mlflow jobs in San Diego

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.

Senior AI Engineer role focused on designing and leading scalable, high-performance data architecture solutions that support AI/GenAI use cases. The role involves building and optimizing data pipelines, defining database schemas (Graph, SQL, NoSQL), and leading infrastructure for AI model deployment across cloud and on-premises environments.…See more Requires 4+ years in data engineering/MLOps with hands-on AWS/Azure/GCP experience, 2+ years managing technical teams, and expertise in DevOps, CI/CD, containerization (Kubernetes, Docker), and ML deployment frameworks. The position includes mentoring junior engineers and driving technology modernization initiatives.

Senior technical leader responsible for integrating AI/ML systems into secure, scalable DoD-compliant environments. Will architect AI system deployments, establish DevSecOps practices, ensure compliance with RMF/NIST 800-53/DISA STIG standards, and provide technical guidance across engineering teams.…See more Requires deep expertise in AI/ML production systems, containerization, CI/CD, and cybersecurity controls, with hands-on experience in Python, Kubernetes, and modern infrastructure tooling.

Staff Engineer responsible for designing and building scalable test automation frameworks and CI/CD infrastructure for machine-learning systems at scale. The role requires expertise validating ML quality across the full lifecycle (data, training, evaluation, packaging, deployment, monitoring), GPU-accelerated workloads in Kubernetes, and integrated hardware-software systems.…See more You will develop automated evaluation suites, performance baselines, release thresholds, and observability solutions while mentoring teams on ML testing best practices and dependency/reproducibility standards.

Staff Engineer responsible for designing and implementing scalable test automation frameworks and infrastructure for machine learning systems across multiple engineering teams. The role requires expertise in validating ML pipelines across data, training, evaluation, deployment, and monitoring; testing GPU-accelerated workloads in Kubernetes; qualifying integrated hardware and software systems; and developing comprehensive integration and regression strategies.…See more Deep experience with Python automation, distributed systems testing, performance profiling, and observability is essential, along with strong system-design skills for complex, multi-tenant environments.

Lead large-scale enterprise data transformation programs at Qualcomm, managing multi-year initiatives across data modernization, cloud migration, and analytics platforms. Coordinate work across distributed data engineering, architecture, governance, security, and analytics teams while managing multi-million-dollar budgets and vendor relationships.…See more Drive adoption of modern data architectures (data lakehouse, data mesh, medallion patterns) and cloud platforms (Databricks, AWS, Azure, GCP), and establish federated data governance frameworks. Influence executives and technical stakeholders to deliver measurable business outcomes while handling legacy system retirement and enterprise data integration from CRM, ERP, HCM, and supply-chain systems.

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.

Build and deploy production-grade AI models that power Petco's e-commerce platform, including personalized recommendations, demand forecasting, and price optimization. Design and maintain robust MLOps pipelines for automated model retraining, monitoring, and 24/7 reliability across web and mobile.…See more Partner with Software Engineering and Mobile teams to integrate AI features into production systems, and mentor junior engineers on ML engineering best practices. Experiment with emerging technologies like Generative AI and LLMs to drive business impact.

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, build, and maintain secure enterprise data platforms supporting AI/ML workloads, with responsibility for database optimization, CI/CD automation, and DoD compliance. Mentor junior engineers and provide technical leadership on architecture decisions.…See more Implement security controls aligned with NIST 800-53, RMF, and DISA STIG standards throughout the platform lifecycle. Develop ETL/ELT pipelines, support data lakes and lakehouses, and evaluate emerging data technologies for mission fit.

Principal-level individual contributor role leading AI/ML architecture and engineering strategy at scale. Requires 13+ years across ML, data engineering, and distributed systems, with 3+ years shipping production Generative/Agentic AI systems.…See more Hands-on expertise in RAG, vector databases, LLM optimization, agentic orchestration, and MLOps/LLMOps practice. Will set technical direction, own architecture decisions, drive platform initiatives, and raise engineering standards across the organization without direct people-management responsibility.

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.

