AI Simulation Engineer

AI Simulation Engineer (m/f/d 100%)

Location: Zurich or Munich

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

ABOUT THE POSITION

We are seeking the brightest minds to join our growing team as an AI Simulation Engineer.

In this role you will lead and deliver high-impact AI projects in collaboration with leading clients across different industries and contribute to the development of our internal AI and data product portfolio. You will work hands-on with real-world multi-modal datasets build predictive models and develop AI-driven simulation technologies to accelerate product development.

Your role will combine technical and hands-on expertise with scientific curiosity: from extracting insights and building robust AI models to shaping client solutions and guiding the evolution of our technology offerings.

This is more than a job it is an opportunity to help shape the future of our company and drive technology innovation in one of the most critical industries of our time.

Requirements

KEY RESPONSIBILITIES

Internal Product Development

• Research innovative ways of solving identified market challenges by applying data-driven and physics-informed AI technologies
• Own development streams towards the productionalization of new simulation products/offerings
• Work closely with stakeholders to gather requirements and define feature priorities

Hands-on Project Involvement

• Participate in the delivery of client projects by developing new features and act as a key sparring partner for project managers and relevant client stakeholders
• Oversee the processes and structures to keep internal timeline targets

Technology Scouting

• Support the constant development of our service portfolio by identifying new technological opportunities

YOUR PROFILE

• Masters degree in Data/Computer Science Applied Mathematics Engineering or a related field
• Relevant practical experience in machine learning applied to at least two different AI domains - such as large language models computer vision time-series modeling etc.
• Strong skills in Python and common libraries such as Pandas Scikit-learn or PyTorch
• Experience in MLOps including model deployment monitoring CI/CD pipelines experiment tracking (e.g. MLflow) as well as cloud platforms (AWS GCP Azure)
• Track record of rapid prototyping POCs and iterative model improvement ideally in a client-facing environment
• Ability to translate ambiguous engineering problems into AI-driven solutions and evaluate the model performance deployment complexity latency and cost tradeoff
• Collaborative mindset paired with a high sense of end-to-end ownership and initiative
• Curiosity to explore emerging AI technologies architectures and tools

NICE TO HAVE

• Experience with system simulations (CFD FEA Thermal/Fluid dynamics etc.) and integrating AI models into real-world engineering systems
• Expertise in multi-modal AI work and various architectures (e.g. transformers multi modal encoders) or novel modalities (multi-sensor fusion LAMs generative design)

Benefits

BENEFITS

• Exposure to innovative technologies in real-world applications across different industries
• A dynamic young and collaborative work environment that fosters innovation
• Opportunity to influence strategy and product roadmap of the company
• Hybrid working mode and flexible working hours
• Fair market salary variable compensation

HOW TO APPLY

If you are ready to embark on a journey of innovation and contribute to the evolution of the engineering industry please share your resume and a cover letter detailing your interest and relevant experience.