Skip to content
Sweep360Sweep360New York, NY

Software Engineer, Machine Learning (Systems)

Build and operate ML systems that process raw signals into reliable decisions across device, cloud, and offline environments for high-stakes cyber-physical security. Requires 5-10 years experience with production ML/LLM deployment, strong Python plus Go/TS, and system design expertise.

Up to 240k/yr
On-site5+ YOEML Engineering

About the role

Responsibilities

  • Own system behavior and data pipelines.
  • Design ingestion → reasoning → decision systems.
  • Improve the decision layer for consistency and reliability.
  • Close the loop from deployments → system learning.
  • Ensure system reliability across device, cloud, and partial connectivity.
  • Partner with RF / hardware / field teams to deliver for elite users globally (~10–15% travel).

Requirements

  • 5–10 years building and operating production systems.
  • Strong system design across APIs, pipelines, and data storage.
  • Deployed ML / LLM systems in production and improved them via feedback loops.
  • Strong Python, plus Go/TypeScript (or similar).
  • Comfortable working across device and cloud environments.
  • Able to debug production systems quickly and decisively.
  • Communicates clearly and operates independently.
  • U.S. Person status required.

Nice-to-Haves

  • Built RF / BLE classification systems and models from zero.
  • Handled streaming systems (Kafka, pub/sub).
  • Created LLM pipelines (prompting, retrieval, evaluation).
  • Designed for adversarial or security environments.
  • Built systems that run on-device as well as in the cloud.
  • Thrived in early-stage startup environment.

Compensation

  • Base salary up to $240,000, depending on qualifications, experience, and impact.
  • Total compensation includes equity, premium insurance, 401(k), flexible PTO, and other individual benefits.

Skills

PythonGoTypeScriptMachine LearningLLMsAPIsData PipelinesKubernetesKafkaStreaming Systems

Similar roles

ML Engineering jobs
Cerebras Systems

CoDesign & NextGen Performance Engineer

Cerebras SystemsSunnyvale, CA

Characterize, analyze, and optimize performance of state-of-the-art AI models on Cerebras' wafer-scale hardware. Build performance models, optimize kernels and compilers, debug runtime behavior, and develop visualization tools to influence next-gen AI architecture.

Salary not listed
On-site3+ YOEML Engineering
OpenAI

Research Engineer, Privacy

OpenAISan Francisco, CA

Research Engineer on OpenAI's Privacy team designing and prototyping privacy-preserving ML algorithms like differential privacy and federated learning at scale. Requires hands-on PETs experience, fluency in PyTorch/JAX, and a track record implementing or publishing novel privacy work.

380k – 445k/yr
HybridML Engineering
Console

Research Engineer

ConsoleSan Francisco, CA

Research Engineer building self-improving AI agent systems at Console. Develop eval/optimization loops, fine-tune specialist models, and improve agent reasoning over enterprise context using production data to drive measurable gains in quality, latency, and reliability.

200k – 350k/yr
On-siteML Engineering
Notion

Software Engineer, AI Platform

NotionSan Francisco, CA +1

Build and scale the shared AI platform foundations at Notion, enabling fast and safe shipping of AI products. Requires experience with LLM/ML platforms, strong ownership, and comfort across backend, infrastructure, and product code.

180k – 201k/yr
Hybrid5+ YOEML Engineering
Liftoff

Machine Learning Engineer

LiftoffCalifornia

Machine Learning Engineer building statistical models, optimization systems, and experiments for mobile ad tech economics on the Revenue Engine team. Requires PhD in CS/ML/Economics and industry experience applying ML or economics at scale.

215k – 275k/yr
RemoteML Engineering