Ai Oncology Portfolio Lead Jobs

Scale AI is seeking a highly motivated Senior Accountant to join our growing accounting team and assist in preparing day to day corporate accounting operations, supporting the month end close process, and helping to implement systems and processes that will support Scale as we continue to grow. You will also gain exposure to working with our international entities as we continue our expansion globally, working on some of the highest value aspects of the busienss. The ideal candidate thrives in a high-growth start-up, is detail-oriented, and has excellent interpersonal and communication skills. Additionally, the candidate has demonstrated the ability to build scalable cross-functional relationships through systems and process implementation. We hope you will join our team! You Will: Prepare journal entries and day to day corporate accounting activities, support the month end close process, and provide timely and accurate month-end close financials that are U.S. GAAP compliant Build or enhance balance sheet account reconciliation workpaper including reviewing and performing some clean-up of historical reconciliations and related balances Collaborate within Accounting and Finance teams on metrics, flux analysis, forecast, and projections and support preparation of the monthly reporting package Prepare documents supporting internal and external audits and ensure the successful completion of those audits Support the implementation of new systems, tools, and processes to streamline close and build scalable solutions to support the growth of the Company Identify and drive process improvements to gain efficiencies and reduce close timeline Develop, maintain and improve internal controls which relate to assigned areas Ideally You Have: Bachelor’s degree in Accounting; CPA or in the process of working towards one is preferred. 3+ years of relevant accounting experience; Combination of public accounting and industry experience preferred. Strong knowledge of U.S. GAAP. Ex

Scale Labs, Research Scientist — Frontier Risk Evaluations As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities; Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems; Publish evaluation methodologies and write technical reports for policymakers. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in m

Role Overview Scale’s EMEA GTM team is scaling rapidly across complex, high-stakes government markets. Our commercial motion spans country leads, account executives, strategists, solutions engineering, engagement management, partnerships, delivery, finance, legal, and product - all operating in fast-moving, region-specific environments. We are hiring a Sales Enablement Lead to build the enablement engine for EMEA GTM. This role will report to the Head of Commercial Strategy and Operations and will be responsible for ensuring every seller, strategist, and field partner has the knowledge, materials, onboarding, operating rhythms, and deal support needed to execute with speed and quality. This is a hands-on builder role. You will create the infrastructure that helps the team ramp faster, sell more consistently, reuse what works, and translate a complex AI product and public-sector GTM motion into practical field execution. What You’ll Do Build and own EMEA GTM onboarding Design and run a structured onboarding programme for new EMEA GTM hires across sales, strategy, solutions, and adjacent commercial roles. Create role-specific ramp plans, learning paths, certification moments, manager check-ins, and practical field exercises. Partner with Commercial Operations, People, Recruiting, and GTM and EPD leadership to ensure new hires understand Scale’s products, market context, customers, sales process, operating model, and expectations. Own the EMEA GTM knowledge base Build and maintain a centralised source of truth for EMEA GTM materials, including pitch decks, account planning templates, customer FAQs, qualification guides, use-case libraries, demos, proposal examples, talk tracks, win/loss learnings, and market-specific collateral. Keep materials current, easy to find, and clearly organised by market, role, product area, customer segment, and sales stage. Partner with central Sales Enablement, Product Marketing, Solutions Engineering, Legal, Finance, Delivery, and Pr

Scale is looking for a Support Systems & Routing Specialist to own and optimize the core infrastructure powering our contributor support operations. In this role, you will be responsible for configuring and maintaining systems like Zendesk, designing routing logic, and building scalable frameworks that ensure tickets are assigned accurately and efficiently. As our operations continue to grow, this role will play a critical part in ensuring our support systems scale seamlessly with increasing volume and complexity. You will partner closely with Support Ops, Product, Engineering, and cross-functional stakeholders to translate operational needs into robust system configurations. You will be part of a highly detail-oriented and systems-driven team, where your work directly impacts operational efficiency and contributor experience. This role is ideal for someone who thrives in building and improving systems that others rely on daily, and who enjoys solving complex operational challenges at scale. You will: Own end-to-end Zendesk configuration, including ticket forms, fields, macros, triggers, automations, SLAs, and views Design and maintain routing logic to ensure accurate ticket distribution across skills, queues, and teams Build and manage the support agent skills framework (skills, tiers, certifications, queue structures) Monitor and optimize queue health, load balancing, and ticket assignment accuracy Configure and maintain integrations across support tools and reporting systems Troubleshoot system issues and partner with Engineering or vendors when needed Collaborate with Support Ops, T&S, TPMs, and Product to implement and improve workflows Document system configurations, workflows, and best practices clearly Provide training and guidance to stakeholders on system usage and routing logic Ideally you’d have: Experience administering Zendesk or similar support CRM systems Experience designing routing logic or managing skills-based systems in high-volume envir

