feature-engineering 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.

As an AI and Data Science Engineer III, you will translate business goals into machine learning use cases and develop predictive models for marketing and advertising applications. You'll perform exploratory data analysis, apply clustering and feature transformation techniques, build proofs of concept, and validate solutions.…See more The role requires 5+ years of industry experience applying data science or machine learning methods, with a strong foundation in translating business requirements into model design approaches and collaborating across analytics and data engineering teams.

Join XiFin's Advanced Data Analytics team as an Associate Machine Learning Engineer to design, develop, and deploy machine learning models with a focus on LLMs, Generative AI, and Agentic AI in healthcare and revenue cycle domains. You will contribute to MLOps pipelines, perform data preparation and prompt engineering, collaborate with cross-functional teams, and validate models for production use.…See more The role requires a Bachelor's degree in Computer Science, Data Science, or related field, with proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch), and foundational knowledge of GenAI architectures, vector databases, and LLM orchestration frameworks.

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.

Senior AI/ML Engineer responsible for shipping end-to-end production ML systems that enable autonomous medical coding in a SaaS platform. Will design robust ML architectures with low-latency inference, build reliable data and model pipelines using modern MLOps practices (CI/CD, model registries, experiment tracking), establish evaluation strategies with statistical rigor, and implement model observability and governance including drift detection and bias assessments.…See more Requires 5+ years of industry experience building and operating ML systems in production, 3+ years with C# or Python, 3+ years on Azure, and 1+ years of LLMOps expertise including prompt engineering and RAG.

Design, develop, and optimize machine learning systems for production AI platforms, focusing on model development, inference optimization, and scalable ML infrastructure. Responsibilities include building ML pipelines and frameworks, optimizing model inference for latency and cost, integrating LLMs into APIs and microservices, and designing data pipelines for preprocessing and feature engineering.…See more The role requires strong software engineering fundamentals combined with deep ML expertise, working across PyTorch/TensorFlow, model-serving systems, distributed computing, and GPU environments.

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.

Build and ship production ML systems end-to-end for autonomous medical coding in a SaaS platform, from problem framing through deployment and monitoring. Own the full lifecycle—data discovery, feature engineering, training, evaluation, and iteration—working with LLMs, deep learning, and modern MLOps tooling to handle millions of medical charts daily.…See more Design robust, low-latency architectures, establish rigorous evaluation strategies, and implement model observability, drift detection, and bias assessments. Collaborate across product, data, and platform teams to translate business goals into measurable ML outcomes.

Senior Data Engineer at Sony to design, build, and maintain scalable data pipelines, dashboards, and reporting solutions supporting PlayStation's payments, subscription, and fraud-prevention systems. Will develop AI-ready data products for analytics, automation, and machine-learning workflows in close partnership with data scientists, analysts, and global payments stakeholders.…See more Requires 7+ years in data engineering or related software/systems work, strong SQL and data modeling, proficiency in Python/Java/scripting languages, and experience operationalizing data for ML and governance. Will mentor team members, communicate technical architectures to executives, and drive platform reliability and security.

A forward-deployed engineer who builds and deploys AI/GenAI-powered solutions on Databricks and cloud platforms for forensic discovery and financial crime clients. The role requires hands-on expertise in Databricks, cloud services (AWS/Azure/GCP), and production AI/LLM systems, combined with the ability to lead client engagements, translate business requirements into technical architectures, and troubleshoot integration issues across enterprise environments.…See more You will design reusable assets, document workflows, and enable client teams to sustain delivered solutions while navigating security, compliance, and privacy reviews.

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.

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, and operate enterprise-scale Databricks lakehouse platforms for a global semiconductor company. Lead AI-native development practices, machine learning enablement, and AIOps automation while mentoring engineering teams and establishing technical standards.…See more Drive platform modernization, cloud-native practices, and intelligent data/AI infrastructure at scale. Requires 4–5 years of hands-on Databricks experience, strong Python/SQL/Spark skills, MLOps expertise, and proven technical leadership.

Lead the design, build, and operation of enterprise-scale Databricks Lakehouse platforms at Qualcomm, driving AI-native development, MLOps practices, and cloud modernization. This hands-on Staff IT Engineer role requires 4–5 years of Databricks experience and 8–12 years total IT background, with responsibility for platform architecture (Delta Lake, Unity Catalog, Workflows), machine learning enablement (MLflow, Mosaic AI), AIOps automation, and technical mentoring of engineers.…See more You will establish engineering standards, optimize platform performance and cost, implement observability and self-healing automation, and drive adoption of generative AI tools and intelligent automation across development teams.

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.

Design and improve autonomous AI trading systems deployed in financial markets, with core work on model architectures, training frameworks, and performance evaluation. You'll integrate novel data sources, optimize models for measurable accuracy gains and reduced training time, and build monitoring systems to detect anomalies in live trading strategies.…See more Requires strong ML fundamentals with hands-on experience in PyTorch, TensorFlow, or JAX, feature engineering, and model optimization; minimum 2 years of ML development experience preferred.

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and customer experiences. Responsibilities include implementing end-to-end AI/ML pipelines using AWS services (SageMaker, Lambda, ECS/EKS), feature engineering with Snowflake, model fine-tuning and testing, and monitoring production performance.…See more The role requires 3+ years of AI/ML experience with 1–2 years in generative AI or LLMs, hands-on cloud deployment experience, and proficiency in Python, PyTorch, TensorFlow, or Hugging Face Transformers.

Deloitte seeks a Forward Deployed Engineer to design, build, and deploy AI-enabled solutions and agentic platforms for government clients using Palantir technologies. The role requires hands-on experience building and operating GenAI/LLM-powered systems in production, contributing production-quality code with strong testing and CI/CD practices, and leading project workstreams to translate business problems into scalable AI solutions.…See more The engineer will prototype and deliver working solutions independently within a pod structure while mentoring teammates, balancing quality, safety, latency, cost, and model risk in architecture decisions.

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.

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.

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.