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Inference Service Data Scientist
3 weeks ago
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.
About The Role
We are seeking an experienced Data Scientist to join the Cerebras AI Inference organization. This role requires strong analytical skills, excellent teamwork and communication. The ideal candidate should have a blend of data engineering and data science experience working on a cloud SaaS product, be proactive, collaborative, and adaptable to a rapidly changing environment.
Responsibilities
- Build data pipelines and tooling for extracting and working with large datasets from diverse data sources, unifying them into a central data source.
- Ensure data integrity and implement data governance best practices.
- Analyze SaaS traffic data to uncover patterns in user behavior, application performance, and resource utilization.
- Develop predictive models to optimize cloud resource allocation and improve efficiency.
- Build interactive dashboards and visualizations to communicate insights to product, engineering, and business teams.
- Apply machine learning and statistical methods to detect anomalies, forecast demand, and optimize costs.
- Collaborate with cloud engineers and devops teams to integrate insights into real-time monitoring systems.
- Present findings and recommendations to stakeholders, influencing product and operational strategies.
Skills And Qualifications
- PhD or MS in Statistics, Mathematics, Data Science, Engineering, Computer Science, Physics, Economics, or a related quantitative field.
- 5+ of relevant industry experience in data engineering, analytics engineering, data science, data analysis, statistical analysis, or data modelling, preferably on a cloud SaaS AI product.
- Good understanding of SQL, NoSQL databases and big data solutions (e.g., Redis, Postgres, InfluxDB, Prometheus, Grafana).
- Experience in setting up data pipelines, querying, extracting, and manipulating large data sets using SQL and/or SQL-like languages.
- Technical proficiency with analytical tools for data extraction and analysis (e.g., Python, Pandas, R, or similar programming languages).
- Experience with data visualization and business intelligence tools (e.g., Tableau, Spotfire, MS Power BI, Omni, Mode, Hex, Looker, or similar tools).
- Experience with time-series forecasting and anomaly detection.
- Proven ability to work independently, define scope, and manage complex technical projects from concept to deployment.
- Strong organizational skills, teamwork, and comfort with open-ended problems in a dynamic startup environment.
- Strong communication and presentation skills.
- Experience as one of the first data scientists at an early/growth stage company a plus.
- Good understanding of LLM architecture a plus.
Location
- This role follows a hybrid schedule, requiring in-office presence 3 days per week. Please note, fully remote is not an option.
- Office locations: Sunnyvale, CA.
