Machine Learning Engineer - WFH

Whatnot is looking for a Software Engineer, Machine Learning to work across machine learning, platform, and product engineering teams., * Partner with machine learning, platform, and product engineering teams to develop models that solve real-world product problems.

• Productionize data science and machine learning artifacts for scalable applications.
• Develop scalable solutions across machine learning service and application serving stacks.
• Help establish technical direction for machine learning infrastructure.
• Build and improve feature construction patterns.
• Develop data and model monitoring systems.
• Support online and offline model scoring systems.
• Establish effective patterns for model usage across products.
• Define and advance technical approaches for scalable machine learning.
• Create dashboards, notebooks, technical documents, and presentations to communicate insights.
• Present findings to technical and non-technical stakeholders.
• Lead initiatives across multiple product areas.
• Develop well-tested and reproducible machine learning solutions.
• Contribute to a strong remote engineering culture through effective communication and documentation.

This position is suited to an engineer with strong Python and machine learning experience who can work independently, lead initiatives across product areas, and communicate technical findings effectively to engineering, product, and leadership teams., * Bachelor’s degree in Computer Science, Statistics, Mathematics, Software Engineering, a related technical discipline, or equivalent professional experience.

• Industry experience applying practical machine learning or statistical methods to real-world problems involving consumer-scale data.
• Extensive Python experience for data science and machine learning software development.
• Experience with technologies such as Flask, FastAPI, and Docker.
• Ability to work independently and take ownership of initiatives spanning multiple product areas.
• Experience communicating technical findings to leadership and product teams.
• Experience with operational databases such as PostgreSQL, DynamoDB, Elasticsearch, or Redis.
• Knowledge of applied statistics and machine learning.
• Experience in areas such as recommendation systems, search, fraud and anomaly detection, experimentation, or causal analysis.
• Familiarity with visualization and monitoring tools such as Datadog and Grafana.
• Understanding of cloud platforms and managed services.
• Familiarity with AWS services such as SageMaker, Lambda, Kinesis, S3, EC2, and EKS/ECS.
• Experience or familiarity with distributed technologies such as Kafka, Flink, or Spark.
• Ability to collaborate effectively in a remote working environment.
• Strong documentation, communication, and reproducibility practices.

Technical Skills

The role involves a broad machine learning and cloud technology stack, including:

Programming & ML: Python, statistical modeling, machine learning, recommendation systems, search, experimentation, causal analysis

Application & Deployment: Flask, FastAPI, Docker

Databases: PostgreSQL, DynamoDB, Elasticsearch, Redis

Monitoring & Visualization: Datadog, Grafana

Cloud & Infrastructure: AWS SageMaker, Lambda, Kinesis, S3, EC2, EKS/ECS

Data & Distributed Systems: Kafka, Flink, Spark, Candidates should be comfortable collaborating across engineering and product teams without relying exclusively on in-person communication. The ability to communicate technical findings clearly through dashboards, notebooks, documents, and presentations is specifically important for this position.

For US-based applicants, the stated base salary range is $153,000-$235,000 per year, plus benefits and stock options.

The salary range may cover multiple levels applicable to the position. Final compensation will depend on factors including level, relevant professional experience, skills, and expertise. The stated range represents base salary and does not include benefits or equity.

Benefits

Whatnot offers a range of benefits and allowances designed to support employees’ professional and personal needs.

Benefits include:

• Flexible time off policy.
• Company-wide holidays, including spring and winter breaks.
• Medical, dental, and vision insurance options.
• Work-from-home support.
• $1,000 home-office setup allowance.
• $150 monthly cell phone and internet allowance.
• Care benefits.
• $450 monthly food allowance.
• $500 monthly wellness allowance.
• $5,000 annual childcare allowance.
• $20,000 lifetime family-planning benefit for eligible expenses such as adoption or fertility.
• US 401(k) options, including Traditional and Roth accounts.
• Employer 401(k) matching of up to 4% of base salary in the US.
• Pension plans internationally.
• Parental leave.
• 16 weeks of paid parental leave plus one month of gradual return to work, subject to applicable country leave requirements.

Remote Work Environment

This is a remote position, making effective communication, documentation, reproducibility, and independent execution important aspects of the role.

Whatnot is a technology company that uses machine learning, data, and software to build consumer-facing products at scale. Its engineering organization works across machine learning, platform infrastructure, and product development to solve complex product and data challenges.

The company supports remote collaboration and emphasizes well-tested, reproducible engineering practices, strong documentation, and clear communication across teams.