Ai Infrastructure Systems Engineer Jobs

About the role As Revenue Operations Manager for Enterprise GTM, you will own the measurement layer of our go-to-market engine. You will be the key to what is in the pipeline, what is converting, what is slipping, and, most importantly, why, and the . Your primary customers are our enterprise new logo and expansion teams across healthcare and life sciences, financial and professional services, TMT and energy, and public sector. We treat go-to-market as an engineered system. Architecture and design sit with the Director you report to. Instrumentation, measurement, and diagnosis sit with you. This is an individual contributor role with a wide mandate and real exposure. You will not manage a team. You will own numbers that go to the VP of Enterprise GTM, the executive staff, and the board. What you'll do Own the enterprise reporting layer Build and maintain dashboards that give real-time visibility into pipeline health, stage conversion, sales velocity, coverage ratios, and attainment against plan, cut by vertical, segment, and rep. Establish a single agreed definition for every core metric (pipeline created, qualified pipeline, coverage multiple, win rate, cycle time, ACV, committed vs. consumed) and defend it. One number, one source, one definition. Report bookings, recognized revenue, and consumption as the distinct measures they are, and make the bridge between them legible to people who do not live in the model. Run the operating cadence: weekly pipeline reviews, forecast calls in Salesforce and Clari, MBRs, QBRs, and the enterprise section of board reporting. Build stakeholder-specific, self-serve views so vertical leaders, sales development, and partnerships can answer their own routine questions without opening a ticket with you. Turn the data into insight Answer the hard "why" questions, e.g., why Stage 3 conversion dropped in financial services, which sourcing motions produce the highest-ACV enterprise deals, where multi-year agreements stall in legal

This posting is for candidates who attended COLM '26 and met with a member of our team. It was great meeting you at COLM 2026! Whether we chatted at our booth, during a poster session, or one of the workshops – we’re thrilled to connect with people who are passionate about pushing the boundaries of machine learning and AI. At Scale AI, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. We’re currently growing our team across multiple roles. If you're excited about the challenges we’re working on, drop your info here, and we’ll make sure someone from our team reaches out if there's a good fit with one of our open roles. Even if the timing isn’t quite right, we’d love to stay in touch. We look forward to continuing the conversation! In the meantime, you can read more about our research at https://labs.scale.com/ . Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and

About Us Are you ready to build the future of the supply chain? At Gather AI, we're not just creating software; we're pioneering a new era of warehouse intelligence. We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery. If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time. About the Team You'll join the Full Stack group within Cloud Services, which is being built now. Today, production and analytical workloads share a single database, and each product defines its own metrics. This team exists to fix that by designing and building the warehouse, transformation layers, and semantic model from the ground up. You'll work closely with Full Stack, ML, Product, Security, and Customer Success. About the Role Most data engineers early in their careers maintain one slice of a large, mature platform, or build pipelines against a model someone else designed years ago. This role is the opposite. As an SDE II, Data Engineer, you'll be one of the first engineers building Gather AI's data foundation from scratch. The work includes: Moving analytics off our production PostgreSQL database Writing the layered dbt models every product will share Defining metrics once so they stay consistent everywhere Linking structured records back to the drone images and video they came from You'll start by shipping well-scoped pipelines and models on our Drone product alongside senior engineers. From there, you'll grow toward owning a dat

Scale is a cutting-edge artificial intelligence startup dedicated to revolutionizing the way businesses leverage AI and machine learning technologies. We specialize in providing high-quality training data to fuel the development of AI models across various industries. As we continue to grow, we are seeking a seasoned Workplace professional for our People Team to join our dynamic team and play a crucial role in shaping the future of AI. Job Overview: As the Head of Workplace at Scale, you will lead our global Workplace function across ~10 offices worldwide. You will own our real estate portfolio, the Workplace budget, and the day-to-day experience in every office, managing our integrated facilities management partner (CBRE) and other outsourced service providers on the ground. You will build and lead the Workplace team, partner closely with Security on safety and preparedness, and work hand in hand with our international leaders as we expand. Your work will make our offices safe, well run, cost-effective, and places people want to be. You will: Real Estate Portfolio Management: Lead strategy, planning, and oversight of Scale’s global real estate portfolio across ~10 offices. Manage site selection, acquisition, lease negotiation and administration, renewals, and disposition of properties, working with brokers, landlords, and legal. Partner with International HR and business leaders to plan for growth and expansion into new markets. Use occupancy, utilization, and cost data to decide when to grow, consolidate, or exit space. Vendor & Service Delivery Management: Own the relationship with our integrated facilities management partner (CBRE) and other outsourced service providers across the global portfolio. Define and manage SLAs, KPIs, and regular performance reviews to deliver a consistent, high-quality experience in every office. Lead vendor sourcing, contract negotiations, and renewals. Budget & Financial Ownership: Own the global Workplace and Real Estate bu

