Background:OctoML is a fast-growing startup developing the industry's leading machine learning deployment platform. We enable customers to take ML models to production faster and with greater performance. OctoML's mission is to make AI sustainable and accessible so it can be used to thoughtfully improve lives.We are founded by the creators of Apache TVM, the open-source stack for ML performance and portability. TVM automates the optimization of machine learning models on CPUs, GPUs, edge devices, and specialized accelerators. Building on the success of TVM, our cloud-based OctoML Platform provides choice, automation, and performance to organizations that are taking their trained models to production.Our team consists of experts in machine learning, hardware, cloud services, and compilers. We have secured over $130M in venture capital funding and our team will more than double in size over the next year. We're based largely in Seattle, but have a remote-first culture with people working all over the US and elsewhere in the world.We dream big but execute with focus and believe in creativity, productivity, and a balanced life. We value diversity in all dimensions and are always looking for talented people to join our team!Overview:This is the perfect opportunity to bring your data science mindset and toolkit to the world of machine learning models, processors, and compilers. You will be responsible for surfacing insights and driving decisions based on our core proprietary model performance datasets, including producing actionable data views for our company's leadership, marketing, and product teams, and selected key strategic partners.The world of machine learning acceleration is, fundamentally, a world of data. Much of that data is gathered to answer the question 'how fast does this model run on this device?' - but that is no simple task, given the need to control the dozens of relevant parameters and configurations each time a model runs in production.If you are passionate about the use of data to make key business decisions and are familiar with machine learning models and trends, this role is for you!As the first formal hire in this function, we will expect you to bring a demonstrable set of past experiences organizing and managing data. We are also looking for colleagues who are as deeply engaged in these questions as we are - who can think independently, identify new possible approaches, and propose solutions.In this role, we'll expect you to be a highly capable individual contributor who works closely with stakeholders of varying degrees of data science familiarity across Engineering, Product, Go-To-Market, and our entire company leadership. We'll expect you to demonstrate strong performance in the core competencies of data science - data ingestion and cleaning, data management, querying methods, experiment management, and tracking, and system design - but also be able to think strategically about what questions our company needs to answer to be successful.Ideal candidates will have direct experience bringing data science to life in a new organization, demonstrate an understanding of the full data science lifecycle, and articulate current data science industry-wide challenges and dynamics. Experience with both startups and large organizations is preferred.However, we value aptitude over experience and are most interested in future colleagues who are able to apply their core data science competencies to an ever-changing array of fascinating problems and possible solutions.If you love building and shipping great data science results, want to deepen and broaden your experience in ML-based software engineering, and feel energized by working with superb technologists in a supportive and collaborative environment, this role is for you!Core Responsibilities:

• Maintain and improve our existing data management tools and processes.
• Develop and communicate key insights regarding model performance and hardware targets to internal and external stakeholders.
• Experience analyzing performance data in HPC, embedded, and/or GPU workloads.
• Build the appropriate tools and mechanisms to allow others to engage in data science projects on their own.
• Drive continuous improvement in our data science culture.

Basic qualifications include:

• 3+ years of experience in data science roles delivering high value to your end-users.
• Strong understanding of data science use cases, methods, tools, and workflows.

• Applied experience developing data analysis tools using one or more of Python, SQL, BigQuery, Pandas, Jupyter, Matplotlib, and Seaborn.
• Familiarity with data visualization methods and techniques.
• Demonstrated ability to succeed in fast-growing organizations.
• Experience working with highly technical tools and platforms.

• Master's degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience.

Ideal candidates will have the following:

• Demonstrated data science thought leadership.
• Experience working with data science in machine learning.

Location: Seattle, WA; San Francisco, CA; or remoteOur Benefits:OctoML aims to provide the resources that employees need to be healthy and comfortable.

• 100% employer paid premium (for employee and dependents) with a low-deductible plan
• Remote and telework setups for employees (post-COVID)
• Flexible work hours
• 4 weeks paid personal time off + company paid holidays and company downtime 2x per year
• Family & Medical Paid Time Off (includes Maternity, Paternity, Adoption, among others)

OctoML is committed to creating a diverse environment and is proud to be an equal opportunity employer. We hire based on an evaluation of abilities and effectiveness. We don't discriminate against employees on the basis of any other personal characteristic or any classification protected by federal, state, or local law. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.