Battery Algorithm Engineer

Battery Algorithm

Key Responsibilities

 

Platform & Data Engineering

Own the end‑to‑end data architecture: ingestion from BMS/SCADA/EMS, time‑series storage, feature store, model serving, and secure APIs.

Establish telemetry pipelines with strong data quality, lineage, observability, and SLA adherence.

 

Analytics & Modeling (Usage & Performance Correlation)

Translate usage signals (Current/C‑rate, SoC, temperature/thermal profiles, cycle vs calendar aging) into performance metrics (SOH, capacity fade, impedance growth, efficiency, safety risk). Build predictive models for RUL, anomaly/failure detection, state estimation (SOC/SOH/SOx); quantify uncertainty and provide explainability. Apply Bayesian optimization and multivariate prognostics for early cycle‑life prediction and parameter tuning.

 

Battery User Experience

Develop on‑device models and energy accounting for SW features; architect end‑to‑end solutions to improve perceived battery life, charging and thermal performance. Build user‑facing systems and interfaces that educate users/operators and guide behavior for healthier usage patterns.

Products, Dashboards & Decisioning

Deliver operator dashboards with actionable KPIs: performance & availability, safety alerts, degradation indicators, dispatch optimization signals.

Partner with EMS/controls on algorithmic hooks for energy arbitrage, peak shifting, compliance, and event analytics.

 

Reliability, MLOps & Delivery

Own MLOps: experiment tracking, CI/CD for models, monitoring (drift/latency), rollback/OTA updates; drive “model‑in‑production” culture. 

Lead QA and site integration for new releases; validate against field data and simulation before rollout. 

 

Bachelor’s/master’s in computer science/P.hD. , Data Science, Electrical/Power/Electrochemistry, or related field.

Experience Level

Senior Level