Founding Senior Machine Learning Engineer
In OfficeSeniorNAArtificial IntelligenceData AnalyticsMachine Learning EngineerSQLGitPythonDockerKubernetes
Upload My Resume
Drop here or click to browse · PDF, DOCX, TXT
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.
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.
Benefits
- $170,000/year - $240,000/year + equity + benefits [across Senior & Staff level]
- Employer paid group health insurance for you and your dependents
- 401(k) plan with employer match (or equivalent for non US-based roles)
- Flexible paid time off
- Regular company-wide in-person events
- Corporate Values:
- Corporate Values:
- Deep Understanding
- Whatever It Takes
- Do Something Smart
Similar Jobs
8h ago
8h ago
8h ago
8h ago