AI Engineer
Summary
Consulting AI engineer on a pharma client's PRIME initiative for brand-performance monitoring: scopes AI use cases with business stakeholders, then designs and deploys ML/GenAI solutions with Python, Azure, and MLOps. B2B contract, 100% remote from Poland, EUR 40-50/hour.
B2B contract
rate 40-50 euro per hour + VAT
100% remote
Pharma domain
We are looking for an experienced AI Engineer to join the PRIME initiative, focused on monitoring brand performance and supporting data-driven decisions regarding resource allocation across brands and markets. The role will initially focus on solution scoping, requirements definition, and translating business needs into scalable AI solutions. In a later phase, the consultant will lead or support the implementation of approved solutions.
Main Responsibilities
Collaborate with business owners and data stakeholders to understand business objectives and define AI use cases.
Participate in workshops and requirements-gathering sessions.
Translate business requirements into AI/ML solution designs and technical specifications.
Define architecture and implementation approaches for AI-enabled products.
Design and develop AI-powered applications and services.
Build scalable pipelines for model deployment and monitoring.
Integrate machine learning solutions into existing data platforms and business processes.
Ensure MLOps best practices, model governance, and operational excellence.
Support solution implementation and production deployment during subsequent project phases.
Key Requirements
5+ years of experience in AI/ML engineering or software engineering with AI focus.
Strong programming skills in Python.
Hands-on experience with machine learning and generative AI technologies.
Experience with cloud platforms (Azure preferred).
Experience designing production-grade AI solutions.
Ability to translate business requirements into technical deliverables.
Strong stakeholder management and communication skills.
Fluent English.
Nice to Have
Experience in FMCG, pharmaceutical, retail, or marketing analytics environments.
Knowledge of LLMs, Retrieval-Augmented Generation (RAG), agentic AI, and prompt engineering.
Experience with Databricks, Azure ML, MLflow, or similar platforms.
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