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Battery Machine Learning Jobs in Texas (NOW HIRING)

MVST), a technology innovator that designs, develops and manufactures lithium-ion battery solutions ... Hands-on experience with machine learning frameworks is a plus. * Familiarity with cloud computing ...

Manage the development of statistic based on big data and machine learning models for predicting and forecasting field failure, cell chemistry variations, battery health degradation, and how various ...

Senior Analyst, Asset Performance

Austin, TX · On-site

$87K - $115K/yr

... solar, and battery storage), including visualizations, data blending, and data validations ... machine learning models, OEM software, data modeling and performance analysis (input variable ...

... battery-powered appliances, network infrastructure, healthcare and aerospace/defense. Visit www ... Experience in automated defect classification and/or machine learning for visual defect binning ...

Nice to have: experience deploying machine learning models to production, deep fluency in Python ... our distributed battery fleet into revenue. That means building and defending the models that ...

Quantitative Developer Intern

Austin, TX · On-site

$19 - $25/hr

Proficiency in statistics, machine learning, and data-driven decision-making. * Strong software ... battery fleet. This encompasses device communications with balancing authorities, telemetry ...

Showing results 21-40

Battery Machine Learning information

What are the key skills and qualifications needed to thrive as a battery machine learning engineer?

To thrive as a Battery Machine Learning Engineer, you need a strong background in machine learning, data analysis, and battery science, typically supported by a degree in engineering, computer science, or a related field. Familiarity with Python, TensorFlow or PyTorch, data processing tools, and battery management system (BMS) software is highly valued. Strong problem-solving skills, collaboration, and effective communication set standout professionals apart in this role. These skills are essential to develop accurate predictive models that optimize battery performance and longevity, driving innovation in energy storage technologies.

What is battery machine learning?

Battery machine learning involves the application of machine learning algorithms to analyze, predict, and optimize the performance, lifespan, and safety of batteries. Professionals in this field work on developing data-driven models to forecast battery degradation, enhance energy management systems, and improve battery design. Their work is crucial in sectors such as electric vehicles, renewable energy storage, and consumer electronics, where battery efficiency and reliability are key. By leveraging large datasets from battery usage and testing, they help accelerate innovation and reduce costs in battery technology.

What are some common challenges faced by professionals working in battery machine learning roles?

Professionals in Battery Machine Learning often encounter challenges related to limited or noisy datasets, as battery performance data can be expensive and time-consuming to collect. Additionally, integrating domain knowledge from electrochemistry with advanced machine learning techniques requires strong interdisciplinary collaboration. Staying up-to-date with both the latest AI methods and battery technology advancements is essential but can be demanding. Collaborating closely with researchers, engineers, and data scientists is a key aspect of the role, as projects frequently depend on cross-functional teamwork to translate predictive insights into practical battery innovations.
What are popular job titles related to Battery Machine Learning jobs in Texas? For Battery Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Battery Machine Learning jobs in Texas look for? The top searched job categories for Battery Machine Learning jobs in Texas are:
What cities in Texas are hiring for Battery Machine Learning jobs? Cities in Texas with the most Battery Machine Learning job openings:
Infographic showing various Battery Machine Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

BMS Data Analysis Engineer

MICROVAST INC

Houston, TX • On-site

Full-time

Re-posted 6 days ago


Job description

BMS Data Analysis Engineer

Are you ready to be part of a company that's not just talking about the future, but energetically shaping it? Join the Microvast Team (NASDAQ: MVST), a technology innovator that designs, develops and manufactures lithium-ion battery solutions. Founded in 2006 and headquartered in Houston, TX, Microvast is renowned for its cutting-edge cell technology and its vertical integration capabilities which extend from core battery chemistry (cathode, anode, electrolyte, and separator) to battery packs. By integrating the process from raw material to system assembly, Microvast has developed a family of products covering a broad breadth of market applications. More information can be found on the corporate website: www.microvast.com

If you’re ready to be part of a company that’s not just adapting to change, but driving it, Microvast is the place for you. Apply now and electrify your career with a true leader in the global energy transformation.

Job Summary

Microvast is seeking a highly skilled BMS Data Analysis Engineer to join our team. This role involves designing, developing, and optimizing advanced algorithms to solve complex problems in battery system. The ideal candidate should have strong analytical skills, a deep understanding of algorithm design, and experience in implementing scalable solutions.

The position is 5 days in office, located at our headquarters in Houston, TX.

Key Responsibilities

  • Collect, clean, and organize data from battery testing (cell/module/pack), BMS logs and field operating data.
  • Develop and maintain scalable data pipelines and dashboards for continuous monitoring.
  • Ensure data quality, traceability, and consistency across various sources.
  • Perform statistical analysis and trend evaluation to identify anomalies, degradation patterns, and performance deviations.
  • Collaborate with system engineers and test engineers to define data requirements for validation and verification.
  • Conduct root-cause analysis of battery failures, safety events, and performance issues based on battery data.
  • Provide data-driven recommendations to optimize test plans, test coverage, and acceptance criteria.
  • Document findings, methodology, and tools in a structured and reproducible way.
  • Work with BMS developers to validate algorithms and improve control strategies.
  • Support field service, warranty, and quality teams with in-depth data analysis.
  • Participate in continuous improvement initiatives for battery lifecycle management.

Qualifications & Skills

Required

  • Master’s or PhD in Computer Science, Mathematics, Engineering, or a related field.
  • 2–5 years of experience in data analysis, preferably in battery systems, energy storage, or electric vehicles.
  • Strong proficiency in Python, SQL, and common data science libraries (numpy, pandas, scipy, scikit-learn).
  • Hands-on experience with data visualization tools (e.g., Power BI, Tableau, matplotlib, Plotly).
  • Good understanding of lithium-ion battery behavior, including SoC/SoH calculation, degradation, thermal behavior, and charging/discharging characteristics.
  • Proficiency in programming languages such as Python, C++, or similar.
  • Solid understanding of mathematical and statistical modeling techniques.
  • Experience with large-scale data processing and optimization techniques.
  • Ability to work collaboratively in a team environment and communicate technical concepts effectively.
  • Strong problem-solving skills and the ability to think critically under challenging scenarios.
  • Creative thinking skills & Strong analytical skills
  • Ability to communicate well with other members of the development team

Preferred Qualifications:

  • Hands-on experience with machine learning frameworks is a plus.
  • Familiarity with cloud computing and distributed computing frameworks

Annual salary + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

Applicants for employment at Microvast must be a U.S. citizen or national, U.S. permanent resident (i.e. current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Microvast is an Equal Opportunity Employer who is committed to building strength and delivering long-term sustainability through diversity and inclusion. Respecting all backgrounds, differences and perspectives enables us to improve the lives of our people, customers, suppliers, contractors, and the communities in which we live and work. All qualified applicants will receive consideration for employment without regard to sex, sexual orientation, gender, gender identity and/or expression, race, national origin, ethnicity, age, religion, marital status, physical or mental disability, pregnancy, childbirth, or related medical condition, military or veteran status, or any other characteristic protected under applicable law.