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kadence

Staff Machine Learning Engineer

kadence, San Francisco, California, United States, 94199

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Base Pay Range

$180,000.00/yr - $250,000.00/yr Direct message the job poster from kadence Senior Consultant | Kadence | AI + ML Talent Solutions

AI Infrastructure Company | $40M Series A About the Company

We are partnered with a developer-focused, open-source data infrastructure company that is led by a world-class team of open-source builders (including contributors to foundational data and storage technologies). Their platform powers cutting‑edge multimodal AI applications, from large‑scale vector search to advanced retrieval workflows and high‑performance data pipelines. They’re building the next‑generation foundation for AI teams working with large, complex, multimodal datasets. About the Role

We’re looking for a Machine Learning Engineer with hands‑on experience in model development (training, fine‑tuning, feature engineering) and a strong background in scalable data/ML systems. In this role, you’ll build core components of our multimodal data platform, shape the developer experience for AI teams, and collaborate with forward‑thinking customers and partners. Responsibilities

Act as an in‑house expert on modern AI engineering, with working experience across frameworks such as PyTorch or JAX. Drive a best‑in‑class Developer Experience to accelerate productivity for AI/ML practitioners. Lead the design and development of high‑performance, large‑scale feature engineering infrastructure. Partner closely with customers, design partners, and the broader open‑source community. Requirements

3+ years of experience building or deploying ML/DL models in production, or developing infrastructure that supports them. Strong Python skills and experience with frameworks such as PyTorch or TensorFlow. Demonstrated ability to own projects end‑to‑end, from design through delivery. Working knowledge of major cloud platforms (AWS, GCP, or Azure), including managed storage and compute services. Familiarity with monitoring/logging stacks like Prometheus, Grafana, or ELK/EFK. Nice to Have

Deep understanding of training architectures (PyTorch/JAX internals, CUDA kernel optimization, TPU environments). Experience building or managing feature stores (Feast, Tecton) or custom feature registries. Knowledge of Docker internals, Kubernetes, Slurm, and scheduling/orchestration systems. Strong Python engineering or Rust background. Prior experience working directly with customers. Experience building advanced monitoring and observability systems. Hands‑on experience with Kubernetes, Terraform, Docker, CI/CD tooling. Familiarity with large‑scale data/compute ecosystems (Spark, Flink, Delta Lake, Ray, Dataflow, Kafka, Airflow, Kubeflow, etc.). Why Join

You’ll join a deeply technical, mission-driven team building the infrastructure that will underpin the next wave of AI. You’ll work on open‑source technology, shape core system architecture, and directly influence how top‑tier AI teams interact with multimodal data at scale. Seniority Level

Mid‑Senior level Employment Type

Full‑time Job Function

Engineering and Research Industries

Technology, Information and Media and Software Development

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