ML Telemetry & Observability Engineer

Matter Intelligence; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity package

Health insurance

Dental & vision

Job summary

Matter Intelligence is seeking a Telemetry and Observability Engineer in San Francisco to bring datasets, training runs, models, and environments into a unified observable system. You will connect flight and mission reality with telemetry, traces, alerts, and reliability mechanisms to ensure safe deployments.

You will design telemetry schemas, instrument distributed training and inference, and establish service objectives to guide incident response and performance optimization.

Qualifications

• Experience with ML observability, telemetry, time-series systems, distributed training or inference, cloud infrastructure, or production AI platforms.
• Strong hands-on engineering skills in observability, automation, APIs, infrastructure, incident tooling, and systems debugging.
• Understanding of metrics, logs, traces, events, model and data monitoring, service objectives, capacity, release safety, and incident diagnosis.
• Ability to reason about AI failure modes including bad datasets, training instability, stale checkpoints, drift, version mismatch, environment bugs, and agent-tool failure.
• Experience designing telemetry schemas and correlation workflows across multiple systems, time domains, and ownership boundaries.

Responsibilities

• Build a common telemetry model linking mission state, datasets, code, checkpoints, accelerators, model and prompt versions, environment episodes, agent steps, tools, decisions, cost, latency, and feedback.
• Instrument distributed training, data loading, GPU utilization, checkpointing, experiment health, batch and online inference, and model-serving behavior.
• Instrument agent workflows across prompts, context, retrieval, memory, planning, tool calls, graph state, human intervention, evidence, outcomes, and safety controls.
• Connect planned-versus-actual mission state, hardware context, time, geometry, and geolocation to relevant datasets and model results.
• Establish actionable service objectives, alerts, incident interfaces, rollout and rollback signals, and escalation paths across platform, model, environment, and agent failures.
• Build capacity and cost visibility across storage, processing, accelerators, training, evaluation, inference, retrieval, and agent execution.

Skills

ML observability

Distributed training

Cloud infrastructure

APIs

Systems debugging

Time-series systems

Tools

Telemetry schemas

Job description

Matter Intelligence is seeking a Telemetry and Observability Engineer in San Francisco to bring datasets, training runs, models, and environments into a unified observable system. You will connect flight and mission reality with telemetry, traces, alerts, and reliability mechanisms to ensure safe deployments.

You will design telemetry schemas, instrument distributed training and inference, and establish service objectives to guide incident response and performance optimization.