The Role
Designs and deploys enterprise AI solutions using multimodal datasets, predictive modeling, generative AI, and computer vision. Establishes MLOps standards and pipelines for model training, deployment, monitoring, governance, and security across cloud platforms. Translates business requirements into scalable technical architectures, advises stakeholders on cost, latency, privacy, and performance tradeoffs, and mentors engineering teams through roadmaps, code reviews, and design reviews.
Summary Generated by Built In
ABOUT THE POSITION
We are looking for an experienced AI Engineer to join our growing team and help design, and deploy robust AI software solutions for our clients. You will lead and deliver high-impact AI projects in collaboration with renowned clients in the European industry. You will work hands-on with multi-modal datasets, build predictive models, and develop AI-driven products to support operations and gain efficiencies across business units. Your role will combine hands-on technical exposure with scientific curiosity and business relevance: from extracting insights from client interactions to building robust AI architectures which incorporate state-of-art technology and best practices to deliver client solutions. This is more than a job — it’s an opportunity to help shape the future of our company and drive innovation.
ABOUT SPHERE ENERGY
We are a young, dynamic and technology-driven company, committed to developing targeted AI-driven solutions that revolutionize the development of products in the broad field of engineering.
Tasks
KEY RESPONSIBILITIES
* Develop scalable AI-driven software solutions and design end-to-end systems that integrate seamlessly with enterprise data and cloud infrastructure.
* Establish MLOps standards and reusable pipelines, ensuring clean, maintainable code for model training, deployment, and monitoring.
* Translate complex business requirements into technical blueprints, bridging the gap between data science exploration and production engineering.
* Advise stakeholders on technical strategy, clearly communicating architectural tradeoffs regarding cost, latency, and performance.
Requirements
QUALIFICATIONS
* Master’s in Computer Science, Data Science, Machine Learning, or a related field with experience in designing enterprise-scale AI solutions.
* Deep architectural expertise across multiple AI domains—specifically within Generative AI, Computer Vision, and complex predictive modeling.
* Advanced proficiency in Python and modern AI frameworks (PyTorch, TensorFlow), with a strong command of software design patterns, microservices architecture, and API design.
* Expertise in designing robust MLOps ecosystems, including defining standards for CI/CD, model governance, security compliance, and infrastructure orchestration on cloud platforms (AWS, GCP, Azure).
* Ability to define and execute technical roadmaps paired with the experience mentoring engineering teams, conducting code/design reviews, and enforcing engineering excellence.
* Expert at balancing critical architectural tradeoffs, including inference latency, scalability, data privacy, and total cost of ownership.
Benefits
WHAT WE OFFER
* The opportunity to drive leading technology solutions in real-world applications
* A high-impact, client-facing role with real responsibility and room for initiative
* A collaborative and dynamic work environment that values vision and impact
* Opportunity to actively contribute to a young company’s growth
* Flexible working hours and hybrid work models
HOW TO APPLY
If you’re excited to shape the future of battery technology and drive real change with leading industry players, please share your resume and an additional cover letter.
We are looking for an experienced AI Engineer to join our growing team and help design, and deploy robust AI software solutions for our clients. You will lead and deliver high-impact AI projects in collaboration with renowned clients in the European industry. You will work hands-on with multi-modal datasets, build predictive models, and develop AI-driven products to support operations and gain efficiencies across business units. Your role will combine hands-on technical exposure with scientific curiosity and business relevance: from extracting insights from client interactions to building robust AI architectures which incorporate state-of-art technology and best practices to deliver client solutions. This is more than a job — it’s an opportunity to help shape the future of our company and drive innovation.
ABOUT SPHERE ENERGY
We are a young, dynamic and technology-driven company, committed to developing targeted AI-driven solutions that revolutionize the development of products in the broad field of engineering.
Tasks
KEY RESPONSIBILITIES
* Develop scalable AI-driven software solutions and design end-to-end systems that integrate seamlessly with enterprise data and cloud infrastructure.
* Establish MLOps standards and reusable pipelines, ensuring clean, maintainable code for model training, deployment, and monitoring.
* Translate complex business requirements into technical blueprints, bridging the gap between data science exploration and production engineering.
* Advise stakeholders on technical strategy, clearly communicating architectural tradeoffs regarding cost, latency, and performance.
Requirements
QUALIFICATIONS
* Master’s in Computer Science, Data Science, Machine Learning, or a related field with experience in designing enterprise-scale AI solutions.
* Deep architectural expertise across multiple AI domains—specifically within Generative AI, Computer Vision, and complex predictive modeling.
* Advanced proficiency in Python and modern AI frameworks (PyTorch, TensorFlow), with a strong command of software design patterns, microservices architecture, and API design.
* Expertise in designing robust MLOps ecosystems, including defining standards for CI/CD, model governance, security compliance, and infrastructure orchestration on cloud platforms (AWS, GCP, Azure).
* Ability to define and execute technical roadmaps paired with the experience mentoring engineering teams, conducting code/design reviews, and enforcing engineering excellence.
* Expert at balancing critical architectural tradeoffs, including inference latency, scalability, data privacy, and total cost of ownership.
Benefits
WHAT WE OFFER
* The opportunity to drive leading technology solutions in real-world applications
* A high-impact, client-facing role with real responsibility and room for initiative
* A collaborative and dynamic work environment that values vision and impact
* Opportunity to actively contribute to a young company’s growth
* Flexible working hours and hybrid work models
HOW TO APPLY
If you’re excited to shape the future of battery technology and drive real change with leading industry players, please share your resume and an additional cover letter.
Skills Required
- Master's degree in Computer Science, Data Science, Machine Learning, or a related field
- Experience designing enterprise-scale AI solutions
- Architectural expertise in Generative AI, Computer Vision, and predictive modeling
- Advanced proficiency in Python
- Proficiency with PyTorch and TensorFlow
- Strong knowledge of software design patterns, microservices architecture, and API design
- Expertise designing MLOps ecosystems, including CI/CD, model governance, security compliance, and cloud infrastructure orchestration
- Experience with AWS, GCP, or Azure
- Experience defining and executing technical roadmaps
- Experience mentoring engineering teams and conducting code and design reviews
- Expertise balancing inference latency, scalability, data privacy, and total cost of ownership
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The Company
What We Do
Sphere Energy is a Germany-based battery technology and advisory firm specializing in advanced research, testing, and diagnostic services. The company leverages AI-driven simulations and digital twin technology to predict battery performance and aging, streamlining the validation process and accelerating innovation in battery development for sectors such as electric vehicles.









