market - translating complex business requirements into durable, scalable backend primitives that directly impact revenue and customer experience. You&#39;ll be expected to define not just what we build, but how we build it well. Requirements - 8+ years of experience building large-scale, fault-tolerant API-driven services and backend systems - Demonstrated track record of tech lead or staff-level scope - owning system architecture decisions, influencing team direction, and delivering multi-quarter initiatives - Deep expertise in designing relational database schemas and backend APIs that support complex product and business requirements at scale - Strong experience leading and influencing cross-functional teams - comfortable partnering with product, finance, and non-technical stakeholders - Expert-level proficiency in one or more of Golang, TypeScript, Python, C++, or Java - Deep knowledge of distributed systems tradeoffs: consistency, availability, fault tolerance, and performance at scale - Strong understanding of low-level</p>",
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            "description": "<p>Director of Tax at Together AI - San Francisco - Director of Tax San Francisco About the Role We&#39;re seeking an exceptional tax leader to establish and scale our tax function from the ground up. This is a rare opportunity to define global tax strategy across multiple jurisdictions within a high-growth, dynamic environment, partnering with a world-class team. Responsibilities Tax Strategy &amp; Planning - Develop and execute a comprehensive global tax strategy aligned with business objectives - Advise leadership on tax implications of corporate structure, financing, and expansion - Optimize effective tax rate through strategic planning and structuring Compliance &amp; Reporting - Lead all federal, state, and international tax compliance (income, sales/use, VAT, payroll tax etc.) - Ensure accurate and timely tax filings and provisions under U.S. GAAP (ASC 740) and applicable international local laws - Manage audits and inquiries from tax authorities Indirect Tax - Lead global indirect tax strategy for Together AI&#39;s AI infrastructure platform, APIs, and usage-based services - Advise on U.S. and international indirect tax matters, including sales tax and VAT/GST across key jurisdictions, with a focus on AI, cloud, and compute offerings - Assess the tax implications of fixed-fee subscription or usage-based AI services - Partner with Product, Finance, and Legal to structure enterprise contracts and bundled offerings in a tax-efficient and compliant manner, including input on pricing, invoicing, and go-to-market decisions Data Center and Infrastructure Operations - Advise on tax treatment of data center operations, including leasing and colocation arrangements - Manage sales and use tax on infrastructure and hardware purchases, including applying for</p>",
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            "description": "<p>Senior Platform Engineer, Voice AI at Together AI - San Francisco - Senior Platform Engineer, Voice AI San Francisco About the Role Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications - serving speech-to-text and text-to-speech models with best-in-class latency and reliability. We&#39;re looking for a Senior Platform Engineer to own the API and infrastructure layer for voice workloads. You&#39;ll build the real-time WebSocket and HTTP APIs that developers use to ship voice experiences, design autoscaling for latency-sensitive streaming workloads, and ensure our multi-provider voice platform is reliable enough for production voice agents handling millions of calls. This is a foundational hire on a small, high-impact team. Voice APIs have fundamentally different infrastructure requirements than text-based inference - bidirectional audio streaming, stateful connections, tight latency SLOs, and complex multi-model routing. You&#39;ll define how developers interact with Together&#39;s voice platform as we grow from early customers to the default infrastructure for voice AI. - Own the real-time API layer (WebSocket + HTTP streaming) that powers Together&#39;s voice platform. - Design autoscaling and orchestration for voice workloads running on tens of thousands of GPUs. - Build the developer experience - APIs, observability, and tooling - for a fast-growing product area. - Work with production voice customers (contact centers, AI agents, communication platforms) to ship what they actually need. - Join a small, early-stage team with outsized impact on a new product line. Responsibilities - Build and harden real-time WebSocket and HTTP streaming APIs for STT and TTS - including connection lifecycle</p>",
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            "description": "<p>Senior Machine Learning Engineer, Voice AI at Together AI - San Francisco - Senior Machine Learning Engineer, Voice AI San Francisco About the Role Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications - serving speech-to-text and text-to-speech models with best-in-class latency and reliability. We&#39;re looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You&#39;ll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro - pushing latency and throughput to the frontier. You&#39;ll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly. This is a foundational hire on a small, high-impact team. Voice inference has unique challenges - streaming audio, tokenization, real-time latency budgets - that require dedicated ML engineering focus. You&#39;ll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech. - Own the model serving stack that powers Together&#39;s voice platform across STT, TTS, and speech-to-speech. - Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference. - Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together&#39;s infrastructure. - Build quality evaluation frameworks that guide model selection for customers and inform the roadmap. - Join a small, early-stage team with outsized impact on a fast-growing product area. Responsibilities - Optimize inference performance for voice models (STT,</p>",
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