Job Description

Join to apply for the Machine Learning Systems Engineer, Model APIs role at Anthropic2 weeks ago Be among the first 25 applicantsJoin to apply for the Machine Learning Systems Engineer, Model APIs role at AnthropicAbout AnthropicAnthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About AnthropicAnthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About The RoleWe are seeking a Machine Learning Systems Engineer to join our Model APIs team at Anthropic. This team is responsible for our Model Evaluations infrastructure and the APIs and infrastructure tailored for "Research Inference." In this role, you will build scalable systems that enable our researchers to effectively evaluate models and conduct inference tasks critical to our research mission. You'll collaborate with researchers across Anthropic to understand their needs and build infrastructure that makes their workflows more efficient and reproducible. Your work will directly impact Anthropic's ability to advance the frontiers of AI in a safe and responsible manner.ResponsibilitiesDesign, build, and maintain Model Evaluations infrastructure that enables researchers to systematically test and assess model capabilitiesDevelop and optimize APIs and infrastructure for Research Inference to accelerate the model development lifecycleCreate scalable data pipelines for collecting, processing, and analyzing research outputsImplement monitoring, logging, and performance optimization for research-focused inference systemsBuild intuitive interfaces and tools that allow researchers to configure, run, and analyze complex evaluation workflowsCollaborate with research teams to understand their evolving needs and translate requirements into reliable technical solutionsImprove system performance, reliability, and scalability to handle increasingly complex research needsParticipate in your team's on-call rotation, deliver operationally ready code, and exercise a high degree of customer focus in your workDocument systems thoroughly to enable broader adoption and ease of useYou May Be a Good Fit If YouHave 5+ years of software engineering experienceHave significant software engineering experience. If you’re a strong engineer with no ML experience, that’s okay!Are results-oriented, with a bias towards flexibility and impactHave experience with data infrastructure and processing large datasetsAre comfortable working independently and taking ownership of projects from conception to deliveryHave excellent communication skills and can collaborate effectively with research teamsAre proficient in Python and have experience with cloud infrastructure (AWS, GCP)Can anticipate the needs of research users and design systems that are both powerful and usablePick up slack, even if it goes outside your job descriptionEnjoy pair programming (we love to pair!)Care about the societal impacts of your work and are committed to developing AI responsiblyStrong Candidates May Also Have Experience WithHigh performance, large-scale ML systemsGPUs, Kubernetes, PyTorch, or ML acceleration hardwareBuilding evaluation frameworks for machine learning modelsWorking in or adjacent to ML research teamsDistributed systems design and optimizationReal-time inference systems for large language modelsPerformance profiling and optimizationInfrastructure as Code and CI/CD pipelinesDeadline to apply: None. Applications will be reviewed on a rolling basis.Annual SalaryThe expected salary range for this position is:$300,000 - $405,000 USDLogisticsEducation requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.How We're DifferentWe believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.Come work with us!Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.Seniority levelSeniority levelMid-Senior levelEmployment typeEmployment typeFull-timeJob functionJob functionEngineering and Information TechnologyIndustriesResearch ServicesReferrals increase your chances of interviewing at Anthropic by 2xGet notified about new Machine Learning Engineer jobs in San Francisco, CA.San Francisco, CA $135,000.00-$200,000.00 2 months agoSan Francisco, CA $166,000.00-$195,000.00 3 weeks agoSan Francisco, CA $130,000.00-$230,000.00 3 months agoSan Francisco, CA $140,000.00-$215,000.00 1 month agoResearch Engineer - Machine Learning (ML)San Francisco, CA $100,000.00-$200,000.00 1 year agoRedwood City, CA $123,000.00-$185,000.00 5 months agoSan Francisco, CA $140,000.00-$160,000.00 3 months agoSan Francisco, CA $130,000.00-$238,000.00 2 weeks agoSan Francisco, CA $88,000.00-$140,000.00 1 month agoMachine Learning, Optimization. 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Work at office, Remote work, Visa sponsorship, Flexible hours,

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