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Sailplane · 1 day ago

Senior Machine Learning Engineer

San Francisco Bay Area

Full-time

Hybrid

Senior Level

$150K/yr - $300K/yr

5+ years exp

Sailplane is an early-stage AI infrastructure startup focused on building autonomous infrastructure for managing AI data centers. The Senior ML Engineer will lead the build and operations of LLMs in production, implementing MLOps best practices and collaborating with cross-functional teams.

Artificial Intelligence (AI)Information TechnologyMachine Learning

Responsibilities

Build, deploy, monitor, and operate LLMs in production on-premises in diverse customer environments

Implement MLOps best practices (CI/CD pipelines, containerization, continuous monitoring) to ensure reliable performance

Benchmark performance and recommend solutions to improve customer deployments including hardware sizing for target throughout (tokens per second, concurrent user sessions)

Experiment and iterate on models by tuning parameters and testing new approaches, continuously improving accuracy and effectiveness through rigorous evaluation

Document and ensure reproducibility of ML work, track experiments, code, and model versions to foster knowledge sharing and maintain high standards in the team

Collaborate cross-functionally with software engineers, customers, and product stakeholders

Qualification

Machine Learning EngineeringMLOpsContainerizationCloud PlatformsPythonML FrameworksPerformance BenchmarkingCommunication SkillsCollaboration

Required

5+ years of experience in ML engineering, preferably in a VC-backed startup environment

Hands-on experience deploying models at scale, including familiarity with containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP, or Azure) to build and operate ML systems in production

Experience with Prometheus, Grafana, distributed tracing, or ML-specific monitoring (Weights & Biases, MLflow for production)

Proficiency in programming (especially Python) and experience with modern ML frameworks/libraries such as TensorFlow, PyTorch, etc

Deep understanding of machine learning algorithms and the model development lifecycle (data preprocessing, training, parameter tuning, and evaluation)

Proven track record of delivering software that creates real value for users

Excellent communication skills with an ability to explain complex ML concepts to non-experts, and a collaborative approach to working with cross-functional teams and partners