SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. They are seeking a founding Senior Machine Learning Engineer to help scale and operationalize their ML systems end-to-end, focusing on building the infrastructure and processes for efficient model development and deployment.
Responsibilities:
- Own SentiLink’s real-time ML model monitoring domain, leading the design, implementation, and ongoing improvement of monitoring systems and workflows
- Own our ML experimentation, model tracking, and versioning infrastructure, ensuring strong reproducibility and visibility across the model lifecycle
- Drive improvements to the model development process, reducing inefficiencies, improving code quality, resolving DS tooling gaps, and enabling faster iteration
- Serve as the primary technical owner of key touchpoints and interfaces between Data Science and Engineering/Infrastructure, defining standards and workflows
- Support efforts to optimize model behavior in production, including latency, reliability, maintainability, and operational best practices
- Investigate and diagnose model performance issues on an ad-hoc basis, including partner escalations and analysis of model behavior in real-world scenarios
- Evaluate, prototype, and recommend new ML infrastructure, tools, and data capabilities, partnering with DS to validate impact and support adoption
Requirements:
- 5+ years of relevant experience, with a degree in Computer Science, Engineering, Mathematics, or a related technical field
- Strong software engineering fundamentals, with proficiency in Python and SQL, and strong working knowledge of Git and modern CI/CD workflows
- Hands-on experience with ML experimentation and model tracking tools
- Strong proficiency with model monitoring and observability tooling
- Experience with ML infrastructure and orchestration technologies, such as Docker, Kubernetes, and workflow orchestration frameworks
- Familiarity with model serving and deployment frameworks
- Proven experience deploying and operating machine learning models as production services, with an emphasis on reliability and performance
- Demonstrated ability to build 0-to-1 prototypes and proof-of-concepts, rapidly standing up ML services and experimentation environments
- Experience designing, building, and optimizing ML pipelines for training, evaluation, and deployment
- Highly adaptable and able to learn quickly in fast-moving environments with evolving technical requirements
- Candidates must be legally authorized to work in the United States and must live in the United States