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Please note: This is a three-month contract position requiring 40 hours per week. Snorkel AI is seeking a detail-oriented Payments Operations Associate to support the compensation lifecycle for a broad and growing network of Expert Contributors who power our LLM data development efforts. You'll be the front line for expert support - investigating and resolving contributor payment issues and discrepancies with clarity, professionalism, and technical rigor. You'll sit at the intersection of data operations, finance, product, and program teams, working within complex pay structures that include quality-based incentives. This is a great opportunity for a detail-driven, technically capable operator with a customer-support mindset to join a fast-moving team at the forefront of AI data development. Main Responsibilities Own the day-to-day queue of payment support tickets, serving as the primary point of contact for expert-facing communications on pay issues, discrepancies, and disputes. Investigate ticket issues by auditing contributor data and complex payment systems with dynamic bonus structures; flagging errors or inconsistencies Resolve contributor’s pay disputes with clear, professional communication, escalating complex or sensitive issues as needed. Build and maintain SQL queries, scripts, automations and payment audit dashboards to speed up ticket investigation and reduce manual, repetitive work. Collaborate with Delivery, Operations, Fin

At Bolna, we’re building tools that change how businesses leverage voice AI. We’re looking for a Product Growth Lead who will work closely with both our Marketing and Product teams to help more users get value from Bolna. You’ll own lifecycle campaigns and email marketing, build and monitor user funnels, and study how different cohorts adopt the platform. When you find a drop-off, you’ll help address it -whether that means a better email journey, clearer product education, or an experiment with the product managers. This is a hands-on, high-ownership role. You’ll work across user data, lifecycle campaigns, email, and product experiments: finding where different users get stuck, building ways to help them move forward, and measuring what changes. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities Own the user lifecycle: Build and improve journeys across signup, activation, repeat usage, paid conversion, retention, and reactivation. Find opportunities in the funnels: Track how users progress through Bolna and identify drop-offs by lifecycle stage, use case, cohort, and product capability. Drive product adoption: Help users discover and use the features relevant to them, whether they’re building their first agent or expanding an existing deployment. Run email and lifecycle campaigns: Own audience selection, copy, setup, testing, launch, and measurement for onboarding, product education, feature adoption, and reactivation campaigns. Turn insights into experiments: Work with engineering, and customer-facing teams to test changes to messaging, onboarding, and the product experience. Measure what works: Define clear success metrics for each initiative. Look beyond opens and clicks to understand whether users took the next step and continued getting value from Bolna. Required Skills Hands-on growth experience: 3+ years of experience building and running growth or lifecycle program

Scale is hiring a Staff/Senior Product Designer to lead product design for Scale’s rapidly growing ‘AI for Enterprise Data’ business unit. The mission of AI for Enterprise Data is to accelerate the deployment of AI by helping large enterprises solve their most ambitious challenges. This role will take on multiple products ranging from 0-1 initiatives to improving established products. This includes a suite of powerful AI tools for insurance AI, document processing, and more. Responsibilities Design end to end user flows, wireframes, high-fidelity mockups, and interactive prototypes for desktop web applications. Partner with Product Managers, Engineers, Data Scientists, and Operations team members to solve product and business challenges. Advocate for the voice of the user as the founding designer of the business unit. Prioritize and execute work in a fast paced environment with rapid timelines and high amounts of scope and ambiguity. Contribute to the evolution of our company-wide design system and interaction patterns. Take ownership to identify product gaps and rally support for proposed solutions. Qualifications Experience leading end-to-end B2B and enterprise web applications. Extremely high proficiency in Figma, fast execution speed is a must. Experience designing dashboards, data visualization, domain-specific editors, and forms. Understanding of front-end development processes for web interfaces. Strong communication and collaboration skills, including customer-facing meetings. Portfolio of product design projects that highlight your diversity of skills. Nice-to-haves Exposure to artificial intelligence, machine learning, and other technical concepts. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develo

