Peter W. Njenga

Lead Perception Engineer / Los Angeles, CA

Peter W. Njenga

Lead Perception Engineer building autonomy, ML infrastructure, and production AI systems.

PhD dropout with nearly a decade of experience building perception and autonomy systems from the ground up. Based in Los Angeles, Peter works across aerospace missions, real-time ML infrastructure, and production AI for hospitals and defense agencies.

Focus

Perception

Object detection, 3D pose estimation, visual-inertial odometry, sensor fusion, and real-time state estimation.

AI platforms

Production ML pipelines, GPU inference, retrieval systems, vector databases, and model deployment infrastructure.

Founder execution

Zero-to-one product development, customer discovery, technical writing, enterprise pilots, and team leadership.

Selected work

  1. March 2024 - Present

    Lead Perception Engineer

    AstroForge / Seal Beach, CA

    Developed computer vision-based perception pipelines for autonomous asteroid approach and characterization using PyTorch object detection and 3D pose estimation.

  2. March 2023 - March 2024

    Founder & CEO

    Reframe AI / Los Angeles, CA

    Led customer discovery and product development, translating GTM team workflows into AI agents that reduced manual research.

  3. March 2020 - March 2023

    Lead AI Platform Engineer

    Vidrovr / New York, NY

    Led development and deployment of a video search and disinformation monitoring system used by major media companies and U.S. federal agencies.

  4. January 2016 - September 2019

    Founder & CTO | Acquired

    Behold AI / London, England

    Architected and led development of a deep learning-powered medical diagnostics platform for real-time radiology triage across NHS trusts and U.S. hospital systems.

Skills

Programming Languages

Python, C/C++, Rust, CUDA, Verilog, shell scripting, system automation, ML pipelines, real-time systems, firmware, high-performance services.

ML / Systems

PyTorch, TensorFlow, object tracking, pose estimation, medical imaging, vector databases, Kubeflow, Airflow, RAG pipelines.

Cloud / Infra

Kubernetes, Docker, Terraform, AWS, GCP, Azure, Supabase, CI/CD, Linux/UNIX, GPU scheduling, distributed caching.

Datastores / Observability

PostgreSQL, Cassandra, Redis, Elasticsearch, Prometheus, Grafana, OpenTelemetry, Sentry.

Frameworks / Tools

FastAPI, Flask, Django, React, Git, REST APIs, gRPC APIs, technical writing, cross-functional leadership.

Education

  1. August 2013 - May 2015

    MS, Computer Engineering

    Columbia University, New York, NY

    Focus in computer vision and machine learning.

  2. August 2010 - May 2013

    BS, Electrical Engineering and Computer Science

    UC Berkeley, Berkeley, CA

    GPA: 3.9/4.0. Focus on high-performance computing systems.