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Team/ Role Paragraph: The Data Platform team builds and operates systems to centralize all of Coinbase's internal and third-party data, making it easy for teams across the company to access, process, and transform that data for analytics, machine learning, and powering end-user experiences. As a BE engineer on the team you will contribute to the full spectrum of our systems, from managing foundational processing and data storage, to building and maintaining scalable pipelines, to developing frameworks, tools, and internal applications to make data oriented services easily and efficiently available to other teams and systems.

What you’ll be doing:

• Build new services to meet critical product and business needs using Golang.
• Design scalable systems to solve novel problems with modern cloud technology and industry best practices.
• Articulate a long term vision for maintaining and scaling our backend systems and the teams running them.
• Work with engineers, designers, product managers and senior leadership to turn our product and technical vision into a tangible roadmap every quarter.
• Write high quality, well tested code to meet the needs of your customers. Debugging extremely difficult technical problems, and making systems and products both work better and are easier to deploy, own, operate and diagnose.
• Review all feature designs within your product area and across the company for cross-cutting projects. Be an owner of the security, safety, scale, operational integrity, and architectural clarity of these designs.

What we look for in you:

• You have at least 5+ years of experience in software engineering.
• You’ve designed, built, scaled and maintained production services, and know how to compose a service oriented architecture.
• You write high quality, well tested code to meet the needs of your customers.
• You’re passionate about building an open financial system that brings the world together.
• You possess strong technical skills for system design and coding
• Excellent written and verbal communication skills, and a bias toward open, transparent cultural practices.

Nice to haves:

• You have gone through a rapid growth in your company (from startup to mid-size).
• Experience with growth experiments or A/B testing frameworks.
• You have experience with Blockchain technology (such as Bitcoin, Ethereum etc..)
• You’ve worked with Golang, Docker, Rails, Postgres, MongoDB or DynamoDB.

Job Id : GPIN05IN

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🚀 Whatnot

Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG. We’re building the future of ecommerce, bringing together community, shopping and entertainment. We are committed to our values, and as a remote-first team, we operate out of hubs within the US, Canada, UK, Ireland, and Germany today.

We’re innovating in the fast-paced world of live auctions in categories including sports, fashion, video games, and streetwear. The platform couples rigorous seller vetting with a focus on community to create a welcoming space for buyers and sellers to share their passions with others.

And, we’re growing. Whatnot has been the fastest growing marketplace in the US over the past two years and we’re hiring forward-thinking problem solvers across all functional areas.

💻 Role

We are looking for intellectually curious, highly motivated individuals to become foundational members of our Core Machine Learning team. You will help drive the development of Whatnot’s machine learning operations and work with machine learning engineers across the company to build scalable design patterns that can be repeatedly used to achieve key business goals. Our ideal candidate has experience in spinning up ML platforms e.g. real-time model serving, approximate nearest neighbor retrieval, high-concurrency and low-latency scaling, feature stores, and model lifecycle monitoring. They are also willing and able to flex into an applied research role to develop models that leverage their own components.

What you'll do:

• Drive the development of the machine learning platform roadmap, staying abreast of emerging business needs that the machine learning platform can help address.
• Enhance our machine learning infrastructure--increase reliability, reduce latency, and continually improve the developer experience.
• Develop scalable machine learning design patterns that make it easy for machine learning scientists and engineers to safely deploy models to production.
• Improve model training, management, and monitoring
• Take a leading role in deploying ML models on business critical surfaces & flows.
• Define and advance our technical approach to scalable machine learning.
• Flex outside your comfort zone to help take on new challenges that emerge

👋 You

Curious about who thrives at Whatnot? We’ve found that low ego, a growth mindset, and leaning into action and high impact goes a long way here.

As our next Software Engineer, Machine Learning you should have 5+ years of experience, plus:

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Software Engineering, a related technical field, or equivalent work experience.
• 2+ years of professional experience setting up machine learning platforms–model serving, features stores, model registries, training pipelines, etc.
• 1+ years of professional experience developing software in Python
• Software engineering experience with a track record of applying practical methods to solve real-world problems on consumer scale data.
• Ability to work autonomously and drive initiatives across multiple product areas and communicate findings with leadership and product teams.
• Experience with operational, search, and key-value databases such as PostgreSQL, DynamoDB, Elasticsearch, Redis.
• Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana
• Familiarity with cloud computing platforms and managed services such as AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, Flink, Spark.
• Professionalism around collaborating in a remote working environment and well tested, reproducible work.
• Exceptional documentation and communication skills.
• Experience in applied statistical and machine learning fields e.g. Recommendations, Search, Fraud & Anomaly Detection, Experimentation and Causal Analysis preferred.

💰Compensation

For US-based applicants: $205,000 - $275,000/year + benefits + stock options

The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity in the form of stock options.

🎁 Benefits

• Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)
• Health Insurance options including Medical, Dental, Vision
• Work From Home Support
  • $1,000 home office setup allowance
  • $150 monthly allowance for cell phone and internet

• Care benefits
  • $450 monthly allowance on food
  • $500 monthly allowance for wellness
  • $5,000 annual allowance towards Childcare
  • $20,000 lifetime benefit for family planning, such as adoption or fertility expenses
• Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
• Parental Leave
  • 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.

💛 EOE

Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.

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