model-evaluation jobs in San Diego

Lead Forward Deployed Engineer responsible for architecting and delivering LLM-enabled applications (copilots, agentic workflows, assistants) using enterprise AI platforms like Claude, Gemini, or GPT-4o. Drive end-to-end RAG pipeline design, prompt engineering, evaluation frameworks, and data foundations while mentoring junior engineers and enforcing delivery standards across multi-pod engagements.…See more Require 7+ years software/data engineering experience, 1+ year hands-on GenAI/LLM production deployment, and proven ability to lead project workstreams and translate business problems into AI solutions.

Forward Deployed Engineer who embeds with clients to identify business needs and translate high-value GenAI use cases into production solutions. Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms, delivering production-quality code with strong testing, CI/CD, logging, and documentation practices.…See more Lead working sessions, prototype solutions, and mentor team members while balancing architecture decisions around quality, safety, latency, cost, and model risk. Requires 3+ years software/data engineering experience, 1+ years hands-on GenAI/LLM deployment, and 1+ years with Microsoft AI & Data (Azure AI Foundry).

Senior forward-deployed engineer at Deloitte GPS responsible for developing scalable AI engineering patterns and production-quality GenAI/LLM solutions for government clients. Must have 7+ years software/data engineering experience, 1+ years hands-on with Palantir (Foundry, AIP, or Maven), and 1+ years building and deploying LLM-powered solutions in production.…See more Role emphasizes architecture balancing quality, safety, latency, cost, and model risk; delivering well-tested, documented code with strong CI/CD practices; and translating business problems into AI solutions while leading technical workstreams.

A forward-deployed engineer who embeds with enterprise clients to identify business needs and build production-grade AI solutions using Palantir platforms (Foundry, AIP, Maven). The role combines solution engineering—developing agentic AI systems, LLM-powered workflows, and scalable patterns with strong testing and CI/CD practices—with client engagement and stakeholder alignment.…See more Requires 3+ years of software/data engineering experience, 1+ years of hands-on GenAI/LLM deployment, and 1+ years working with Palantir; involves 50% travel and mentoring of junior team members.

Design, develop, and optimize production machine learning systems including model development, inference optimization, and scalable ML infrastructure. Build end-to-end ML pipelines from training through deployment, optimize model inference for latency and cost, integrate LLM/ML models into APIs and microservices, and engineer data pipelines for preprocessing and validation.…See more Requires strong software engineering fundamentals with deep ML expertise, proficiency in Python and systems languages, and experience with ML frameworks, model serving, and distributed computing.

Develop scalable AI engineering patterns and production-quality code for government clients, balancing quality, safety, latency, cost, and model risk. Apply strong practices in testing, CI/CD, logging, versioning, and documentation while designing extensible functionality aligned with senior team members.…See more Requires 4+ years of software/data engineering experience, 1+ year building and deploying GenAI or LLM solutions, and 1+ year with Google Cloud (Gemini API, Vertex AI Agent Builder, Grounding, or Google Workspace integration). Lead project workstreams, translate business problems into AI solutions, and contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.

Senior Machine Learning Engineer to design and ship production voice and conversational AI agents within AppFolio's Realm-X platform. You will architect real-time, multi-turn agent pipelines that balance reasoning depth against latency, lead a small pod of ML and platform engineers, and define quality metrics and evaluation harnesses.…See more Required expertise includes shipped production experience with agent frameworks (LangChain, LangGraph), voice stacks (STT/TTS/Voice-to-Voice models), LLM reasoning and tool use, Twilio, AWS, expert Python with async and WebSocket streaming, and demonstrated team leadership.

Build applied AI systems for Crucible, Firestorm's manufacturing operations software. You'll productionize ML and optimization models, integrate foundation models and LLMs into workflows, and design end-to-end AI capabilities—from model selection and evaluation through reliable production deployment across cloud, air-gapped, and edge environments.…See more This is a hands-on engineering role requiring 5+ years shipping production ML/AI systems, strong Python and software engineering fundamentals, and deep experience with LLMs, transformer models, and production ML monitoring.

