Revolution Technologies
Artificial Intelligence Engineer (Behavox Communications Surveillance)
Revolution Technologies, San Jose, California, United States, 95199
Artificial Intelligence Engineer (Behavox Communications Surveillance)
Location:
Hybrid – San Jose, CA
Contract:
3-Month Contract to Start (extensions possible)
Overview We are seeking a highly specialized AI/ML Engineer with deep experience in Behavox Communications Surveillance, large language models (LLMs), and capital markets environments. This role is critical in advancing model performance, enabling compliant communications surveillance, and supporting key initiatives within a leading financial technology program.
The ideal candidate will have
direct, recent hands‑on experience (within the last 3–4 years)
implementing or configuring Behavox surveillance systems, combined with strong LLM development and optimization skills, and experience supporting capital markets, trading, or regulatory technology use cases.
Key Responsibilities LLM Development & Optimization
Design, train, fine‑tune, and evaluate LLMs for performance, efficiency, interpretability, and alignment.
Apply advanced optimization techniques such as quantization, distillation, caching strategies, and parameter‑efficient fine‑tuning (PEFT).
Run structured experiments to identify weaknesses, improve accuracy, and reduce latency in model outputs.
Systems Integration & Deployment
Implement scalable inference pipelines to support production‑grade model serving.
Integrate LLM‑based capabilities into applications, APIs, and surveillance workflows.
Ensure model deployments adhere to compliance, security, and audit requirements, particularly in regulated financial environments.
Support or lead configuration, tuning, and deployment of Behavox Communications Surveillance systems.
Integrate Behavox data feeds, behavioral signals, and alerting workflows into model development pipelines.
Collaborate with compliance and surveillance teams to validate detection logic and enhance accuracy.
Research & Cross‑Functional Collaboration
Drive experimentation with new model architectures, retrieval‑augmented generation (RAG), and prompt‑engineering techniques.
Work closely with product, data engineering, MLOps, and compliance teams to translate research into production capabilities.
Produce clear technical documentation, experiment results, and model evaluation reports.
Required Qualifications
Hands‑on experience implementing and configuring Behavox Communications Surveillance , including tuning alerts, ingestion pipelines, and detection workflows (must be within the last 3–4 years).
Recent, strong experience in AI/LLM development , including training, fine‑tuning, or optimizing large‑scale models.
Capital markets experience , ideally within trading, market surveillance, compliance, risk, or regulatory technology.
Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX, etc.).
Experience deploying models into production environments with performance, reliability, and compliance considerations.
Strong understanding of communications surveillance, market abuse detection, and financial regulatory requirements.
Preferred Qualifications
Experience with reinforcement learning (RLHF, RLAIF) and prompt engineering.
Exposure to RAG frameworks and vector database technologies. \ Familiarity with MLOps (Docker, Kubernetes, MLflow, distributed training).
Experience working directly with compliance teams or within regulated financial institutions.
Additional Information
3‑month contract to start; extensions possible based on project needs.
Hybrid schedule with required onsite presence in
San Jose, CA .
W2 engagement through our staffing organization.
#J-18808-Ljbffr
Hybrid – San Jose, CA
Contract:
3-Month Contract to Start (extensions possible)
Overview We are seeking a highly specialized AI/ML Engineer with deep experience in Behavox Communications Surveillance, large language models (LLMs), and capital markets environments. This role is critical in advancing model performance, enabling compliant communications surveillance, and supporting key initiatives within a leading financial technology program.
The ideal candidate will have
direct, recent hands‑on experience (within the last 3–4 years)
implementing or configuring Behavox surveillance systems, combined with strong LLM development and optimization skills, and experience supporting capital markets, trading, or regulatory technology use cases.
Key Responsibilities LLM Development & Optimization
Design, train, fine‑tune, and evaluate LLMs for performance, efficiency, interpretability, and alignment.
Apply advanced optimization techniques such as quantization, distillation, caching strategies, and parameter‑efficient fine‑tuning (PEFT).
Run structured experiments to identify weaknesses, improve accuracy, and reduce latency in model outputs.
Systems Integration & Deployment
Implement scalable inference pipelines to support production‑grade model serving.
Integrate LLM‑based capabilities into applications, APIs, and surveillance workflows.
Ensure model deployments adhere to compliance, security, and audit requirements, particularly in regulated financial environments.
Support or lead configuration, tuning, and deployment of Behavox Communications Surveillance systems.
Integrate Behavox data feeds, behavioral signals, and alerting workflows into model development pipelines.
Collaborate with compliance and surveillance teams to validate detection logic and enhance accuracy.
Research & Cross‑Functional Collaboration
Drive experimentation with new model architectures, retrieval‑augmented generation (RAG), and prompt‑engineering techniques.
Work closely with product, data engineering, MLOps, and compliance teams to translate research into production capabilities.
Produce clear technical documentation, experiment results, and model evaluation reports.
Required Qualifications
Hands‑on experience implementing and configuring Behavox Communications Surveillance , including tuning alerts, ingestion pipelines, and detection workflows (must be within the last 3–4 years).
Recent, strong experience in AI/LLM development , including training, fine‑tuning, or optimizing large‑scale models.
Capital markets experience , ideally within trading, market surveillance, compliance, risk, or regulatory technology.
Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX, etc.).
Experience deploying models into production environments with performance, reliability, and compliance considerations.
Strong understanding of communications surveillance, market abuse detection, and financial regulatory requirements.
Preferred Qualifications
Experience with reinforcement learning (RLHF, RLAIF) and prompt engineering.
Exposure to RAG frameworks and vector database technologies. \ Familiarity with MLOps (Docker, Kubernetes, MLflow, distributed training).
Experience working directly with compliance teams or within regulated financial institutions.
Additional Information
3‑month contract to start; extensions possible based on project needs.
Hybrid schedule with required onsite presence in
San Jose, CA .
W2 engagement through our staffing organization.
#J-18808-Ljbffr