Role overview

Qualifications

Strong background in Data Science / ML / Statistics
Hands-on ML pipelines in Python or R (e.g., scikit-learn, pandas, numpy)
Practical GenAI experience (LLMs, LangChain, Chainlit, RAG)
Comfortable working with messy, real-world customer data

Responsibilities

Build and deliver AI / ML proof-of-concepts
Prepare data, implement models, and deliver production-ready code
Apply LLMs in practice (prompting, structured outputs, evaluation, RAG)
Collaborate closely with client teams and support workshops

Key facts

Remote from: Anywhere
Full time
Artificial Intelligence Engineer
English

Hard skills

Data Science Large Language Modeling Python (Programming Language) Data Quality Assessment Prompt Engineering Statistics Data Wrangling Code Generation Proof Of Concept (POC) Development Model Validation R (Programming Language) Meeting Facilitation

Other skills

Collaboration

About the company

BilgeAdam Technologies

Company details

Links

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Job description

This is a remote position.

Project overview

Client: AI company
Duration: 12 months
Start: ASAP
Working mode: Fully remote
Daily rate: up to 350€

Role context

Hands-on Data Scientist / Applied AI Engineer role focused on delivering practical AI and GenAI solutions. The work is execution-driven, with strong emphasis on data quality, evaluation, and reliable outputs rather than platform or BI development.

Scope

· Build and deliver AI / ML proof-of-concepts

· Prepare data, implement models, and deliver production-ready code

· Apply LLMs in practice (prompting, structured outputs, evaluation, RAG)

· Collaborate closely with client teams and support workshops

Good fit / No fit (important)

Good fit: hands-on, Python-first, delivery-oriented AI engineers
No fit: data platform / BI profiles, architecture-heavy roles, research-focused or lead-only profiles

Requirements

Required profile

· Strong background in Data Science / ML / Statistics

· Hands-on ML pipelines in Python or R (e.g. scikit-learn, pandas, numpy)

· Practical GenAI experience (LLMs, LangChain, Chainlit, RAG)

· Comfortable working with messy, real-world customer data

· English B2+

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