Machine Learning Systems Engineer Model APIs
Machine Learning Systems Engineer Model APIs
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$ 300000 - 405000
1 Vacancy
Job Description
About Anthropic
Anthropics 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 Role
We 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. Youll 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 Anthropics ability to advance the frontiers of AI in a safe and responsible manner.
Responsibilities
- Design build and maintain Model Evaluations infrastructure that enables researchers to systematically test and assess model capabilities
- Develop and optimize APIs and infrastructure for Research Inference to accelerate the model development lifecycle
- Create scalable data pipelines for collecting processing and analyzing research outputs
- Implement monitoring logging and performance optimization for researchfocused inference systems
- Build intuitive interfaces and tools that allow researchers to configure run and analyze complex evaluation workflows
- Collaborate with research teams to understand their evolving needs and translate requirements into reliable technical solutions
- Improve system performance reliability and scalability to handle increasingly complex research needs
- Participate in your teams oncall rotation deliver operationally ready code and exercise a high degree of customer focus in your work
- Document systems thoroughly to enable broader adoption and ease of use
You May Be a Good Fit If You
- Have 5 years of software engineering experience
- Have significant software engineering experience. If youre a strong engineer with no ML experience thats okay!
- Are resultsoriented with a bias towards flexibility and impact
- Have experience with data infrastructure and processing large datasets
- Are comfortable working independently and taking ownership of projects from conception to delivery
- Have excellent communication skills and can collaborate effectively with research teams
- Are 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 usable
- Pick up slack even if it goes outside your job description
- Enjoy pair programming (we love to pair!
- Care about the societal impacts of your work and are committed to developing AI responsibly
Strong Candidates May Also Have Experience With
- High performance largescale ML systems
- GPUs Kubernetes PyTorch or ML acceleration hardware
- Building evaluation frameworks for machine learning models
- Working in or adjacent to ML research teams
- Distributed systems design and optimization
- Realtime inference systems for large language models
- Performance profiling and optimization
- Infrastructure as Code and CI/CD pipelines
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected salary range for this position is:
Annual Salary:
$300000 $405000 USD
Logistics
Education requirements: We require at least a Bachelors degree in a related field or equivalent experience.
Locationbased 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 were different
We believe that the highestimpact AI research will be big science. At Anthropic we work as a single cohesive team on just a few largescale research efforts. And we value impact advancing our longterm 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. Were an extremely collaborative group and we host frequent research discussions to ensure that we are pursuing the highestimpact 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: GPT3 CircuitBased 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.
Employment Type
Full Time
