Machine Learning Engineer (Agentic AI & Automation)
Descrizione dell'offerta
Machine Learning Engineer (Agentic AI & Automation)
Location: Italy (Hybrid / Remote within Milan area)
Employment: Full-time · Permanent
Recruitment handled by: Independent search consultant on behalf of a confidential early-stage client
About the Company
Our client is a fast-growing early-stage technology company developing an AI-first platform for operational automation .
Their product combines software engineering, data, and applied AI to streamline processes in a complex, data-intensive sector.
They are now expanding their team with a Machine Learning Engineer who will take ownership of designing, evaluating, and scaling agentic AI workflows built on modern frameworks.
The Role
The company is developing AI agents that automate decision-making and process execution.
You will work on designing, implementing, and fine-tuning these agents, analysing how they perform in production, and improving their behaviour through evaluation and iteration.
This position requires both machine learning understanding and software engineering discipline .
You’ll be joining a small, highly technical team where initiative, autonomy, and experimentation are expected.
Key Responsibilities
- Build and maintain AI agents and automation workflows using the Mastra framework (TypeScript).
- Design evaluation pipelines and metrics to track model performance and behaviour.
- Conduct fine-tuning, prompt iteration, and workflow optimisation to improve outcomes.
- Integrate LLMs, vector databases, and external APIs into structured agentic workflows.
- Develop new automation use cases in collaboration with the engineering and product teams.
- Document experiments and results to ensure reproducibility and transparency.
Tech Environment
- Core: TypeScript, Mastra (agentic AI framework)
- Supporting tools: LangGraph / LangChain (Python), vector DBs such as LanceDB or Pinecone
- MLOps concepts: evaluation, scoring, telemetry, CI/CD, prompt versioning
- Infrastructure: Node.js, GCP, Docker, Cloud Run, Pub/Sub, Dataflow
Knowledge of Mastra is not required, experience with any agentic or LLM-based framework is acceptable.
Candidate Profile
- 2–6 years of experience in machine learning, applied AI, or software engineering with ML components.
- Understanding of LLMs, embeddings, RAG, and agentic workflow concepts .
- Strong coding skills (Python or TypeScript).
- Practical mindset and willingness to experiment, test, and iterate.
- Capable of working autonomously in a non-structured, startup environment .
- Comfortable analysing data, debugging models, and communicating results clearly.
Desirable Skills
- Experience with workflow orchestration , LLM evaluation , or MLOps .
- Familiarity with document automation or structured data extraction .
- Prior exposure to startups or small engineering teams.
Ideal Candidate Mindset
We’re looking for a builder, someone who enjoys solving open-ended technical problems, exploring new frameworks, and turning research into working production systems.
If you like fast feedback loops, autonomy, and the idea of being the first engineer in a growing AI vertical, this environment will suit you well.