(Senior) ML Platform Engineer (w/m/d)
at Billie
Berlin, Berlin, Germany -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 21 Nov, 2024 | Not Specified | 23 Aug, 2024 | N/A | Good communication skills | No | No |
Required Visa Status:
Citizen | GC |
US Citizen | Student Visa |
H1B | CPT |
OPT | H4 Spouse of H1B |
GC Green Card |
Employment Type:
Full Time | Part Time |
Permanent | Independent - 1099 |
Contract – W2 | C2H Independent |
C2H W2 | Contract – Corp 2 Corp |
Contract to Hire – Corp 2 Corp |
Description:
We are Billie, the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. We are to create a new standard for business payments and have made it our mission to simplify the purchasing experience for all businesses making it a tool for growth. Our solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes and a highly scalable tech platform. This makes us a deep-tech company building financial products, not the other way around. We love building simple and elegant solutions and we strive for automation and scalability.
WHO WE ARE LOOKING FOR:
- You are familiar with data versioning and data governance practices
- You have an understanding of model versioning, reproducibility, and Experimentation using tools like MLflow or Weights & Biases
- You have experience with machine learning workflows and MLOps tools such as Metaflow and MLflow
- You have knowledge of model deployment, serving, and monitoring using tools like AWS SageMaker, KServe, Seldon Core
- You are familiar with model training and inference using popular frameworks like Scikit-learn or (optional) TensorFlow, PyTorch
- You are able to design and implement model deployment pipelines using Github Actions, ArgoCD or similar
- You have experience using orchestration tools such as Airflow, ArgoCD, Prefect.
- You are able to collaborate with data scientists to deploy, monitor, and optimize ML models in production
Responsibilities:
Billie is proud of having its decision engine, consisting of a combination of cutting-edge machine learning models and business logics, built internally. This engine is a core functionality of the product allowing Billie to evaluate Fraud and Risk propensity efficiently.
As a Senior MLOps Engineer, you will be responsible for designing, building, and maintaining scalable and resilient machine learning pipelines that support real-time and batch model deployment and monitoring. Your expertise in ML model lifecycle management, CI/CD for machine learning, and MLOps best practices will be key in supporting various AI and machine learning initiatives across the organization.
In this job you will:
- Design and implement a scalable and reliable ML platform: Develop robust ML pipelines for real-time and batch processing using tools such as MLflow, Kubeflow, Metaflow
- Ensure that ML model predictions are delivered reliably and timely and are continuously monitored for performance, accuracy, and reliability.
- Maintain and extend our inhouse batch and real-time feature platforms that power dozens of feature pipelines allowing timely data for model inference and reliable point in time accurate data for model training
- Collaborate with cross-functional teams: Work closely with data scientists and data engineers to understand model and feature requirements and translate them into scalable and reliable pipelines.
- Drive continuous improvement: Actively contribute to the team’s knowledge sharing, participate in tech talks, and drive architectural decisions as the subject matter expert (SME) in MLOps.
- Stay abreast of industry trends and advancements in MLOps technologies to improve our ML Platform
REQUIREMENT SUMMARY
Min:N/AMax:5.0 year(s)
Information Technology/IT
IT Software - Other
Software Engineering
Graduate
Proficient
1
Berlin, Germany