We're looking for a Lead Machine Learning Engineer with deep expertise in Bayesian modeling, strong infrastructure skills, and a passion for taking experimental models into real-world, production-ready systems.
This role is key to building a scalable Bayesian-as-a-Service platform that can be deployed across industries like music, gaming, media, and consumer goods.
This is a highly technical position combining applied statistics, backend engineering, and MLOps.
You'll help design, build, and deploy probabilistic modeling solutions from the ground up, working closely with a founding team.
English level: B2/C1
What this role is about
This position is ideal for someone who enjoys:
- Translating complex Bayesian models into scalable, user-facing APIs.
- Designing robust ML infrastructure that supports real-time inference and scalability.
- Collaborating with cross-functional teams to shape reusable solutions for different business verticals.
You'll lead the full model lifecycle: from statistical design to deployment, monitoring, and continuous improvement.
Key responsibilities
- Design and optimize Bayesian models with hierarchical priors and uncertainty quantification.
- Build scalable ML infrastructure on AWS (EC2, S3, Lambda, API Gateway, CloudWatch, IAM, RDS, Athena, SageMaker).
- Develop and deploy production-ready APIs (Flask or FastAPI) to serve models.
- Manage CI/CD pipelines and automated deployments using GitHub.
- Optimize GPU-accelerated inference for large-scale execution.
- Work closely with stakeholders to adapt models to various use cases across multiple industries.
Technical requirements
Bayesian Modeling
- Deep understanding of probabilistic inference and hierarchical modeling.
- Experience with PyMC, NumPyro, or Stan.
- Ability to communicate technical results clearly to non-technical audiences.
ML Engineering & Infrastructure
- Strong hands-on experience with AWS services relevant to ML pipelines.
- Proven skills in scalable ML workflows and model serving.
- GPU computing experience is a plus.
Backend & MLOps
- Advanced Python skills with clean, maintainable code.
- Experience with Flask or FastAPI for building scalable APIs.
- Proficiency in CI/CD, GitHub workflows, and version control.