Build, deploy, and continuously improve MITRE ATT&CK–aligned threat detections across cloud, endpoint, identity, email, and application telemetry. Own the full detection lifecycle from hypothesis and data validation through deployment, tuning, and retirement, advancing a detection-as-code platform with version control, peer review, automated testing, and CI/CD.…See more Evaluate AI-powered security capabilities including LLMs, anomaly detection, and response automation. Partner with Security Operations on investigations, incidents, and detection maintenance.

Design, build, test, and operate production ML and LLM-powered components for cybersecurity applications at scale. You will turn ambiguous requirements into working code, partner across product and security teams, and apply AI safety and guardrail practices.…See more The role requires solid software engineering fundamentals, hands-on experience building production ML/LLM applications (RAG, embeddings, agents), and the ability to take prototypes to reliable, maintainable systems. You'll work with distributed systems, cloud-native technologies, and graph/data plumbing while contributing to code reviews and raising team quality standards.

The AI Engineer designs, builds, and operates production-grade AI solutions in Azure Government (GCCH) environments, with a focus on LLM and RAG implementations. Responsibilities include testing and optimizing LLMs and model variants, benchmarking RAG systems, building MCP server integrations to connect AI agents to enterprise data, implementing agentic AI workflows using platforms like N8N and Copilot Studio, and developing modular AI microservices.…See more The role also involves supporting security practices (RBAC, Key Vault, data protection), monitoring and incident response for AI workloads, and helping BI and DevOps teams adopt AI capabilities toward production. A Bachelor's degree in Computer Science or related field and 1–2 years' experience with LLMs, RAG, or AI solution development are required.

As an AI Performance Engineer at Qualcomm, you will create and implement machine learning techniques, frameworks, and tools for efficient discovery and deployment of ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, optimize software for AI model deployment on hardware (kernels, compilers, model efficiency tools), and develop ML techniques into products.…See more You will conduct experiments to train and evaluate ML models, work independently with minimal supervision, and provide technical guidance to team members. The role requires 4+ years of hardware/software/systems engineering experience, proficiency with ML frameworks (TensorFlow, PyTorch, Keras), embedded systems optimization, and programming languages suited for ML (Python, C++, R).

Lead engineering and data science roadmap for Teradata's AI Platform, overseeing architecture, LLM integrations, RAG pipelines, vector store implementations, and data science experimentation frameworks. Partner with product, research, and engineering teams to define requirements for predictive modeling, multi-agent collaboration, and tool orchestration.…See more Manage and mentor a team of backend engineers, data scientists, and AI platform specialists while driving technical excellence, cloud-native practices, and platform scalability.

Chief AI Subject Matter Expert leading the development of intelligent data processing pipelines, NLP systems, and AI-enabled dashboards for defense applications. The role requires 15+ years of experience with generative AI, LLMs, and agent-based development workflows, including hands-on use of tools like GitHub Copilot and Claude for code generation and automation.…See more Responsibilities include prototyping emerging AI tooling, mentoring engineering teams on AI integration, designing secure production AI solutions, and identifying opportunities to accelerate the software lifecycle through AI and automation. Must demonstrate expertise in LLM APIs, RAG architectures, vector databases, prompt engineering, and AI-specific security considerations in classified/sensitive environments.

Lead a specialized team of software engineers at the intersection of hardware, software, and AI, focusing on developing innovative Pixel experiences using sensor signals. The role requires deep expertise in real-time embedded software development, sensor fusion algorithms, machine learning infrastructure optimization, and AI/ML design.…See more You will independently design and implement systems, collaborate with stakeholders on technical direction, and manage a team building power-efficient, sensor-driven features leveraging computer vision, signal processing, and estimation theory.

Engineering Lead responsible for designing, developing, and deploying production ML models for live trading environments while leading day-to-day technical execution across the engineering team. You will work with leadership to shape the research agenda, mentor engineers, drive adoption of AI tools to accelerate engineering workflows, and build/improve core ML infrastructure including data pipelines, training workflows, and inference systems.…See more The role requires 4–6 years of applied ML/AI experience with 1–2 years leading technical projects or teams, strong proficiency in Python and PyTorch, and a track record of shipping ML systems where model performance directly impacts business outcomes.

