Machine Learning Engineer Python AWS

Client Server Limited

Milano

Ibrido

EUR 45.000 - 75.000

Tempo pieno

7 giorni fa
Candidati tra i primi
Generatore di candidature

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Vantaggi offerti da questo lavoro

Lunch tickets (€7)
Welfare credit €1,500/year
Work from anywhere in EU (30 days)
Diverse, inclusive team environment

Descrizione del lavoro

Client Server Limited is seeking a Machine Learning Engineer (Python, AWS, MLOps) in Milan with hybrid/remote options. You will join a cross-functional team to develop and deploy ML models for insurance pricing, data modelling, and forecasting, contributing from design through production.

The role offers flexible work from home most of the time and 1–2 days in the Milan office. The ideal candidate has advanced Python skills, strong AWS knowledge, and experience across the full ML lifecycle,

Competenze

  • Advanced Python coding skills and strong knowledge of AWS.
  • Experience across the full lifecycle of ML model development including production.
  • Collaborative, problem solving, and team-oriented.
  • Knowledge of modern software engineering practices, microservices, TDD/DDD, design patterns.

Mansioni

  • Collaborate with data scientists and software engineers on ML projects.
  • Develop ML models and bring them into production.
  • Work on data modelling and forecasting/pricing projects.

Conoscenze

Python
AWS
ML lifecycle
Collaboration
Problem solving
Microservices
TDD/DDD
Design Patterns

Strumenti

Databricks
PostgreSQL
Amazon Redshift
MLflow

Descrizione del lavoro

Machine Learning Engineer (Python AWS MLOps) Milan / WFH to €75,000

Are you a tech savvy Machine Learning Engineer with experience of implementing ML algorithms into production?

You could be progressing your career in a senior, hands-on role as part of a friendly and supportive international team at a growing and hugely successful European car insurance tech company as they expand their UK presence; their platform enables an insurance quote to be made to the consumer within 60 seconds, using just 4 clicks.

As a Machine Learning Engineer you'll join a cross functional team, collaborating with Data Scientists and Software Engineers on complex insurance underwriting and pricing systems. They'll be a range of projects including data modelling and implementing Machine Learning algorithms, with Greenfield projects in the pipeline around forecasting and pricing.

There's a collaborative team Agile environment where you'll participate in technical discussions and have your voice heard, there's also opportunities to mentor other more junior team members if desired.

Location / WFH:

The company is a big advocate of flexible working and prides itself on DEI; you can work from home most of the time, joining colleagues in the Milan office 1-2 days a week; you can also work at times that suit you.

About you:
  • You are a data savvy Machine Learning Engineer with advanced Python coding skills and a strong knowledge of AWS
  • You have experience of across the full lifecycle of ML model development including into production
  • You're collaborative, enjoy problem solving and working with others to overcome technical challenges
  • You have a good knowledge of modern software engineering best practices, microservices, TDD / DDD, common Design Patterns
  • Experience with Databricks, PostgreSQL, Amazon RedShift or MLflow would be great but not essential
What's in it for you:
  • Up to €75,000 salary
  • €7 lunch ticketsWelfare credit of €1,500 p/year
  • Ability to work 30 days from any EU country
  • Diverse, inclusive team environment with a range of support networks (e.g. LGBTIQA+, Women's Networking group)

At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values. #LI-DNI

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