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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 ...

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

$122K - $161K/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

$122K - $161K/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

$122K - $161K/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

$122K - $161K/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

BMS Data Analysis Engineer

Houston, TX · On-site

$109K - $131K/yr

... machine learning frameworks is a plus. • Familiarity with cloud computing and distributed computing frameworks Company : Microvast designs, develops, and manufactures charging, battery control ...

MICROVAST INC

BMS Algorithm Engineer

Houston, TX · On-site

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 ...

MICROVAST INC

BMS Data Analysis Engineer

Houston, TX · On-site

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 ...

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 ...

Ørsted

Senior Analyst, Asset Performance

Austin, TX

$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 ...

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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 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.

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:
Battery Machine Learning jobs near you
Staff Data Science Engineer

Staff Data Science Engineer

Qorvo, Inc.

Richardson, TX • On-site

Full-time

Re-posted 26 days ago

Qorvo rating

8.3

Company rating: 8.3 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

Job description

Qorvo (Nasdaq: QRVO) supplies innovative semiconductor solutions that make a better world possible. We combine product and technology leadership, systems-level expertise and global manufacturing scale to quickly solve our customers' most complex technical challenges. Qorvo serves multiple high-growth segments of large global markets, including consumer electronics, smart home/IoT, automotive, EVs, battery-powered appliances, network infrastructure, healthcare and aerospace/defense. Visit www.qorvo.com to learn how our innovative team is helping connect, protect and power our planet.
Role Summary
We are looking for a Staff Data Science Engineer to lead the design and delivery of scalable data science, machine learning, and analytics solutions that create measurable business value across the enterprise. This role sits at the intersection of data science, data engineering, analytics engineering, and AI productization. The right person will pair strong technical depth with practical business judgment, helping turn complex data into decisions, tools, and systems that improve operations, reduce cost, accelerate insight, and scale AI adoption.
This is a senior individual contributor role for someone who can operate as a technical leader across functions, influence stakeholders from engineers to executives, and build robust solutions in environments where data quality, governance, speed, and return on investment all matter.
In the current integration environment, this role must also work effectively within approved collaboration and information-sharing processes, including formal handling of cross-company meetings, data requests, documentation, and CSI-sensitive workflows described in the Project Comet guidance.
What You'll Do
  • Lead the architecture and implementation of production-grade data science and machine learning solutions, from problem framing through deployment and adoption.
  • Build scalable data products, models, and decision-support tools using statistical methods, machine learning, optimization, and modern analytics engineering practices.
  • Partner with business leaders, engineering, IT, manufacturing, quality, finance, and other cross-functional teams to identify high-value opportunities and prioritize work with clear business impact.
  • Translate ambiguous business problems into structured analytical approaches, measurable success criteria, and deliverable roadmaps.
  • Design and maintain reliable data pipelines, feature pipelines, experimentation frameworks, and model monitoring practices.
  • Drive the responsible use of AI across the organization by developing reusable frameworks, templates, evaluation approaches, and best practices for enterprise adoption.
  • Serve as a technical mentor to data scientists, analysts, and engineers; raise the bar on coding, experimentation, documentation, and stakeholder communication.
  • Create executive-ready narratives, visualizations, and recommendations that connect technical findings to business outcomes.
  • Partner with data platform and governance teams to ensure solutions meet requirements for security, compliance, and maintainability.
  • Help shape standards for model lifecycle management, MLOps, analytics engineering, and AI solution delivery.
  • Contribute to integration planning and enterprise analytics initiatives while following approved protocols for meetings, shared materials, data requests, and CSI/non-CSI handling where applicable. Project Comet guidance requires legally approved agendas for certain new cross-company meetings, use of the Data Request List for shared data, and routing potentially sensitive data through the appropriate review path or clean room process.

What Success Looks Like
  • You deliver analytics and AI solutions that produce measurable operational or financial impact.
  • You help the team focus on high-return opportunities that leadership can easily justify and support.
  • You raise technical quality while also improving speed, reuse, and maintainability.
  • You make data science more accessible to the business through better tools, communication, and enablement.
  • You influence decisions well beyond your direct project work.
  • You help the organization use data and AI more effectively without compromising governance, security, or compliance.

Required Qualifications
  • Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, Applied Mathematics, or a related technical field.
  • 8+ years of experience in data science, machine learning, analytics engineering, or data platform development, including experience delivering business-facing solutions in production.
  • Strong programming skills in Python and SQL.
  • Deep experience with statistical analysis, machine learning, feature engineering, model evaluation, and experimental design.
  • Strong experience building data pipelines and working with modern data platforms and cloud analytics ecosystems.
  • Demonstrated ability to own ambiguous, high-impact problems and drive them through to adoption.
  • Experience partnering with senior stakeholders and influencing decisions across technical and non-technical groups.
  • Strong written and verbal communication skills, including the ability to explain complex concepts clearly to executives and business partners.
  • Proven ability to mentor others and lead technically without direct authority.

Preferred Qualifications
  • Advanced degree in a quantitative or technical field.
  • Experience in semiconductor, manufacturing, operations, supply chain, quality, or related industrial domains.
  • Experience building and operationalizing AI/ML solutions at enterprise scale.
  • Experience with MLOps, model monitoring, and deployment workflows.
  • Experience with Databricks, Spark, orchestration tools, BI platforms, and modern software engineering practices.
  • Familiarity with secure data environments and regulated data handling.
  • Experience working in environments that require balancing innovation with compliance, governance, and business urgency.
  • Exposure to enterprise AI enablement, internal tooling, or organization-wide adoption programs.

Technical Skills
  • Python, SQL
  • Machine learning, statistics, optimization, experimentation
  • Data modeling, ETL/ELT, analytics engineering
  • Cloud and distributed data platforms
  • BI and visualization tools
  • Git-based development workflows and production-quality software practices
  • MLOps and model lifecycle management
  • Data governance, documentation, and reproducibility

Leadership Expectations
  • Acts like an owner and focuses on business value, not just technical elegance.
  • Brings an abundance mindset and collaborates across organizational boundaries.
  • Balances strategic thinking with hands-on execution.
  • Pushes for clarity, rigor, and practical outcomes.
  • Elevates the team through mentorship, standards, and example.
  • Exercises strong judgment around sensitive data, stakeholder alignment, and enterprise constraints.

Sample Responsibilities by Problem Type
  • Build predictive and optimization models that improve yield, quality, throughput, cost, or planning.
  • Develop AI-enabled tools that scale analyst and engineer productivity.
  • Create reusable data products that standardize metrics, reduce manual effort, and improve decision speed.
  • Lead diagnostic and exploratory analyses on complex manufacturing, product, or enterprise datasets.
  • Establish frameworks for model governance, evaluation, and business adoption.

This position is not eligible for visa sponsorship by the Company.
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MAKE A DIFFERENCE AT QORVO
We are Qorvo. We do more than create innovative RF and Power solutions for the mobile, defense and infrastructure markets - we are a place to innovate and shape the future of wireless communications. It starts with our employees. As a unified global team, we bring a commitment to excellence, growth and a passion for creating what's next. Explore the possibilities with us.
We are an Equal Employment Opportunity (EEO) employer and welcome all qualified applicants. Applicants will receive fair and impartial consideration without regard to any characteristics protected by applicable law, including race, color, religion, sex (as defined by law), national origin, age, military or veteran status, genetic information, or disability.
Qorvo is an E-Verify Employer. For more information, please see the Right to Work and E-Verify Participation posters.

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