Apply without cover letter: Fullstack Developer to Spond - one of the world’s leading team management apps and a Norwegian tech success story! (Java/Go + React)

ABOUT FATHOM We created Fathom to eliminate the needless overhead of meetings. Our AI assistant captures, summarizes, and organizes the key moments of your calls, so you and your team can stay fully present without sacrificing context or clarity. From instant, searchable call summaries to seamless CRM updates and team-wide sharing, Fathom transforms meetings from a source of friction into a place for alignment and momentum.   We’re a small company that creates magical experiences through the hard work of focused builders. We try to live our values - Care Deeply, Seek Leverage, Share Ownership, Sustain Urgency, and Be Tenacious - in everything we do, every day.   We started Fathom to rid us all of the tyranny of note-taking, and people seem to really love what we've built so far: 🥇 #1 Most Used App of the Year on HubSpot for 2025 🔥 #1 Rated on G2 with 4,500+ reviews and a perfect 5/5 rating 🥇 #1 Product of the Day and #2 AI Product of the Year 🚀 Most installed AI meeting assistant on both the Zoom and HubSpot marketplaces 📈 We’re hitting revenue and usage records every week We think you’ll be pretty excited about Fathom too if you give it a try. Sign up today (it’s free)! ROLE OVERVIEW We're hiring a Model Performance Engineer to own the speed, cost, and reliability of our model inference stack, and to build the fine-tuning infrastructure that makes the rest of the AI team faster. This is not a research role. You'll be optimizing real systems serving millions of meetings — choosing between quantization trade-offs, debugging speculative decoding, or figuring out why one GPU family's tail latency explodes at high concurrency while another stays stable. You'll own two things: 1. Inference performance. You'll make our models faster and cheaper — speculative decoding, quantization, serving configuration, GPU selection, batching strategies, cold start mitigation, adapter swapping. Our traffic is extremely spiky (meetings end in 30-minute blocks), so you need to think about throughput curves. Our team greatly values offering a fast product. 2. Fine-tuning pipelines. The AI team constantly fine-tunes models for new tasks — distilling large teacher models for classification, training adapters for domain-specific behavior, DPO for preference tuning. Right now each project reinvents the training loop. You'll build repeatable infrastructure so an AI Engineer can go more quickly from dataset to deployed model. HOW YOU’LL HELP US WIN * Benchmark FP8 quantization across GPU families, find that FP8 KV cache causes catastrophic repetition loops, identify static quantization as 6% faster than dynamic on certain hardware, and ship a production config that gets 1.3x speedup with <1% quality degradation * Evaluate serving frameworks (vLLM vs SGLang) with speculative decoding — discover that ngram speculation degrades ASR quality while EAGLE3 draft models don't, and that torch.compile makes certain GPUs 7% slower * Build a fine-tuning pipeline that takes a JSONL dataset and produces an optimized tune ready for serving, so a teammate can train a small classifier in an afternoon instead of a week * Optimize GPU spend — know which GPU families are best for batch workloads (stable under high concurrency) vs latency-sensitive paths (40% faster, but tail latency blows up under load), and when a 30% cost premium isn't worth it * Debug production inference issues — trace a quality regression to a serving framework upgrade that changed the default attention backend, or find that audio format handling in the multimodal pipeline silently drops segments REQUIREMENTS Hard Skills: * Deep experience with LLM serving frameworks (vLLM, SGLang, TensorRT-LLM, or similar) — not just deploying them, but tuning them: attention backends, scheduling strategies, CUDA graph warmup, prefix caching * Hands-on quantization experience — you've gone beyond "apply FP8 and hope." You understand weight vs activation quantization, per-channel vs per-tensor scaling, and when dynamic quantization introduces more overhead than it saves * Production fine-tuning experience — LoRA/QLoRA SFT, familiarity with training frameworks (ms-swift, Axolotl, torchtune, or similar), understanding of data formatting, learning rate schedules, and how to diagnose training failures * Strong Python. You'll write serving infrastructure, benchmarking harnesses, and training pipelines — not notebooks * Comfort with GPU profiling and performance analysis. You should be able to look at a benchmark result and know whether the bottleneck is compute, memory bandwidth, or scheduling overhead Strong signal: * Cost modeling for GPU infrastructure — you've had to choose between GPU types and justify the tradeoff * Experience with multimodal models (audio/vision encoders + LLM decoders) * Experience with Modal, Ray Serve, or similar serverless GPU platforms * Understanding of audio processing (codecs, chunking, sample rates) * Experience building internal tooling that other engineers use — this role succeeds when the rest of the team ships faster Not required: * ML research background or publications * Prompt engineering expertise (we have a team for that) * Frontend or full-stack experience * Masters/PhD (though it's fine if you have one)   WHAT'S IN IT FOR YOU * The opportunity to shape the foundational software services of a growing company * A role that balances innovation and incremental improvement * A dynamic and collaborative engineering team * Competitive compensation and benefits * A supportive environment that encourages innovation and personal growth   WHY YOU SHOULD JOIN US * Opportunity for impact. We’re established enough to ship instead of fighting fires and early enough that your work will have a real impact. * Startup experience. You’ll work closely with our CEO, a 2X Founder/CEO with a background in computer science and product design. * We embrace being fully remote. We schedule meetings sparingly and instead heavily use async comms (Slack, Notion, Loom) ABOUT THE INTERVIEW * You’ll meet the entire team. We think it’s important that you get to meet everyone you’ll be working with. * No bullshit. Ask us anything you like. We’ve never understood why companies pretend they’re something that they’re not in the hiring process - you’re going to find out eventually so we’d rather you know who we are up front so we can both make sure this is a good fit for all involved. * Quick turnaround time. We know you have lots of options so we move fast usually in less than a week from start to finish. HOW TO APPLY Include a brief write-up or demo of inference optimization or model serving work you've done. We care about the reasoning behind your decisions — why you chose a specific quantization strategy, how you diagnosed a performance regression, what tradeoffs you navigated. A GitHub repo, blog post, or even a few paragraphs in your cover letter works.

