Senior AI​/ML Engineer

Location: West Hollywood / Los Angeles, CA
Work Model: On-site (5 days per week)
Employment Type: Full-Time
Compensation: $180,000–$350,000+ USD (depending on experience and seniority)

Applicants must be legally authorized to work in the United States. Visa sponsorship is not available for this role.

Our client is an AI-native technology company building a next-generation AI intelligence platform that ingests data from satellite feeds, autonomous sensors, logistics networks, structured enterprise data, and open-source intelligence (OSINT). These diverse data sources are fused into a live knowledge graph that generates calibrated probabilistic assessments in real time.

This is not a chatbot, prompt-engineering, or RAG-wrapper opportunity. The engineering team is building production-grade machine learning infrastructure where prediction accuracy, reliability, and system robustness directly impact real-world decision making.

You’ll join a small, senior engineering team building AI systems from the ground up, with significant ownership over architecture, production deployment, and the future evolution of the platform. The role offers the opportunity to solve complex machine learning problems in an environment where technical depth, first-principles thinking, and engineering excellence are highly valued.

We are looking for a Senior AI/ML Engineer to design, build, and operate the core machine learning systems powering the platform’s intelligence engine.

This role is best suited for engineers who have successfully shipped production ML systems—not just research prototypes—and who enjoy building scalable AI infrastructure capable of processing large volumes of heterogeneous data in real time.

You will work across the full machine learning lifecycle, including model development, probabilistic inference, data fusion, deployment, monitoring, evaluation, and continuous improvement.

• Design, build, deploy, and maintain production-grade machine learning systems.
• Own the lifecycle of multiple specialized prediction models supporting:
  • Temporal event prediction
  • Activity convergence modeling
  • Supply chain and logistics forecasting
  • Behavioral attribution
  • Trajectory prediction
  • Composite risk and threat scoring
  • Long-term anomaly detection
• Design ensemble architectures that combine multiple independent models into calibrated predictions.

• Build Bayesian inference pipelines supporting real-time prediction across multiple ingestion tiers.
• Implement probabilistic calibration techniques including Platt Scaling and related approaches.
• Produce confidence-scored predictions suitable for operational decision-making.
• Continuously evaluate and improve model reliability and calibration performance.

• Design large-scale ingestion pipelines processing:
  • Satellite imagery
  • Autonomous sensor data
  • Video and imagery streams
  • Logistics networks
  • Structured intelligence datasets
  • Open-source intelligence (OSINT)
• Maintain knowledge graph infrastructure using:
  • Neo4j
  • Qdrant
  • Apache Iceberg
• Implement entity resolution, deduplication, temporal versioning, and confidence-weighted data fusion across multiple sources.

• Build spatiotemporal event aggregation pipelines.
• Develop anomaly detection systems over streaming multi-source data.
• Implement clustering and sequence analysis techniques including DBSCAN and Dynamic Time Warping (DTW).
• Design systems capable of detecting adversarial signal manipulation, deception, and data poisoning.
• Develop testing frameworks that improve model robustness in contested data environments.

• Deploy production models using NVIDIA Triton Inference Server or comparable infrastructure.
• Build automated model versioning, promotion, A/B evaluation, and deployment pipelines.
• Implement human-in-the-loop feedback mechanisms.
• Maintain reproducible training lineage and auditable model lifecycle records.
• Monitor production KPIs including:
  • Calibration accuracy
  • Prediction lead time
  • False alert rate
  • Operational reliability

• Partner with…