nlp jobs in San Diego

Lead a team of AI/ML engineers building autonomous medical coding solutions that process millions of clinical charts daily. Translate emerging advances in machine learning and LLMs into production-ready systems, define engineering strategy for ML/LLM-powered products at scale, and ensure systems meet stringent requirements for accuracy, reliability, privacy, security, and explainability.…See more Partner across data science, clinical, compliance, and software engineering teams to architect scalable inference pipelines, establish evaluation frameworks, and integrate AI capabilities into SaaS products. Requires 6+ years of AI/ML engineering experience, 2+ years leading technical teams, and hands-on expertise in production ML pipelines, LLMs, RAG, and MLOps platforms.

Senior Staff Engineer leading the development of embedded AI software and runtime systems for on-device machine learning inference and training on Qualcomm hardware. Responsibilities include designing and optimizing ML/AI frameworks, compiler technologies, and runtime software for performance and power efficiency; developing agentic AI and novel ML solutions; and providing technical leadership across a multidisciplinary team.…See more Requires 6+ years of software/hardware/systems engineering experience, strong C/C++ and Python capabilities, deep embedded systems knowledge, and expertise in low-level OS-hardware interactions and ML optimization domains like NLP and multimedia.

Advanced manager and technical consultant designing and implementing enterprise-scale AI solutions spanning classical ML, generative AI, and agentic AI systems. Responsibilities include architecting AI-powered applications for business transformation (customer service, supply chain, finance, HR, operations), building RAG and autonomous agent workflows, developing ML pipelines, and establishing governance and observability frameworks.…See more Requires 8+ years in AI/ML/data science with 5+ years hands-on experience with Claude, GPT, LLMs, agentic frameworks, and RAG systems, plus deep expertise in prompt engineering, vector databases, and multi-agent architectures.

As an AI Science Intern, you will work alongside AI Scientists and Machine Learning Engineers to build, train, and evaluate machine learning and deep learning models on real-world datasets. Responsibilities include data gathering and ETL, feature engineering, model development using techniques like classification, regression, clustering, and neural networks, and designing experiments to measure impact.…See more You'll explore current AI/ML research including generative AI and LLMs, develop proofs-of-concept, and partner with cross-functional teams to translate insights into product features. The role requires strong Python and SQL skills, familiarity with core ML techniques and their mathematical foundations, and the ability to communicate findings to both technical and non-technical audiences.

Develop Python solutions for natural language processing and machine learning, including text analytics, topic modeling, embedding-based classification, and entity extraction. Build network-analysis capabilities such as knowledge graphs and GraphRAG-like systems, deploy APIs, integrate data feeds, and adapt to new technical environments with limited supervision.…See more Requires 4+ years of Python development experience, an active Secret clearance, and active Security+ certification. Experience with TypeScript front-end development and API deployment is required.

This role blends data science expertise with hands-on automation engineering to design and deploy intelligent process automation solutions across business units. You will build, train, and validate both classical ML and LLM-based models — including fine-tuning and RAG — and architect end-to-end systems connecting CRM, APIs, and AI services on AWS infrastructure.…See more Responsibilities span solution design, CI/CD implementation with Jenkins, Python development, agentic AI capabilities, and business translation, with emphasis on measurable business outcomes and compliance.

As an ML engineer at Booz Allen Hamilton, you'll design, build, and deploy production-grade AI/ML systems for Defense and Intelligence clients. You'll work across the full ML lifecycle—from model development in deep learning, computer vision, NLP, and signal processing through MLOps, containerization, and cloud deployment.…See more The role requires 2+ years of ML engineering or data science experience, proficiency with frameworks like TensorFlow and PyTorch, and the ability to obtain a Secret clearance.

As a Staff Machine Learning Engineer focused on model optimization, you will create and implement ML techniques, frameworks, and tools enabling efficient discovery and deployment of state-of-the-art ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, develop optimized inference/training software and compiler tools, and collaborate with cross-functional teams on joint hardware-software design.…See more The role requires 4+ years of hardware/software/systems engineering experience (or equivalent with advanced degree), deep expertise in ML frameworks (TensorFlow, PyTorch, Keras, Caffe), embedded systems optimization, and programming languages like Python or C++. You will work independently with minimal supervision, provide technical guidance to team members, and influence key organizational decisions through consultation with senior leadership.

The AI SW Integration Engineer will develop backend tools and services that automate test generation, improve requirements traceability, and streamline engineering workflows across teams. The role requires strong expertise in generative AI and large language models (LLMs), with hands-on experience designing and deploying agentic AI systems end-to-end.…See more You will integrate tools and databases via REST APIs, parse structured documents, and build automation solutions using Python and CI/CD pipelines. The ideal candidate brings 3–5 years of production experience developing automation or integration tools, plus familiarity with RAG, MCP, and requirements management workflows.

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).

As an LLM 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, develop optimized software for AI model deployment (kernels, compilers, model efficiency tools), and lead ML technique application into products.…See more You will work independently with minimal supervision while providing technical guidance to team members and collaborating across cross-functional teams on joint hardware-software design.

