ML Engineer
Put machine learning models into production with scalable and reliable infrastructure.
ML Engineer
The ML Engineer bridges the gap between data science and production engineering. As companies move from ML experiments to production systems, the demand for engineers who can deploy, scale, and maintain ML models has skyrocketed. With GenAI requiring massive infrastructure, ML Engineers who understand both the science and the engineering are commanding top salaries across Europe and the US.
Competências
Otimização LinkedIn
- 1
Show experience with model deployment at scale
- 2
Highlight projects with real production metrics
- 3
Post about MLOps trends and best practices
- 4
Connect with ML leads at target companies
- 5
Mention specific ML infrastructure you've built
CV e Currículo
- 1
Quantify: "Deployed model serving 1M predictions/day"
- 2
Detail ML infrastructure and pipeline experience
- 3
Show end-to-end ML lifecycle management
- 4
Include monitoring and model drift detection experience
- 5
Highlight experience with feature stores and experiment tracking
Estratégia de Outreach
- 1
Research what ML infrastructure the company uses
- 2
Mention specific ML challenges you can help solve
- 3
Share a case study of ML deployment at scale
- 4
Connect with ML engineers already at the company
- 5
Demonstrate understanding of MLOps best practices
Preparação para Entrevistas
- 1
Prepare ML system design scenarios
- 2
Know the full ML lifecycle from training to monitoring
- 3
Practice explaining trade-offs in model serving architectures
- 4
Have examples of debugging production ML systems
Um dia como ML Engineer
Review model performance dashboards, optimize inference latency, build and maintain ML pipelines, collaborate with data scientists on model deployment, work on feature engineering and experiment infrastructure.
Trajetória Profissional
Erros comuns
Only showing research projects without production experience
Not mentioning infrastructure and deployment skills
Ignoring monitoring and observability in your profile
Not having cloud ML platform experience
Forgetting to mention collaboration with data scientists
Ferramentas essenciais
Perguntas frequentes
Salário médio de um/a ML Engineer?
O salário médio de um/a ML Engineer na Europa varia entre 60K - 110K EUR. Isso varia de acordo com experiência, localização e tipo de empresa.
Competências-chave para um/a ML Engineer?
Principais competências técnicas: Python, MLOps, Cloud ML, Docker, Data Pipelines. Soft skills como comunicação e trabalho em equipe são igualmente importantes.
Trajetória profissional de um/a ML Engineer?
Caminho típico: Junior ML Engineer > Mid ML Engineer > Senior ML Engineer > Staff ML Engineer > Head of ML Engineering > VP of AI Infrastructure.
ML Engineer
Envie seu perfil para revisão. Estudo pessoalmente cada aplicação. Se você qualificar, entrarei em contato com uma análise detalhada e seu plano de otimização personalizado.