Description
Job Title: Senior Machine Learning Engineer
Job Description:
Before 1965, it was extremely difficult and time-consuming to analyze complicated signals, like radio or images. You could solve it, but you had to throw a ton of compute at it. That all changed with the invention of the Fast Fourier transform, which could efficiently break that signal down into the frequencies that are a part of it.
The Risk Onboarding team is working on efficiently reviewing customers’ applications without compromising on quality. We are the front line of defense for preventing money laundering and financial crimes, building systems to verify that someone is who they say they are and that we are allowed to do business with them.
About Us:
At Mercury, we craft an exceptional banking experience for startups. Our team is focused on ensuring our products create a safe environment that meets the needs of our customers, administrators, and regulators.
Job Responsibilities:
As part of this role, you will:
- Partner with data science & engineering teams to design and deploy ML & Gen AI microservices, primarily focusing on automating reviews
- Work with a full-stack engineering team to embed these services into the overall review experience, including human in the loop, escalations, and feeding human decisions back into the service
- Implement testing, observability, alerting, and disaster recovery for all services
- Implement tracing, performance, and regression testing
- Feel a strong sense of product ownership and actively seek responsibility – we often self-organize on small/medium projects, and we want someone who’s excited to help shape and build Mercury’s future
Ideal Candidate:
The ideal candidate for the role has:
- 7+ years of experience in roles like machine learning engineering, data engineering, backend software engineering, and/or devops
- Expertise with:
- A full modern data stack: Snowflake, dbt, Fivetran, Airbyte, Dagster, Airflow
- SQL, dbt, Python
- OLAP / OLTP data modelling and architecture
- Key-value stores: Redis, dynamoDB, or equivalent
- Streaming / real-time data pipelines: Kinesis, Kafka, Redpanda
- API frameworks: FastAPI, Flask, etc.
- Production ML Service experience
- Working across full-stack development environment, with experience transferable to Haskell, React, and TypeScript
Total Rewards Package:
The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.
Salary Range:
Our target new hire base salary ranges for this role are the following:
- US employees (any location): $200,700 - $250,900
- Canadian employees (any location): CAD 189,700 - 237,100
Diversity & Belonging:
Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic.