Machine Learning Engineer

Shields Group; San Francisco (CA); À distance; USD 170 000 - 220 000; Plein temps

Avantages offerts par ce poste

Equity

Résumé du poste

Shields Group is seeking a Machine Learning Engineer to build real-time ML models for AI infrastructure and security. You will work on production-grade systems that classify agents vs attacks under load, with latency constraints and no offline batches.

You can work remotely from the Americas (UTC-8 to UTC-3) or onsite in San Francisco, joining a team focused on fast, secure inference and end-to-end ML pipelines from data ingestion to live serving.

Qualifications

• Production ML experience in real-world deployments.
• Python and ML frameworks (PyTorch or TensorFlow).
• SQL proficiency.
• End-to-end ML systems incl. feature pipelines, training and real-time serving.
• Data analysis, statistics, and experiment design.
• Strong software engineering and reproducible code.

Connaissances

Production ML

Python

SQL

ML systems

Experiment design

Software engineering

Anomaly detection

Weak supervision

Description du poste

Location: Remote, Americas (UTC-8 to UTC-3) or Onsite in San Francisco, CA

Employment Type: Full-Time

Compensation: $170,000–$220,000 Base Salary + Equity

Industry: AI Infrastructure / Cybersecurity / Agentic AI

About the Opportunity

Shields Group Search is partnering with an innovative AI infrastructure and security startup to hire a Machine Learning Engineer.

Build the models that tell a trusted agent from an attack, in real time and under load.

Our client verifies AI agents in real time, on the request path. That means the models behind it run under the same latency budget as the rest of production.

There is no offline batch job to hide behind, and no second chance if a call is slow or wrong.

Work Arrangement: You can work remotely from anywhere in the Americas, between UTC-8 and UTC-3, or on-site from the company's San Francisco office, whichever you prefer. The company is not hiring outside that time-zone band for this role.

What We're Looking For

Must-Haves

• Years of production ML experience, building, evaluating, and deploying models, not just research or notebooks.
• Strong Python and a modern ML framework (PyTorch or TensorFlow); solid SQL.
• Production ML systems end to end: feature pipelines, training, evaluation, and low-latency, real-time serving.
• Comfort with low-label and cold-start problems, including anomaly detection, unsupervised methods, weak supervision, and building evaluation sets and labels from scratch.
• Data analysis, statistics, and experiment design.
• Strong software engineering skills. You ship versioned, testable, reproducible code, not throwaway models.

Strongly Preferred

• Applied ML experience in fraud, risk, abuse, account integrity, or security.
• Graph ML / GNNs, sequence or behavioral modeling, or anomaly detection.
• LLM / NLP work, and familiarity with AI agents, including tool use, function calling, and MCP.
• Experience in adversarial settings, where the threat evolves against the model.
• Explainable, auditable, reproducible ML, with real model versioning.

Bonus Qualifications

• Experience with payment protocols (x402), agent identity (DID / VC), or crypto commitments (Merkle anchoring).

Compensation & Location

• Equity: Included
• Location: Remote across the Americas (UTC-8 to UTC-3) or onsite in San Francisco
• Employment: Full-Time

Apply

Interested in building production ML systems at the intersection of AI agents, security, and real-time infrastructure?