Staff Machine Learning Engineer

kadence; San Francisco (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

A leading AI infrastructure company in San Francisco is looking for a Machine Learning Engineer with expertise in model development and scalable ML systems. The role involves creating essential components for multimodal data platforms and enhancing the developer experience for AI teams. Ideal candidates should possess strong Python skills and experience with ML frameworks like PyTorch or TensorFlow. This is a full-time position with a focus on advancing AI infrastructure solutions.

Qualifications

• 3+ years of experience building or deploying ML/DL models in production.
• Strong Python skills and experience with frameworks like PyTorch or TensorFlow.
• Demonstrated ability to own projects end-to-end.

Responsibilities

• Act as an in-house expert on modern AI engineering.
• Drive a best-in-class Developer Experience for AI/ML practitioners.
• Lead the design and development of high-performance, large-scale infrastructure.

Skills

Python

Machine Learning

Data Engineering

Experience with PyTorch

Tools

TensorFlow

AWS

Kubernetes

Job description

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