{"id":13091,"date":"2025-10-24T13:37:11","date_gmt":"2025-10-24T13:37:11","guid":{"rendered":"http:\/\/kick-start.us\/?post_type=job_listing&#038;p=13091"},"modified":"2025-10-24T13:37:11","modified_gmt":"2025-10-24T13:37:11","slug":"california-398-research-engineer","status":"publish","type":"job_listing","link":"https:\/\/kick-start.us\/it\/vaga\/california-398-research-engineer\/","title":{"rendered":"Ingegnere di ricerca"},"content":{"rendered":"<p>Descrizione completa del lavoro<br \/>Applied Compute builds in-house, highly specialized agent workforces for the most advanced enterprises in the world.<br \/>Today\u2019s state-of-the-art AI is no longer a one-size-fits-all model, but a tailored system that continuously learns from a company\u2019s own processes, data, expertise, and goals. The same way companies compete today by having the best human workforce, the companies building for the future will compete by having the best agent workforce supporting their human bosses. We call them Model Employees, and we are already building them today.<\/p>\n<p>We are a small, talent-dense team of engineers and operators who have built some of the most influential AI systems in the world, including reinforcement learning infrastructure at OpenAI and data foundations at Scale AI, with additional experience from Together, Two Sigma, and Watershed.<\/p>\n<p>We\u2019re backed by Benchmark, Sequoia, Lux, Greenoaks, Conviction, and Elad Gil. We work in-person in San Francisco.<\/p>\n<p>The Role<br \/>As a founding Research Engineer, you\u2019ll join a mission-driven team training frontier-scale models and turning them into specialized experts for enterprise and scientific applications. You will design and run experiments at scale, developing methods for synthetic data generation, distillation, and continual learning across trillions of tokens.<\/p>\n<p>You\u2019ll work closely with RL researchers, engineers, and operators to create evals that guide scientific data curation, and you\u2019ll collaborate with supercompute engineers to scale compute-efficient LLM training to thousands of GPUs. You\u2019ll build tools and pipelines for yourself and others, enabling faster iteration cycles and deeper investigation into how data shapes intelligence.<\/p>\n<p>This role is perfect for an engineer who loves working at the intersection of research and systems. You care about both the rigor of experimentation and the performance of large-scale training, and you\u2019re motivated to push the boundaries of what\u2019s possible with data, models, and compute.<\/p>\n<p>What You\u2019ll Do<\/p>\n<ul>\n<li>Train large language models on curated datasets spanning trillions of tokens<\/li>\n<li>Develop scalable methods for synthetic data generation, distillation, and continual learning<\/li>\n<li>Design and run experiments to understand scaling laws and compute-optimal hyperparameters<\/li>\n<li>Explore cutting edge RL techniques and build synthetic datasets<\/li>\n<li>Partner with infrastructure engineers to scale training efficiently across thousands of GPUs<\/li>\n<li>Build high-performance internal tools for probing, debugging, and analyzing training runs<\/li>\n<li>Contribute to the broader research ecosystem through publications, open-source work, or shared benchmarks<\/li>\n<\/ul>\n<p>What We\u2019re Looking For<br \/>Technical expertise<\/p>\n<ul>\n<li>Experience training LLMs or other large-scale deep learning models<\/li>\n<li>Familiarity with scaling laws, optimization, and compute\/resource tradeoffs<\/li>\n<li>Proficiency in PyTorch, JAX, or similar ML frameworks, and experience with distributed training<\/li>\n<li>Ability to manage and analyze experiments at scale, including data pipelines and logging systems<\/li>\n<\/ul>\n<p>Research intuition<\/p>\n<ul>\n<li>Strong experimental design skills, with the ability to connect model performance to data and training choices<\/li>\n<li>Comfort bridging research ideas into production-scale systems<\/li>\n<li>A bias toward fast iteration, with rigor in evaluation and reproducibility<\/li>\n<\/ul>\n<p>Strong Candidates May Also Have<\/p>\n<ul>\n<li>Experience generating billions of tokens of high-quality synthetic data<\/li>\n<li>Background in reinforcement learning, continual learning, or multi-modal LLMs<\/li>\n<li>Previous experience in high-performance computing environments or working with large-scale clusters<\/li>\n<li>Contributions to open-source ML research or infrastructure<\/li>\n<li>Demonstrated technical creativity through published research, OSS contributions, or side projects<\/li>\n<\/ul>\n<p>Logistics<\/p>\n<p>Location:\u00a0This role is based in San Francisco, California.<br \/>Benefits: Applied Compute offers generous health benefits, unlimited PTO, paid parental leave, lunches and dinners at the office, and relocation support as needed. We work in-person at a beautiful office in San Francisco\u2019s Design District.<br \/>Visa sponsorship:\u00a0We sponsor visas. While we can\u2019t guarantee success for every candidate or role, if you\u2019re the right fit, we\u2019re committed to working through the visa process with you.<br \/>Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000\u2013$250,000 USD.<\/p>\n<p>We encourage you to apply even if you do not believe you meet every single qualification.<br \/>As set forth in Applied Compute\u2019s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.<\/p>","protected":false},"author":10,"featured_media":0,"template":"","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"pmpro_default_level":"","_promoted":"","_job_location":"California","_application":"https:\/\/www.indeed.com\/viewjob?jk=9085dfa9e48488b3&from=mobRdr&utm_source=%2Fm%2F&utm_medium=redir&utm_campaign=dt","_company_website":"","_company_tagline":"","_company_twitter":"","_company_video":"","_filled":0,"_featured":0,"_remote_position":0,"_job_salary":"","_job_salary_currency":"","_job_salary_unit":"","_joinchat":[]},"job-types":[398],"class_list":{"0":"post-13091","1":"job_listing","2":"type-job_listing","3":"status-publish","4":"hentry","5":"pmpro-has-access","7":"job-type-h1-b"},"_links":{"self":[{"href":"https:\/\/kick-start.us\/it\/wp-json\/wp\/v2\/job-listings\/13091","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/kick-start.us\/it\/wp-json\/wp\/v2\/job-listings"}],"about":[{"href":"https:\/\/kick-start.us\/it\/wp-json\/wp\/v2\/types\/job_listing"}],"author":[{"embeddable":true,"href":"https:\/\/kick-start.us\/it\/wp-json\/wp\/v2\/users\/10"}],"wp:attachment":[{"href":"https:\/\/kick-start.us\/it\/wp-json\/wp\/v2\/media?parent=13091"}],"wp:term":[{"taxonomy":"job_listing_type","embeddable":true,"href":"https:\/\/kick-start.us\/it\/wp-json\/wp\/v2\/job-types?post=13091"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}