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Senior Emulation Engineer Location: India - Remote Job Description: At EnCharge AI, we are building the next generation of AI compute silicon — purpose-built for high-performance, low-power, and scalable AI inference. As an Emulation Engineer, you will play a critical role in validating complex AI accelerator architectures on emulation platforms before tape-out. This position is ideal for someone passionate about bridging the gap between hardware and software in fast-paced, deep tech environments. Responsibilities: • Set up and maintain Siemens Veloce emulation and prototyping platforms • Adapt SoC designs for Emulation and Prototyping • Develop and debug emulation testbenches and system-level environments • Support pre-silicon validation, power/performance analysis, and early software bring-up. Participate in silicon bring-up and validation. • Collaborate with design and verification teams to isolate design issues and accelerate debug. • Optimize performance of the emulation workloads and reduce turnaround time. • Work with firmware/software teams to enable use of emulators for OS and driver testing. Required Background: • BS/MS/Ph.D. in EE, CS, or related field with 7+ years of SoC design experience. • Experience with emulation platforms (Veloce, Palladium, or ZeBu) and FPGA-based prototyping systems (proFPGA, HAPS, or Protium) • Experience with emula

About Bolna Bolna is Voice AI infrastructure built for India - and now for the world. We help businesses deploy intelligent voice agents that can call, converse, and convert in any language, at scale. From collections to customer support to sales, our agents handle millions of conversations so humans don’t have to. We’re a YC F25 company, backed by General Catalyst, with 1,050+ paying customers and growing fast. Our team of ~25 is based in Bengaluru. The Role Every voice AI agent Bolna deploys makes real-time judgment calls - when to speak, when to go silent, when a customer is done talking, when to hand off. We’re building automated systems to grade these calls at scale, using LLMs as judges of call quality. But before you trust a model’s judgment, you verify it against a human’s. That’s this role. You’ll listen to real calls, annotate what actually happened, and check whether our automated systems - LLM-as-judge evals and quantitative signal detection - got it right. It’s precise, high-attention work, and it sits right at the center of how we know our voice agents are actually working. This is an internship role for someone early in their career who wants hands-on exposure to how a voice AI company builds trust in its own AI. What You’ll Do Annotation Listen to and annotate real customer calls - transcription review, issue tagging, labeling - using tools like Label Studio Follow (and help sharpen) annotation guidelines for a multilingual environment (Hindi, English, Hinglish, ) Verifying LLM-as-Judge Evaluations For calls flagged by our automated eval pipeline, verify whether the model’s call was actually correct - for example, confirming whether a detected barge-in (agent/customer talking over each other) genuinely happened by listening to the audio Mark agreements and disagreements clearly, with reasoning, so we can measure and improve model accuracy over time All tools needed for this will be provided Verifying Quantitative Measures Check system-flagged quantit

At Bolna, we’re building tools that change the way teams leverage Voice AI. We’re looking for a Founding Machine Learning Engineer to own the end-to-end lifecycle of building, evaluating, deploying, and improving models that power millions of production conversations. This is a high-impact, high ownership role where you won’t just work on Bolna’s ML stack—you’ll help build the foundation it scales on. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities: Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions. Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases. Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality. Set up human-in-the-loop pipelines to capture subjective quality at scale. Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system. Monitor performance in the wild, debug regressions, and iterate fast. Required Skills: 3+ years of hands-on ML experience with deep practical real-world experience in training models. Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.). Training data as a first-class problem. Experience designing data pipelines from collection, cleaning, labeling, deduplication, augmentation and treating data quality as a core engineering discipline. Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model. Speech model experience is a plus with real-time / streaming inference experience where you would have contributed to latency optimization

At Bolna, we’re building tools that change how businesses leverage voice AI. We’re looking for a Software Engineer to build reliable, scalable systems that power millions of production conversations across languages, industries, and telephony environments. This is a high-impact, high-ownership role where you’ll work on core platform problems across distributed systems, real-time communication, developer infrastructure, and customer-facing products. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities Build systems that operate at scale: Design and build backend services that support high-volume, real-time voice AI conversations with strong reliability, performance, and fault tolerance. Own features end to end: Take problems from product requirements and technical design through implementation, testing, deployment, monitoring, and iteration. Improve platform reliability: Build systems that are observable, resilient, and easy to debug. Identify bottlenecks, reduce failure rates, and improve system availability. Work on real-time infrastructure: Solve problems across telephony, streaming audio, webhooks, queues, scheduling, concurrency, and low-latency communication. Build for developers and customers: Improve APIs, SDKs, integrations, dashboards, and internal tools that make the Bolna platform easier to use and operate. Raise the engineering bar: Contribute to technical design reviews, code quality, testing standards, documentation, incident response, and engineering best practices. Required Skills Strong engineering fundamentals: Solid understanding of data structures, algorithms, databases, networking, operating systems, and distributed systems. Backend development experience: 2+ years of experience building and operating production backend systems using Python, Go, Java, Node.js, or a similar language. Production ownership: Experience shipping software to production and own

