time-series jobs in San Diego

Design and implement embedded control and management software for Software-Defined Radio (SDR) wireless mesh systems, optimizing low-level radio control logic and real-time operational analytics. Build high-performance APIs, telemetry pipelines, and edge analytics to process network KPIs (RSSI, SINR, packet error rates, latency, spectral efficiency) while managing embedded databases and enforcing zero-trust encryption.…See more Mentor team members and collaborate with hardware/RF engineers to translate system requirements into reliable, documented software. Requires 7+ years of C++, DSP, SDR architecture, multi-core processor, and Linux expertise, plus experience with time-series databases and telemetry frameworks.

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.

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.

Research Programmer III will develop machine learning and computational methods to understand behavior and neural activity in the Kennedy Lab at Scripps Research. The role involves building and training deep neural networks for supervised, unsupervised, and reinforcement learning problems, applying computer vision for high-throughput animal phenotyping, and contributing to scientific papers.…See more Candidates must have 4+ years of software development experience in Python with demonstrated expertise in deep learning, version control (git/GitHub), and software engineering principles. The position offers opportunities to lead independent research projects on datasets from collaborating institutions and is ideal for those building toward graduate studies in computational neuroscience or machine learning.

Performance Engineer II will evaluate and optimize utility-scale solar PV system performance using modeling software like PVsyst, analyze equipment failures and underperformance, and create project-specific troubleshooting templates. The role requires 4+ years of PV performance engineering or data analytics experience, proficiency in Excel and programming languages (Python, VBA, MATLAB, Java), and the ability to mentor junior engineers while maintaining strong client relationships and project ownership.See more

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.

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.