About Us Are you ready to build the future of the supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery. If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time. About the Team You’ll be part of our Engineering organization, working closely with our Full Stack and WMS integration teams. The group builds and operates the production systems behind Gather AI’s warehouse intelligence platform, including APIs, integrations, data pipelines, databases, and application services used by our customers and internal teams every day. This is a small, distributed engineering team where engineers work across a broad technical surface area and have the opportunity to see their work through the full software development lifecycle, from design and development through deployment, production monitoring, troubleshooting, and improvement. About the Role We are hiring an SDE II, Full Stack, for our India-based team. You'll build and run the web platforms behind Gather AI's products - Drone Vision, MHE Vision and SAGE, from the customer-facing dashboards down to the APIs, Integration layers and data pipelines that serve them. This is a fully remote, hands-on engineering role for someone early in their career who already has experience building production software and wants broader ownership. You’ll work alo

Come join our legal team to work on the most exciting legal, policy, and operational issues at the leading edge of AI. We're seeking strong product lawyers with specialized expertise in intellectual property law. As product counsel, you will advise on all legal aspects of product development, launch, and operations - including regulatory compliance, user terms, and risk management - while bringing deep expertise in your specialized legal area. The ideal candidate will have deep subject matter expertise in intellectual property law, a technology background, and a demonstrable history of providing practical product counsel to solve complex, time-sensitive problems in close partnership with cross-functional teams. This role reoprts to the Associate General Counsel, IP & Product. You will: Strategic Product Advice: Lead IP strategy for product development, embedding IP protection into the full product lifecycle from conception to commercialization, while also advising on related product and regulatory matters in collaboration with the broader legal team. Cross-Functional Collaboration: Partner with Research, Product, Engineering, Operations, Communications, and Marketing teams to mitigate IP risks in product development, data licensing, and open-source governance. IP Counsel: Support management of Scale's worldwide IP portfolio including patents and trademarks; assist with patent prosecution and trademark registration and enforcement. Risk Mitigation: Advise on third-party, synthetic, and open-source data and models, ensuring compliance with licensing requirements; design open-source governance policies. Agreements: Support drafting and negotiation of commercial agreement provisions involving intellectual property. Specialized Expertise: Provide counsel on machine learning, robotics, and other technical areas, with ability to engage effectively with technical teams on complex engineering and product issues. Training: Develop and deliver IP and data licensing trainin

Role Overview As a Research Intern in the Model Shaping team, you will work on one or more of the following areas: Advanced post-training methods across supervised learning, preference optimization, and reinforcement learning New techniques and systems for efficient training of neural networks (e.g., distributed training, algorithmic improvements, optimization methods) Robust and reliable evaluation of foundation model capabilities The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. Past research led by Model Shaping interns resulted in the following publications: Escaping the Verifier: Learning to Reason via Demonstrations (ICML 2026) Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking (ICML 2026) ​​ FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models (ICLR 2026) Responsibilities Research and implement novel techniques in one or more of our focus areas Design and conduct rigorous experiments to validate hypotheses Document findings in scientific publications and blog posts Integrate the research results into Together products Requirements Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Familiarity with the Transformer architecture and recent developments in foundation models Preferred Requirements Prior research experience with training foundation m

Role Overview As a Research Intern in the Model Shaping team, you will work on one or more of the following areas: Advanced post-training methods across supervised learning, preference optimization, and reinforcement learning New techniques and systems for efficient training of neural networks (e.g., distributed training, algorithmic improvements, optimization methods) Robust and reliable evaluation of foundation model capabilities The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. Past research led by Model Shaping interns resulted in the following publications: Escaping the Verifier: Learning to Reason via Demonstrations (ICML 2026) Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking (ICML 2026) ​​ FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models (ICLR 2026) Responsibilities Research and implement novel techniques in one or more of our focus areas Design and conduct rigorous experiments to validate hypotheses Document findings in scientific publications and blog posts Integrate the research results into Together products Requirements Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Familiarity with the Transformer architecture and recent developments in foundation models Preferred Requirements Prior research experience with training foundation m