AI Architect role requires designing and delivering enterprise-scale AI/ML solutions on AWS, with 5–7 years of cloud experience and 2–3 years hands-on with LLMs, agentic frameworks, and AI/ML services. The position demands deep expertise in AWS AI services (Bedrock, SageMaker, Kendra), orchestration frameworks (LangChain, LangGraph), RAG pipelines, MLOps tooling, and responsible AI principles.…See more Candidates must architect scalable, cost-optimized solutions integrating AI with cloud infrastructure, data platforms, and microservices, and communicate complex technical concepts to executive and technical audiences.

Design and build scalable, distributed data platform systems on AWS and Databricks, owning workspace architecture, governance, and lifecycle management. Implement infrastructure as code with Terraform, develop end-to-end data pipelines from ingestion to analytics and ML, and operate Amazon EKS clusters.…See more Define SLIs/SLOs for platform reliability, lead incident response and on-call rotations, implement security and compliance controls, and mentor engineers on platform standards. This senior staff role requires 8+ years building large-scale cloud platforms, 5+ years in Data Platform/DevOps/SRE roles, expert AWS knowledge, and deep hands-on experience with Databricks Lakehouse (Unity Catalog, Delta Lake, MLflow), Terraform, CI/CD pipelines, and Python/Bash scripting.

The AI Architect II is a senior technical leadership role responsible for establishing architectural standards and patterns for AI solutions, including RAG pipelines, agentic workflows, and model serving. The role involves designing scalable AWS cloud architectures, defining MLOps practices, implementing responsible AI governance, and translating business requirements into enterprise AI and cloud strategies.…See more The position requires hands-on technical expertise to evaluate and integrate AI/ML services, lead systems design across microservices and event-driven architectures, and mentor engineering teams on cloud and AI best practices. This role drives technology decisions with real business impact while modernizing the company's platform through cloud-native and AI transformation initiatives.

Sr. Director role overseeing SIE's data and AI platform ecosystem, including data infrastructure (streaming, ingestion, warehouse), experimentation platforms, and governance tools.…See more Responsible for defining long-term vision, leading global engineering teams, and ensuring platforms process massive data volumes to deliver insights across gaming, content creation, and enterprise operations. Must drive scalability, cost efficiency, security, and operational excellence while collaborating with senior leadership to align platform strategy with business objectives. Requires proven Sr. Director-level experience and thought leadership in platform architecture, real-time data processing, and ML/AI integration.

Build and operate the data and ML infrastructure powering an AI platform for materials science, owning both sides: data pipelines that ingest and curate large-scale scientific output into training-ready formats, and model packaging, serving, monitoring, and CI/CD systems that move models safely from research to production across customer environments. You will design data ingestion and transformation workflows, implement validation and quality gates, package and version models with reproducible builds, run models through batch and online inference with safe rollout and rollback, monitor for drift and degradation, and build observability and internal tooling for engineering and science teams.…See more The role requires 6+ years shipping production software with deep expertise in data systems, ML infrastructure, containers, orchestration, and observability.

Build the foundational agentic AI layer for a materials-science platform, including multi-model provider abstraction, agent orchestration with stateful checkpoints, retrieval systems, prompt versioning, and comprehensive tracing and evaluation frameworks. You'll design agents that plan and reason over tool calls in production, implement human-in-the-loop safety gates, and ensure all LLM behavior remains auditable and cost-tracked across customers' secure environments.…See more The role demands deep production experience with agentic and LLM systems: async Python, structured outputs, memory and context management, multi-step workflow orchestration, and evaluation harnesses that catch regressions before deployment.

As a Data Developer, you will design, develop, and maintain scalable ETL/ELT pipelines and cloud-based data platforms that integrate enterprise systems and support AI/ML initiatives for the U.S. Navy.…See more You will perform data engineering tasks including cleansing, transformation, and optimization of SQL and Apache Spark workloads on AWS, while also developing predictive models and generative AI solutions using Python-based technologies. You will build interactive dashboards and visualizations in Tableau or Qlik, translating technical findings into actionable insights for stakeholders. An active Secret clearance, U.S. citizenship, and a bachelor's degree in a technical field (or 4+ years of relevant professional experience) are required.