Machine Learning Engineer

About

ALSO Holding AG (ALSN.SW) (Emmen/Switzerland) is one of the leading technology providers for the ICT industry, currently operating in 31 European countries and numerous other countries worldwide through PaaS partners. The ALSO ecosystem comprises a total potential of more than 135,000 resellers, to whom we offer hardware, software, and IT services from more than 800 vendors in over 1,570 product categories. In line with the circular economy, the company provides all services from a single source, from provision to refurbishment.

The business activities include Supply, Solutions, and Service. Supply encompasses the transactional offering of hardware and software. Solutions supports customers in developing customized IT solutions. Subscription-based cloud offerings and digital platforms for IoT, cybersecurity, virtualization, and AI are at the core of the Service division. The main shareholder is Droege Group, Düsseldorf, Germany. Further information at: https://also.com.

ALSO Values

It is one of our fundamental values to respect human rights and ensure they are respected. This includes, in particular, respecting the personal dignity and privacy of each individual. Ethical conduct in business dealings with our partners is also expected from all our employees. We are committed to fair, unrestricted competition and do not allow ourselves to be influenced by gifts or invitations, let alone financial advantages, in our decisions. ALSO's goal is to improve the lives of all people through technology. This also includes protecting our environment and carefully managing the limited resources available to us. Further information can be found in our Code of Conduct.

Learn more about ALSO – THE TECHNOLOGY PROVIDER at: https://also.com

Job Description

As an ML Engineer within the ALSO Analytics Team, you will contribute directly to data-driven solutions that create tangible business impact across the organization. In this role, you will work closely with internal business stakeholders and domain experts to transform complex challenges into scalable, intelligent systems. Your technical expertise and curiosity will help you spot opportunities in a rapidly evolving business environment, enabling our teams to make better, faster, and more informed decisions. You will help shape the entire life-cycle of machine-learning products—from early experimentation and prototyping to scalable deployment and long-term maintenance. By combining analytical rigor with hands-on engineering skills, you will play a key role in building the next generation of data products that support our colleagues in their daily work.

Key Responsibilities

Machine Learning Engineering

• Design and develop robust ML systems, models, and algorithms that address real business needs.
• Train, fine-tune, and optimize models to ensure high performance and reliability.
• Evaluate model behavior through experiments and benchmarking to guide technical decisions.

Data Workflows & Pipelines

• Prepare, clean, and analyze large and complex datasets to support ML development.
• Build, maintain, and improve automated ML pipelines—from data ingestion to model deployment.
• Ensure scalability and operational stability of end-to-end ML workflows.

Deployment & Operations

• Deploy ML models to production environments, ensuring they integrate seamlessly with business applications.
• Monitor, evaluate, and continuously improve existing models to maintain accuracy and relevance over time.

Communication

• Communicate insights, findings, and results in a clear and accessible way to both technical and non-technical audiences.
• Contribute to shared best practices, internal knowledge exchange, and the evolution of team workflows.

Required Skills & Qualifications

Technical Skills

• Contribute to shared best practices, internal knowledge exchange, and the evolution of team workflows.
• Strong programming skills, particularly in Python.
• Experience with major ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Expertise creating LLM solutions using base-models (Agents, Tool calling, Workflows).
• Solid foundation in statistics, mathematics, and data modeling techniques.
• Knowledge of neural network architectures and modern ML methodologies.
• Understanding of fundamental software engineering principles, version control, and CI/CD.
• Familiarity with cloud computing environments.

Soft Skills

• Strong problem-solving abilities combined with creativity and initiative.
• Analytical and structured thinking, with attention to detail.
• Ability to communicate complex topics clearly and effectively.
• Comfortable working in cross-functional, collaborative teams.
• Curiosity and a mindset of continuous learning in a rapidly evolving field.

Information at a Glance

• Location: Berlin, Germany | Remote | Soest, Germany
• Experience Level: Senior
• Job Function: Information Technology
• Travel: No travel