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Battery Machine Learning Jobs in Texas (NOW HIRING)

Qorvo, Inc.

Staff Data Science Engineer

Richardson, TX · On-site

... battery-powered appliances, network infrastructure, healthcare and aerospace/defense. Visit www ... Lead the architecture and implementation of production-grade data science and machine learning ...

Apple

Hardware Systems Engineering

Austin, TX

$122.40K - $161.60K/yr

MACHINE LEARNING AND AI Within Appleʼs Artificial Intelligence and Machine Learning organization ... battery, applications processors, storage controllers, sensors silicon, display silicon and other ...

Apple

Hardware Systems Engineering

Austin, TX · On-site

$122.40K - $161.60K/yr

MACHINE LEARNING AND AI Within Appleʼs Artificial Intelligence and Machine Learning organization ... battery, applications processors, storage controllers, sensors silicon, display silicon and other ...

Apple

Hardware Systems Engineering

Austin, TX · On-site

$122.40K - $161.60K/yr

MACHINE LEARNING AND AIWithin Apple's Artificial Intelligence and Machine Learning organization ... battery, applications processors, storage controllers, sensors silicon, display silicon and other ...

Apple

Hardware Systems Engineering

Austin, TX

$122.40K - $161.60K/yr

MACHINE LEARNING AND AI Within Appleʼs Artificial Intelligence and Machine Learning organization ... battery, applications processors, storage controllers, sensors silicon, display silicon and other ...

MICROVAST INC

Lead BMS Software Engineer

Houston, TX · On-site

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 ...

RWE

VP, Data & AI

Austin, TX

... machine learning, and production AI capabilities * Lead the design, build, and continuous ... battery storage projects that safely deliver affordable, reliable electricity to our customers.

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Battery Machine Learning information

What are the key skills and qualifications needed to thrive as a Battery Machine Learning Engineer, and why are they important?

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 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 is battery machine learning and what do professionals in this field do?

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.
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What cities in Texas are hiring for Battery Machine Learning jobs? Cities in Texas with the most Battery Machine Learning job openings:
Battery Machine Learning jobs near you
Infographic showing various Battery Machine Learning job openings in Texas as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Sr. Machine Learning Engineer, Cell Manufacturing

Sr. Machine Learning Engineer, Cell Manufacturing

Tesla

Austin, TX • On-site

$90.20K - $123.40K/yr

Full-time

Posted 4 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers

Job description

Job Summary:
Tesla is re-thinking battery manufacturing from first principles, seeking research-minded engineers who can bridge rigorous theory and statistical methods with real-world factory impact. In this role, you will apply advanced machine learning to optimize yield, quality, and production efficiency in the Global Cell Manufacturing Analytics team at Giga Texas.
Responsibilities:
• Develop and productionize ML models for key manufacturing problems such as defect detection, anomaly identification, yield forecasting, and process optimization
• Conduct in-depth statistical analysis and feature engineering on complex time-series, sensors, and process datasets while preventing issues like temporal or batch leakage
• Implement full-lifecycle solutions including validation frameworks, drift monitoring, conditional retraining, and metrics linked to factory cost and performance
• Collaborate cross-functionally with process, quality, and materials experts to ensure models are grounded and deliver sustainable results
Qualifications:
Required:
• Degree in a quantitative field such as Applied Mathematics, Physics, Electrical/Systems Engineering, Statistics, Machine Learning, or equivalent experience
• 3+ years of relevant experience applying ML to complex, sensor-rich, or data-intensive problems (research, industrial, or scientific environments preferred)
• Research-oriented mindset with proven experience applying strong ML and statistical fundamentals to challenging data-intensive problems
• Proficiency in PyTorch or equivalent for scientific modeling, going well beyond basic tabular models; experience with vision models preferred
• Hands-on expertise across the full ML lifecycle, including temporal validation, leakage prevention, class imbalance, and production monitoring
• Strong communication skills and the ability to rapidly absorb manufacturing domain knowledge
• Demonstrated research or publication record in ML for complex systems or sensor data (strongly preferred)
Preferred:
• Experience with industrial or physical datasets in manufacturing, energy, or semiconductor environments
• Familiarity with optimization or physics-informed modeling
• Industrial manufacturing experience is a plus but not required
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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