Design, create, and implement production-grade AI/ML systems for Defense and Intelligence clients. You'll architect scalable machine learning solutions handling fast-moving data, deploy models across multiple data modalities using frameworks like TensorFlow and PyTorch, and integrate solutions into mission environments.…See more The role requires 2+ years of ML engineering or data science experience, proficiency with ML frameworks and programming, and hands-on work in deep learning, computer vision, NLP, or signal processing.

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.

As a Machine Learning Engineer at Qualcomm, you will develop and optimize machine learning frameworks, tools, and algorithms for deployment across mobile, edge, automotive, and IoT products. You will collaborate with cross-functional teams to design hardware-software co-optimized solutions, build efficient inference and training systems, and create ML kernels and compiler tools.…See more The role requires proficiency in ML frameworks (TensorFlow, PyTorch, Keras), embedded systems optimization, and programming languages like Python or C++, with experience in problem domains such as NLP or multimedia.

This role combines prompt engineering expertise with AI system governance and enterprise adoption strategy. The engineer will optimize LLM performance across platforms (OpenAI, Anthropic), design and configure AI agents and chatbots with knowledge grounding, and establish prompt governance frameworks and best practices.…See more Success requires 5+ years in AI/ML systems, 2+ years of hands-on prompt engineering, and demonstrated ability to evaluate AI performance, manage knowledge systems, and guide enterprise clients through AI tool adoption and deployment.

Design, build, and operate production ML systems across the full lifecycle—from data preparation and model training through deployment, monitoring, and continuous improvement. Partner with data scientists, software engineers, and platform teams to turn research prototypes into reliable, scalable services.…See more Work across recommendation, ranking, forecasting, classification, NLP, and generative AI depending on product priorities. Balance model quality, inference latency, scalability, and operational resilience as equally important outcomes.

Senior Software Engineer at ServiceNow building enterprise-grade, AI-integrated conversational platforms and large-scale server-side systems. You'll design and implement highly interactive, performant applications; apply AI/ML concepts to enhance platform functionality; and write clean, scalable code following best practices in architecture, testing, and code review.…See more The role requires expertise in backend (Java, Spring, Hibernate, REST, SQL), frontend (JavaScript, Python), and machine learning/NLP systems including Large Language Models, with collaboration across product and engineering teams from design through delivery.

Senior AI Subject Matter Expert responsible for developing intelligent data processing and NLP pipelines, AI-enabled dashboards, and proofs-of-concept for AI use cases. The role requires 7+ years of professional experience with advanced expertise in LLM APIs, RAG architectures, agent-based development, generative AI coding tools, and secure AI deployment patterns.…See more Responsibilities include prototyping emerging AI developer tooling, mentoring engineering teams on generative AI workflows, and identifying software lifecycle areas that can be accelerated through AI and automation. The candidate must critically evaluate AI-generated code for correctness and security, understand AI-specific security risks across the full SDLC, and scope requirements for engineering solutions that meet business challenges with measurable outcomes.

Build and integrate agentic AI systems with physical laboratory automation platforms (Hamilton, Tecan, Opentrons) and LIMS infrastructure to autonomously design, run, and refine chemistry and biology experiments. Design multi-agent orchestration architectures with state management, error recovery, and tool integration; prototype agent planning strategies and memory systems; deploy containerized services on Kubernetes with GitOps and CI/CD.…See more Work hands-on with chemists, biologists, and automation engineers to transition prototypes into production lab operations that measurably accelerate the Design-Make-Test-Analyze cycle.

Develop software for the Qualcomm AI Stack SDKs (QAIRT and Genie) to enable execution of generative AI models and large language models on Snapdragon platforms. You will validate, optimize, and debug machine learning inference solutions, collaborating with cross-functional teams on feature development, performance analysis, and system reliability.…See more The role requires expertise in machine learning frameworks, embedded systems optimization, programming languages like Python or C++, and low-level OS/hardware interactions.

Lead the design and governance of Sharp HealthCare's enterprise data architecture, including data models, warehouses, and integration patterns supporting clinical, operational, and strategic analytics. Collaborate with IT, analytics teams, and business stakeholders to translate organizational needs into scalable, compliant data solutions.…See more Optimize data pipelines, define data standards, and guide implementation of data platforms while mentoring technical team members and contributing to long-term data strategy.

As an AI Software Engineer at Qualcomm, you will develop and optimize machine learning software for the Qualcomm AI Stack (QAIRT and Genie SDKs), enabling efficient execution of large language models and deep neural networks on Snapdragon platforms. You will validate and optimize performance of generative AI models, debug complex issues, and collaborate across teams to deliver robust AI solutions.…See more The role requires strong software design, programming, and debugging skills, with expertise in machine learning frameworks, embedded systems optimization, and languages like Python or C++. You will work with minimal supervision, participate in design reviews, and contribute to a culture of technical excellence.