About AiDASH AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com. The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024. Join us in Securing Tomorrow Together! The Role As a Geospatial Analyst at AiDASH, you will produce high-quality annotated datasets from diverse imagery sources — satellite, LiDAR, aerial, and ground-based panoramic images and videos. Your work will directly feed AI/ML pipelines and client deliverables that protect critical infrastructure. This role demands a sharp eye for detail, comfort working with visual and geospatial data at scale, and fluency with modern AI tools. You won’t just annotate images; you’ll build AI-accelerated workflows that make the entire team faster. How You’ll Make an Impact Annotate and label imagery (satellite, LiDAR, aerial, drone, ground-based panoramic photos and videos) to identify, classify, and delineate features such as vegetation, assets, terrain, and infrastructure components Prepare,

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. This role is hybrid, based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Strong C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles. Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination. Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments. Curious and first-principles thinker who challenges conventional approaches to distributed system design. Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure. What We Need Architect, implement, and optim

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a skilled Software Engineer with a passion for building high-performance, low-level systems software. In this role, you’ll contribute to the development and optimization of the infrastructure that powers our cutting-edge processors, with a primary focus on C/C++ development and low-level programming. You'll work closely with large inference and training model development to further drive Scale Out software and hardware performance. This role is hybrid, based out of Toronto, ON. Who You Are Strong C or C++ systems engineer with a deep understanding of memory, threading, I/O, and low-level execution models. Experienced building low-level software, drivers, embedded systems, or performance-critical infrastructure. Comfortable working close to hardware and curious about how systems behave under the hood. Proficient with Linux systems programming and debugging tools such as gdb, strace, and perf. Structured problem solver who thrives in fast-paced, highly technical environments. What We Need Design, develop, and maintain core infrastructure software that interfaces directly with Tenstorrent hardware. Build low-level libraries and APIs for communication and synchronization across compute nodes. Optimize system-level software for performance, scalability, and reliability in distributed environments. Support hardware

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building the world’s fastest, most efficient AI compute clusters. TT-Fabric is the high-performance nervous system of this platform: the low-level networking layer that lets thousands of RISC-V and AI processors snap together into a single, massively parallel distributed supercomputer. If you love squeezing nanoseconds out of hot paths, designing protocols that move data at absurd scale, and turning messy hardware constraints into elegant distributed systems, this is an opportunity to shape the fabric that future AI models will run on This role is hybrid based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who We Are Strong systems engineer with deep C or C++ experience and comfort working in low-level or bare-metal environments. Passionate about hardware-software interaction, performance tuning, and eliminating inefficiencies at the protocol level. Curious about networking, synchronization, and communication across large clusters. Comfortable reasoning from first principles and challenging industry conventions. Motivated by building infrastructure that directly impacts large-scale

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. At Tenstorrent, we are building open, scalable compute for real AI workloads. As Director, Customer Hardware Engineering, you own the technical relationship with strategic customers and FAEs, turning their silicon needs into precise requirements for our hardware and software teams. You connect customer architectures to Tenstorrent platforms so their models run efficiently on our silicon. This role is hybrid, based out of Toronto, Austin, TX or Belgrade, Serbia. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced leader of customer-facing technical teams and Field Application Engineering organizations. Strong background across RTL, verification, and physical design for custom silicon programs. Systems thinker who understands how RTL choices affect software, performance, and customer solutions. Clear communicator who aligns customers, FAEs, and internal teams around shared technical goals. What We Need Own technical customer relationships and convert high-level asks into concrete engineering specifications. Coordinate with hardware and software leads on customer-specific NEO silicon configurations. Oversee RTL changes and NEO cus

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are seeking a GCC Compiler Engineer to design, develop, and optimize compilers for next-generation RISC-V and AI compute architectures. You will work across hardware and software teams to improve performance, programmability, and integration of our custom toolchains into real applications. This role is fully hands-on and central to how developers interact with Tenstorrent hardware across both traditional compute and advanced machine learning workloads. This role is Hybrid, based out of Santa Clara, CA, Austin, TX, or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced compiler engineer with deep knowledge of GCC and LLVM internals, comfortable optimizing for custom hardware targets. Strong C/C++ developer with a solid grasp of algorithms, data structures, and performance analysis. Collaborative and analytical, able to work across hardware and software domains to deliver efficient, high-performance toolchains. Passionate about enabling breakthrough compute architectures through compiler innovation and software-hardware co-design. What We Need Design, develop, and optimize GCC and/or LLVM compilers for Tenstorrent’s cust

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Our Tensix Team is building the next generation of high-performance AI compute systems. We’re looking for a Power Architect to drive architectural strategy, modeling, and design decisions that shape how power is understood and optimized across our products. This is a hands-on role with massive influence over how we build power-aware systems from the ground up. This role is hybrid, based out of Santa Clara, CA, Boston, MA, Austin, TX or Toronto. We welcome candidates at various experience levels. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are 15+ years experience with power estimation tools like PowerArtist, PtPX, RTL Architect, and PrimePower. Skilled in modeling and optimizing power at the architectural level, with deep knowledge of power-gating, voltage domains, and leakage control. Track record of influencing architectural and micro-architectural changes that meaningfully reduced design power. Proficient in Verilog HDL, Design Compiler, C/C++ and Python. Background in power-optimization of compute datapath and/or interconnects. What We Need Predict power consumption early in architecture and track it through RTL evolution. Propose architectural changes for power optimization across server and non-