Lead a team of Databricks engineers delivering GenAI and LLM solutions to government clients. You'll architect and deploy production-scale data platforms, mentor engineers, and translate business requirements into AI solutions using Databricks' full stack (Lakehouse, Agent Bricks, Model Serving, Genie, Apps).…See more Enforce strong data management, CI/CD, testing, and documentation practices while working across AWS, Azure, and Google Cloud environments.

Senior Forward Deployed Engineer at Deloitte GPS building AI-enabled solutions and agentic platforms on Databricks for enterprise government clients. Requires 7+ years software/data engineering experience, 5+ years deploying GenAI/LLM solutions in production, and 5+ years hands-on Databricks expertise across Lakehouse, Agent Bricks, Model Serving, and Genie.…See more Mentors junior engineers, designs scalable AI patterns with human-in-the-loop controls, delivers production-quality code with strong CI/CD and testing practices, and translates complex business problems into deployable AI solutions.

Lead machine learning strategy and development for AppFolio's Leasing products, owning the ML roadmap and autonomous leasing agent architecture. Build evaluation frameworks, model quality infrastructure, and establish ML standards across the Leasing Engineering team while ensuring production-grade reliability, SLOs, and observability.…See more Translate research into shipped features by evaluating fine-tuning approaches, RAG patterns, and agentic systems; operate with production discipline on a SaaS platform serving real customer workflows.

Lead ML research and production model development for a quantitative trading firm, working hands-on to design, train, and deploy ML systems that directly impact live trading environments. You will drive technical execution across the engineering team, mentor engineers to raise the bar, and translate ambiguous research problems into executable modeling work with measurable real-world impact.…See more The role requires 4–6 years of applied ML experience with 1–2 years of technical leadership, strong fluency in Python and PyTorch, and a track record of shipping production systems in high-stakes contexts.

Lead the design, development, and operation of Qualcomm's enterprise AI platform, supporting agentic AI, model lifecycle management, and multi-cloud ML/inference infrastructure. Own core platform services including identity/RBAC, secrets, service meshes, observability, vector stores, and model gateways across on-prem GPU clusters and managed cloud services.…See more Manage a ~10-engineer global team (platform, SRE, MLOps/LLMOps), drive incident response and continuous improvement, and partner with product and security teams on AI governance and high-impact use cases.

Staff Analytics Engineer responsible for designing and operationalizing agentic AI workflows, ML models, and Databricks applications at scale. Will build multi-step agent pipelines combining rules, ML models, and reasoning to solve complex business problems, then productionize them with monitoring, drift detection, and retraining strategies.…See more Requires 5+ years of hands-on ML engineering or data science with production system ownership, deep Python proficiency, strong traditional ML foundations, and proven Databricks expertise including notebook apps, dashboards, and ML pipelines. Will serve as technical authority, mentor peers, and influence architectural decisions across teams.

Senior engineer at Deloitte GPS delivering production-quality code for GenAI/LLM-powered solutions, with 7+ years in software/data engineering and 1+ years hands-on experience building and deploying Claude-based applications. Responsibilities include designing extensible functionality, leading project workstreams, translating business problems into AI solutions, and contributing reusable assets (code, prompt libraries, runbooks).…See more Strong emphasis on testing, CI/CD, logging, documentation, and mentoring junior team members in fast-paced, ambiguous client delivery environments.

Google seeks a Software Engineer III to develop computer vision and computational photography features for Pixel camera autofocus, exposure, and white balance systems. You will own the end-to-end product lifecycle from research and algorithm development through prototyping, optimization, and commercialization.…See more The role requires proficiency in C++, machine learning infrastructure (model deployment, optimization, data processing), and computer vision or imaging platforms, along with experience in large-scale system design and performance analysis.

Lead a Palantir Forward Deployed Engineering team for the Government & Public Services practice, guiding architecture of data pipelines powering GenAI use cases. You will contribute production-quality code, enforce strong data management and CI/CD practices, and translate business problems into AI solutions while working with federal/state/local government clients.…See more The role requires 10+ years of software/data engineering experience, 1+ years of hands-on GenAI/LLM deployment, and 1+ years working with Palantir (Foundry, AIP, or Maven), with deep familiarity in AWS, Azure, and/or Google Cloud environments.