We Love AI JobsAI / ML Engineer - Simulation
Talent360GlobalAbout Talent360Global
Talent360Global is an AI-driven HR innovation initiative focused on skills-first hiring and workforce development. As part of our global pledge, we are committing to train and skill-verify 300 candidates free of charge, helping professionals demonstrate their real capabilities through practical job simulations rather than traditional CV screening. Skills-first hiring focuses on evaluating candidates based on demonstrable abilities and competencies rather than degrees or job titles, enabling employers to identify talent that can actually perform the role.
Through this initiative, Talent360Global aims to connect verified talent with organizations seeking professionals who can deliver measurable results. Participants who successfully complete the simulation may have their profiles shared with our hiring partners across multiple industries.
More details about the pledge and our skills-first hiring approach are available at:
www.talent360global.de
About the Role (AI/ML Engineering Simulation)
Talent360Global invites engineers and data professionals worldwide to participate in a skills-based simulation for the role of AI / Machine Learning Engineer. This simulation is based on real market vacancies and is designed to identify professionals who can demonstrate practical machine learning capability through real problem solving.
This is not a job offer.
Candidates who successfully complete the simulation will have their profiles shared with partner organizations and companies actively hiring for AI / Machine Learning Engineer roles, participation certificate, and placement in our database of qualified candidates
Responsibilities
1. Design and implement machine learning models and algorithms to solve data-driven problems
2. Analyze and preprocess structured or unstructured datasets
3. Perform feature engineering and select appropriate data representation methods
4. Train, evaluate, and optimize machine learning models
5. Conduct model testing and experiments to improve performance
6. Build data pipelines and prepare datasets for machine learning workflows
7. Collaborate with engineering or data teams to translate business problems into machine learning solutions
8. Deploy machine learning models or propose deployment architecture for production systems
9. Monitor model performance and improve prediction accuracy
Skills
1. Strong programming ability (Python preferred)
2. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
3. Knowledge of machine learning algorithms, classification, regression, and model evaluation
4. Experience with data analysis libraries such as Pandas and NumPy
5. Understanding of statistics, probability, and data modeling
6. Ability to analyze large datasets and extract insights
7. Familiarity with cloud infrastructure, APIs, or model deployment pipelines is an advantage
8. Strong analytical and problem-solving skills
9. Ability to document and communicate technical approaches clearly
Qualifications & Experience
* Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related technical field
* Typically 3–5 years of experience in machine learning, AI, or data science roles
* Experience building machine learning models or data-driven systems
* Familiarity with machine learning experimentation and model evaluation techniques
Simulation Overview
Successful candidates will receive a link to complete a structured technical simulation designed to reflect real machine learning engineering tasks.
The simulation is completed remotely and has a maximum duration of 8 hours.
What to Submit
* • Curriculum Vitae (CV)
* • Educational documents
* • Reference letter from previous employer (if available)
* • Optional proof of previous employment or project experience (We recommend to request references from your managers and colleagues while being on the job)
Onboarding
Simulation onboarding will take place online via our LinkedIn event on 29 March 2026 from 13:00 to 15:00 (Berlin Time), Please adjust for your local time zone.
Participants should register here: https://www.linkedin.com/events/7428171353423233024
Participation is free for simulation candidates.
The final access link and instructions will be shared two day before the event on 27 March 2026.