Putra Wibisono
III. Work Experience

Engineering, Research & Operations.

Chronological overview of my work in electric-vehicle battery manufacturing, data engineering, computational drug discovery, and materials research, alongside my current role in Business Operations & Strategy at our family-owned enterprise.

Roles (2020 – Present) Open Printable CV →

Roles & Key Contributions

2020 – Present
Current

Family-Owned Enterprise

Indonesia

Current Role

Business Operations & Strategy

Operations · Strategic Planning · Agriculture

Supporting day-to-day business operations, partner coordination, and strategic initiatives at my family's agricultural enterprise.

  • Operations & Coordination: Assist with operational management, commercial coordination, and strategic planning across my family's agricultural business.
  • Field Trial Evaluation: Support field demonstration plot trials to evaluate organic fertilizer strategies and track crop productivity.
  • Data & Reporting Exploration: Explore practical approaches for baseline soil and satellite analysis as well as clear reporting for business and institutional partners.

Methods & Tools: Business Operations · Strategic Planning · Field Trial Analysis · Python & SQL

May 2023 – Dec 2024

Tesla, Inc.

Fremont, CA (Supporting Berlin & Austin Gigafactories)

Data Engineering

Sr. Data Engineer (P3): Apr 2024 – Dec 2024 · Data Engineer (P2): May 2023 – Apr 2024

Sr. Data Engineer (P3) & Data Engineer (P2)

EV Battery Manufacturing · 4680 Cell & Factory Telemetry

Built battery formation screening libraries (FAST), real-time multi-gigafactory telemetry dashboards (RAPID), Generation 4/5 battery simulation models, and 4680 cell API recipe synchronization workflows.

  • FAST Screening Library (P3): Developed the FAST (Formation Analytics Screening Toolbox) library used by data scientists to evaluate new development recipes during battery formation and reach deterministic pass/fail trial conclusions.
  • RAPID Live Factory Dashboard (P3): Developed and maintained the RAPID internal dashboard for Berlin and Austin Gigafactory sites, enabling process engineers to inspect real-time telemetry and make live production-line adjustments.
  • EoL Defect Detection & Vendor Scoring (P3): Developed automated early defect detection during End of Line (EoL) testing and established vendor scoring parameters for business analytics teams.
  • Milmont AWS Streams, Gen 4/5 ML Models & 4680 API Sync (P2): Implemented temperature, pH, and electrical current data streams for the Milmont facility into AWS; developed proprietary Generation 4 & 5 ML models simulating Model Y and Model 3 batteries across vendors; and engineered API call-and-sync recipe systems supporting 4680 battery cell development.

Methods & Tools: Python · SQL · AWS · FAST Toolbox · RAPID Dashboard · Gen 4/5 ML Simulation · REST APIs

Sep 2022 – May 2023

ATOM Science

San Francisco, CA

Data Science

Data Science Intern

Computational Drug Discovery · Molecular Machine Learning

Curated drug discovery datasets and trained transfer-learning and active-learning models in Python to screen molecular candidates for wet-lab testing.

  • Molecular Property Prediction: Used Python to curate drug discovery datasets and build machine learning models to predict molecular properties.
  • Transfer & Active Learning: Applied transfer learning and active learning techniques to make effective use of sparse chemical datasets.
  • Wet-Lab Candidate Screening: Screened large databases of molecules to identify promising candidates to advance into wet-lab testing.

Methods & Tools: Python · TensorFlow · Keras · NumPy · Pandas · Transfer Learning · Active Learning

Sep 2021 – Sep 2022

Rivian

Irvine, CA

Process Development

Process Development Engineer, Formation

EV Battery Cell Formation · SEI Diagnostics

Developed proprietary battery cell formation recipes for R1S, R2, and R3 vehicle programs and predictive Solid Electrolyte Interphase (SEI) anomaly detection protocols.

  • R1S, R2 & R3 Formation Recipes: Developed proprietary formation recipes for R1S, R2, and R3 models with improved charging compatibility on Tesla’s Supercharger network.
  • Predictive SEI Anomaly Detection: Developed diagnostic protocols to detect Solid Electrolyte Interphase (SEI) formation anomalies during precharge steps.
  • Production & Development Recipe Standardization: Deployed 6 recipes (4 development recipes and 2 production recipes) that served as the standard baseline from December 2021 to December 2022.

Methods & Tools: Battery Cell Formation · SEI Precharge Diagnostics · Electrochemical Testing · Python / MATLAB

Sep 2020 – Jun 2021

UC San Diego — Department of Nanoengineering

San Diego, CA

Academic Research

Research Assistant — Battery Engineering

Electrochemical Energy Storage & Materials Characterization

Conducted coin-cell assembly, cathode active material synthesis, materials characterization (XRD, FTIR, NMR), and battery cell recycling research.

  • Coin-Cell Assembly & Cycling: Assembled coin cells in argon glove boxes and ran electrochemical testing on automated battery cyclers.
  • Cathode Synthesis & Characterization: Synthesized cathode active materials and performed physical characterization using XRD, FTIR, NMR, vacuum ovens, and ROTAP shakers.
  • Direct Recycling Teardown: Harvested and tore down spent cells (cathode, separator, and electrolytes) for battery recycling studies and authored experiment reports.

Methods & Tools: Coin Cell Assembly · Battery Cyclers · XRD · FTIR · NMR · Glove Box Operations · ROTAP Shaker

Graduation University Degree & Concentration
June 2023 University of California, Berkeley
Berkeley, CA
Master of Engineering (M.Eng.) in Materials Science and Engineering
Concentration in Data Science · Major GPA: 3.92
June 2021 University of California, San Diego
San Diego, CA
Bachelor of Science (B.S.) in Chemical Engineering
Minor in Computer Science