Machine Learning -Reward Modeling

Immediate need for a talented Machine Learning -Reward Modeling. This is a 12+ months opportunity with a possible extension or hire with long-term potential and is located in Mountain View, CA (Onsite). Please review the job description below and contact me ASAP if you are interested. Job ID: 26-20943 Pay Range: $100 - $110/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location). Key Responsibilities: • Design and train prompt injection detection models and prompt safety classifiers that operate on both inputs to and outputs from agentic AI systems. • Build hybrid deployment pipelines that split safety inference between on-device (phone, XR/AR) and cloud, optimizing for latency, privacy, and detection coverage. • Apply post-training techniques (e.g., RLHF, reward modeling, policy optimization) to optimize guardrail model performance, calibration, and robustness against adaptive adversaries. • Curate and generate adversarial training data: direct and indirect prompt injections, jailbreaks, tool-use exploits, and unsafe-output cases drawn from red-teaming and production signals. • Build evaluation harnesses that measure attack success rate, false-positive rate, latency, and on-device footprint across model iterations and threat categories. • Partner with agent, device, and platform teams to integrate safety models into mobile-use agents, XR/AR assistants, and cloud agentic workflows, and to close the loop from production incidents back into training data. • Work cross-functionally with security researchers, modeling teams, and product engineers; document methods and, where appropriate, contribute to patents and publications. Key Requirements and Technology Experience: • Must have skills: - 3+ years of industry experience in ML engineering or Applied AI research • M.S. or Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related field; or B.S. with equivalent industry experience. • Python and PyTorch (or JAX/TensorFlow), with solid software engineering fundamentals. • Hands-on experience post-training LLMs with RLHF, DPO, RLAIF, or reward modeling • Hands-on experience with ML deployment (ExecuTorch, Core ML, TFLite, MLC-LLM, vendor NPU toolchains) and model compression (quantization, distillation, pruning) for safety models • ML engineering or applied AI research, with demonstrated ownership of production ML systems • Python and PyTorch (or JAX/TensorFlow) • Post-training LLMs with RLHF, DPO, RLAIF, or reward modeling including reward design, preference data curation, and training stability • ML deployment (ExecuTorch, Core ML, TFLite, MLC-LLM, vendor NPU toolchains) Our client is a leading Software Development Industry and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration. Pyramid Consulting, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. By applying to our jobs you agree to receive calls, AI-generated calls, text messages, or emails from Pyramid Consulting, Inc. and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here.