About us RISE Research Institutes of Sweden is Sweden's research institute and innovation partner. In international collaboration with companies, academia, and the public sector, we contribute to a competitive business and a sustainable society. Our 3000 employees run and support all types of innovation processes. RISE is an independent, state-of-the-art research institute that offers unique expertise and around 130 test and demonstration environments for future-proof technologies, products, and services. Both applied research and long-term fundamental research activities are in line with RISE future strategy since the latter has the potential to revolutionize the industry with game-changing research findings from the bottom of the research value chain. At RISE, we support and encourage researchers’ independent as well as collaborative initiatives. Kista High-Speed Transmission lab and Elecrum cleanroom have excellent facilities for advanced Ph.D. student education and meeting real-life engineering design criteria. Part of the RISE strategy is to continue strengthening its collaboration with academia. We believe that it is an excellent opportunity to conduct high-quality academic research and a common student is an effective mechanism leading to mutual benefits. Why Join RISE and HCF-6G/Quantum? Access to state-of-the-art facilities, including the optical fiber draw tower at RISE Hudiksvall and the Kista High-Speed Transmission Lab and Electrum cleanroom. A collaborative environment with world-class partners, offering exposure to real-world challenges and cutting-edge solutions. An open and inclusive culture, emphasizing a balance between professional and personal life, with a strong commitment to diversity and gender equality. About the role  We are seeking a motivated and curious doctoral student to join our research environment and contribute to advancing knowledge within the field. In this position, you will engage in cutting-edge research, work closely with supervisors and collaborators, and actively participate in a dynamic academic community. The role includes conducting independent research, contributing to ongoing projects, publishing results in high-quality scientific venues, and participating in teaching and departmental activities. You will have access to strong supervision, a collaborative network, and opportunities for professional development. This is an excellent opportunity for candidates who are eager to develop their research skills, deepen their expertise, and make meaningful contributions to both academia and society. Your responsibilites: Develop and characterize HCF-based optical systems, targeting data rates beyond 200 Gbps and supporting multi-band 6G and or quantum transport solutions. Explore integration of HCF and modulator, Quantum Photonic Integrated Circuits (QPICs) technologies for ultra-low-latency, low-dispersion communication systems. Collaborate with partners at RISE, Umeå University, and leading Swedish industry players to design and test next-generation optical transceiver technologies and x-haul solutions. Actively disseminate research findings through scientific publications, conferences, and public outreach to promote understanding of the project’s significance. Who are you? In order to be admitted for PhD studies at third-cycle level at Umeå University the applicant is required to have completed a second-cycle level degree or least 240 credits of courses, of which at least 60 credits are at second-cycle level, or have an equivalent education from another educational system, or equivalent qualifications. To fulfil the specific entry requirements to be admitted for studies at third-cycle level in applied physics, the applicant must have completed courses of at least 120 credits within the field of physics or other related subject areas considered to be relevant for the project. The requirements must be fulfilled at the time of admission to postgraduate education and need not be met at the time of application. Desired Background: A Master’s degree in engineering physics, photonics, quantum or a related field. Strong lab skills are particularly important, as a significant portion of the research will involve hands-on experimentation at the Kista High-Speed Transmission Lab. Meritorious: Prior experience in optical communication systems. Knowledge of programming (e.g., LabView, C++, MATLAB) for experimental setups and data analysis. Understanding of semiconductor device technologies and system-level integration. Are we right for each other? At RISE, we like different and we are convinced that diversity contributes to an innovative environment where we together challenge boundaries and develop new knowledge for the future. With us, passionate problem solvers meet to solve some of the world's most important, and perhaps fun, problems. We can not promise you an easy job, but what we can promise you is a bunch of committed colleagues and some really exciting societal and industrial challenges to tackle. You will work in a dynamic environment that gives you development opportunities both professionally and personally. With us, you get the opportunity to make a real difference. Welcome to the entire Swedish research institute and innovation partners! Welcome with Your Application! For more information, please contact Linda Johansson, Unit manager, at linda.johansson@ri.se or Qin Wang, supervisor, at qin.wang@ri.se. The last application date is august 16th. Selection and interviews will be conducted continuously during and after the application period. Apply without cover letter. Our union representatives are Ingemar Petermann, SACO, +46 10 228 41 22 and Linda Ikatti, Unionen, +46 10 516 51 61.