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- Collaborate with AI researchers to identify key legal concepts and areas for model training.
- Provide expert insights into legal terminology and processes.
- Curate and review legal datasets for training purposes.
- Validate and test the model's outputs for accuracy and reliability in legal contexts.
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Freelance Mathematics Expert for AI Model Training (m/f/d)
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This is a remote part-time role that can be flexibly tailored to your availability – from just a few hours per week to full-time.
Key responsibilities:
- Evaluate AI models for mathematics applications.
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- Collaborate with the development team to ensure alignment with industry standards.
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- Conduct tests to validate model performance and reliability.
Freelance Chemistry Expert for AI Model Training (m/f/d)
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This is a remote part-time role that can be flexibly tailored to your availability – from just a few hours per week to full-time.
Key responsibilities:
- Evaluate AI models for chemistry applications.
- Analyze model outputs and provide feedback for improvement.
- Collaborate with the development team to ensure alignment with industry standards.
- Document findings and recommendations for model optimization.
- Conduct tests to validate model performance and reliability.
Freelance Physics Expert for AI Model Training (m/f/d)
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- Collaborate with the development team to ensure alignment with industry standards.
- Document findings and recommendations for model optimization.
- Conduct tests to validate model performance and reliability.
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This is a flexible, impact-driven role where you’ll have space to grow, contribute ideas, and help shape how evaluation and quality are scaled across the project.
This role is especially well-suited for:
Analysts, researchers, or consultants with strong structuring and reasoning skills Junior product managers or strategists curious about AI and evaluation work Smart problem-solvers (students or early-career professionals) who enjoy digging into logic, systems, and edge cases
You do not need a coding background. What matters most is curiosity, intellectual rigor, and the ability to evaluate complex setups with precision.
What you’ll be doing
- Fully own the QA pipeline for agent evaluation tasks;
- Review and validate tasks and golden paths created by scenario writers and experts;
- Spot logical inconsistencies, vague requirements, hidden risks, and unrealistic assumptions;
- Provide structured feedback and ensure quality alignment across contributors; Train, onboard, and mentor new QA team members;
- Collaborate with domain experts, delivery managers, and engineers to improve test clarity and coverage;
- Maintain and improve QA checklists, SOPs, and review guidelines;
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- Take initiative to suggest new approaches, tools, and processes that help scale validation and analysis.
New
Consultant Corporate Finance / M&A Consultant / Finance
For an AI lab we are looking for freelance finance consultants to train an AI model (Large Language Model - LLM) in various domains:
You help AI to make sense of the world. As consultant, you may be invited to take part in online projects to train the model in your domain of expertise. This flexible role accommodates both experts seeking part-time engagement (minimum few hours/week) and those interested in full-time opportunities
Support on one or more of the following tasks:
- Financial Forecasting
- Risk Management
- International Finance
- Financial Engineering
- Economics, Corporate Finance
- Investment Management, Mathematical Finance
- Public Finance, Behavioral Finance
- Financial Markets and Institutions
- Finance Technology
- Algorithmic Trading
Frontend developer to HR platform with Angular experience
Reach out to us if you are interested in working with us on the project.
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Cloud Infrastructure Engineer (m/f/d) (9442)
Industry
Telecommunication
Area
Information Technology (IT)
Project info
- Period01.05.2025 - 30.06.2025
- Capacityfrom 95%
- Daily rate500 - 550€
- Languages Essential:
- English(Advanced)
Desirable:- German(Advanced)
- English
- Remotefrom 95%
Description
The AWS Landing Zone project aims to provide a scalable and standardized cloud environment to support cloud migration efforts. As part of the Cloud Center of Excellence, the focus is on establishing a secure, compliant, and extensible architecture that serves as a foundation for future cloud workloads. Particular attention is given to the challenges of scalability and security to ensure a flexible, high-performance, and policy-compliant environment.
A key milestone is the implementation of a Security Credential Management system that ensures secure access and authorization while complying with corporate policies and regulatory requirements. Additionally, automation and testing are used to guarantee efficiency and quality in the deployment and management of the cloud environment. Another critical aspect is the provision of a secure internet connection that meets stringent security requirements and enables reliable communication for cloud workloads. The architecture must be designed to support future expansion and adapt flexibly to new demands.
Scope of Work:
- Optimization of the AWS Landing Zone using AWS, Terraform, Terragrunt, and Python; automation of processes with AWS Lambda, Go, and Bash; code development with CodeCommit and GitLab; development and administration using CoPilot and Visual Studio Code.
- Expansion and improvement of CI/CD pipelines through the use of GitLab for source code management, AWS CodeBuild for automated builds, State Machines and AWS Lambda for deployment orchestration, and Python for process automation.
- Reinforcement of security controls and compliance validation by leveraging AWS IAM for identity and access management, AWS Config for configuration monitoring, AWS EventBridge for security-relevant events, and automation via AWS Lambda and Python; continuous alignment with security standards in consultation with the security team.
- Enhancement of the monitoring system using Amazon CloudWatch and DevOps Guru for log and metric monitoring, log forwarding and custom metrics for detailed analysis, active network tests for performance validation, and automation with AWS Lambda and Python.
- Optimization of network services using AWS Route 53 Resolver, Route 53, VPC, VPN, Transit Gateway (TGW), and Direct Connect (DX); increased availability with Network Load Balancer (NLB) and Application Load Balancer (ALB); secure application integration using API Gateway; and strengthened security mechanisms through firewalls in collaboration with the Firewall & Security team.
Requirements
- Two or more years of comprehensive hands-on experience in infrastructure development and operations in cloud environments.
- Very good hands-on experience with Infrastructure as Code and CI/CD practices using Terraform.
- Additional Terragrunt experience is preferred.
- Experience developing code in at least one of the following programming languages (Python, Go, Bash).
- Knowledge of networking concepts (e.g. DNS, routing, firewalls).
- Hands-on experience with agile methodologies (Scrum, Scrumban, etc.).
- Experience in building and operating highly automated infrastructures.
- Proficiency in auditing, monitoring and debugging cloud-based infrastructure.
- Understanding of modern development and operations processes and methodologies.
- Understanding of security concepts with hands-on experience in implementing security controls and compliance requirements.
- Knowledge of recommended best practices for building secure and reliable infrastructure in cloud environments.
- Role specific certifications (AWS, Terraform) will be preferred.
Must have:
- Good Terraform skills
- Good experience on AWS
- Python skills
Should have:
- Agile methods
- Experience with "Go" programming language
- CI/CD with Infrastructure as Code using Terraform
- Remote working
English
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