Founding Senior Machine Learning Engineer
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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
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