About The Role The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, directly contributing to the mission of advancing open and transparent AI. Our work operates at the critical intersection of cutting-edge model architectures, high-performance systems engineering, and deep hardware optimization. We focus on co-designing software, algorithms, and models to significantly lower the cost and latency of modern AI systems. As a research intern, you will dive into the complexities of distributed inference, compiler-aware optimization, and novel inference-time computation strategies (such as speculative decoding and phase-aware execution). You will be tasked with co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on areas like KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment (e.g., Mixture-of-Experts), and robust, reproducible evaluation under realistic serving workloads. Responsibilities Design and conduct rigorous experiments to validate hypotheses Communicate the plans, progress, and results of projects to the broader team Document findings in scientific publications and blog posts Requirements Currently pursuing a final year of Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Preferred Qualifications Prior research experience in foundation models , efficient machine learning , or ML systems . Publications at leading conferences in machine learning or systems (i.e., ML

About The Role The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, directly contributing to the mission of advancing open and transparent AI. Our work operates at the critical intersection of cutting-edge model architectures, high-performance systems engineering, and deep hardware optimization. We focus on co-designing software, algorithms, and models to significantly lower the cost and latency of modern AI systems. As a research intern, you will dive into the complexities of distributed inference, compiler-aware optimization, and novel inference-time computation strategies (such as speculative decoding and phase-aware execution). You will be tasked with co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on areas like KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment (e.g., Mixture-of-Experts), and robust, reproducible evaluation under realistic serving workloads. Responsibilities Design and conduct rigorous experiments to validate hypotheses Communicate the plans, progress, and results of projects to the broader team Document findings in scientific publications and blog posts Requirements Currently pursuing a final year of Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Preferred Qualifications Prior research experience in foundation models , efficient machine learning , or ML systems . Publications at leading conferences in machine learning or systems (i.e., ML

Scale's Public Sector customer base is growing rapidly, and you will ensure that these customers become passionate, lifelong Scale partners. In this role, you will lead technical delivery for one of Scale's most consequential Public Sector programs, building AI-enabled planning and decision-support capability for major Department of War commands. Partnering with the program's Delivery Lead, you own the technical shape of what we ship: how Scale's products come together, where we extend them, and what we build from scratch. You will also lead a team of Technical Program Managers, coaching them through ambiguous problems and multiplying what the group can take on. You will: Lead and mentor a team of Technical Program Managers who own the program's key technical delivery areas, allocating scope, raising the technical bar, and unblocking them as they interface directly with stakeholders and end users Own the technical shape of what we deliver: whether we are combining Scale's products in the right way, extending them in the right way for this program, and being deliberate about what genuinely warrants a bespoke build Plan and sequence releases alongside engineering, anticipating technical risk early and putting engineering trade-offs in terms stakeholders can decide on Serve as the senior technical voice to program stakeholders and users, translating operational needs into delivery decisions the team can execute against Drive innovation and transformation by diving deep into technical and operational challenges, solving undefined problems, and delivering impactful solutions for Public Sector customers Leverage technical concepts, tools, and expertise to create solutions from scratch or drastically improve existing solutions Use data, analytics, and technical expertise to align internal resources and create tools that directly add value to customers in the public sector space Transition AI/ML technologies and processes into working Public Sector products / solutio

Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share. The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that. Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves. Let’s achieve more, together. Where this role sits This role owns a product area end to end. Where the product marketer is the market lens, you are the person accountable for what we build, how it works, and whether it ships and succeeds. You lead a cross-functional team of engineers, designers, and applied AI specialists to turn strategy into a product members rely on. You own the roadmap for your area, the decisions inside it, and the outcomes it produces. You work at the center of the product organization, translating a clear point of view into shipped work that moves MINERVA and the COGENT architecture forward through each GR/GA milestone. Why this role exists In an AI market where capabilities can be copied in weeks, the advantage goes to teams that decide well and ship fast. Someone has to hold the point of view, make the calls, and keep a team building the right thing. Collective intelligence is hard product work: reasoning over messy knowledge, earning member trust, and fitting into how communities already operate. It needs an owner who can hold both the ambition and the details. The Senior Product Manager is that owner. You set direction for your area, make the hard prioritization calls, and are accountable fo