Job Description
Job Description
Title of the Position: AI Solution Engineer
Employment Status: Salary, Exempt
Department: Department R&D
Accountable to:
This position reports directly to the Team Lead. In the absence of the direct supervisor, Employee would report to the Department Lead R&D.
Supervisory Responsibilities: No
Job Summary:
The AI Solution Engineer designs, develops, and operationalizes AI and machine learning solutions within the Robotics Software Development domain. The role acts as a bridge between business stakeholders and technical implementation, ensuring that AI solutions are scalable, production-ready, and aligned with customer and organizational needs. This position plays a key role in translating real-world logistics and robotics challenges into intelligent, data-driven systems deployed in customer environments.
Essential Functions and Responsibilities:
- Partner with cross-functional stakeholders (product management, engineering, and customers) to identify business problems and translate them into AI-driven solution designs.
- Design, develop, and maintain end-to-end machine learning pipelines, including data ingestion, preparation, training, validation, and benchmarking.
- Integrate, test, and deploy AI models into production environments, particularly within KiSoft RSC solutions.
- Continuously analyze and improve model performance through data-driven optimization and refinement techniques.
- Ensure scalability, robustness, and reliability of deployed AI systems in real-world customer operations.
- Develop efficient inference pipelines and optimize models for performance and resource utilization.
- Collaborate with DevOps and platform teams to implement MLOps practices for automated deployment and monitoring.
- Monitor live systems, troubleshoot issues, and ensure operational stability of AI solutions.
- Document solutions, architectures, and processes to ensure knowledge transfer and maintainability.
Requirements and Qualifications
- 3+ years' experience in Software Development within a relevant industry
- Advanced proficiency in Python and solid software engineering skills.
- Hands-on experience with machine learning frameworks such as PyTorch or TensorFlow.
- Strong understanding of MLOps concepts, tools (e.g., MLflow, Skypilot), and CI/CD practices.
- Experience with cloud platforms such as AWS, Azure, or OCI.
- Proven track record in deploying and optimizing machine learning models in production.
- Knowledge of large language models (LLMs), vision-language models, or computer vision techniques is an advantage.
- Strong analytical, problem-solving, and debugging skills.
- Ability to work in cross-functional teams and communicate complex technical topics effectively.
- Fluent in English (written and spoken); German is a plus.
Other Duties and Responsibilities:
- Contribute to internal knowledge sharing, documentation, and training sessions.
- Stay up to date with emerging AI technologies, tools, and industry trends.
- Support continuous improvement of development standards, tools, and processes.
- Actively contribute to innovation initiatives and pilot projects within the organization.
- Promote a culture of ownership, accountability, and continuous learning.
Working Conditions and Environment:
- Work is performed in a professional office and software development environment.
- Hybrid working model possible depending on project requirements and business needs.
- Collaboration with international and cross-functional teams.
- Traveling is required for customer integration, workshops, or trainings.
- Fast-paced, innovation-driven R&D environment with evolving priorities.