Automat-it is where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps, FinOps, and GenAI solutions that drive real results. We work across EMEA, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.
We’re looking for a Senior Data Scientist to help shape how our clients build and scale AI solutions on AWS. In this role, you’ll develop and deploy cutting-edge generative AI models on SageMaker – from model training and fine-tuning to optimized deployment – guiding customers from ideation to production through proof of concept. You’ll work closely with startup founders, technical leaders, and account teams to create scalable, high-impact AI solutions that drive real business value.
Work location - hybrid from Madrid
If you are interested in this opportunity, please submit your CV in English.
Requirements:
- 4+ years of experience in machine learning or data science roles, with deep learning (NLP, LLMs) expertise.
- Expert in Python and deep learning frameworks (PyTorch/TensorFlow), and hands-on with AWS ML services (especially SageMaker and Bedrock).
- Proven experience with generative AI and fine-tuning large language models.
- Strong experience deploying ML solutions on AWS cloud infrastructure and familiarity with MLOps best practices.
- Excellent communication skills and ability to work directly with customers in a consulting capacity.
- A master’s degree in a relevant field and AWS ML certifications are a plus.
Responsibilities:
- Model Development & Deployment: Deploy and train models on AWS SageMaker (using TensorFlow/PyTorch).
- Model Tuning & Optimization: Fine-tune and optimize models using techniques like quantization and distillation, and tools like Pruna.ai and Replicate.
- Generative AI Solutions: Design and implement advanced GenAI solutions, including prompt engineering and retrieval-augmented generation (RAG) strategies.
- LLM Workflows: Develop agentic LLM workflows that incorporate tool usage, memory, and reasoning for complex problem-solving.
- Scalability & Performance: Maximize model performance on AWS’s by leveraging techniques such as model compilation, distillation, and quantization and using AWS specific features.
- Collaboration: Work closely with Data Engineering, DevOps, and MLOps teams to integrate models into production pipelines and workflows.
Benefits:
- Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
- International work environment
- Referral program – enjoy cooperation with your colleagues and get a bonus
- Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
- Wellbeing and professional coaching
- English classes
- Soft skills training
Country-specific benefits will be discussed during the hiring process.
Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognizing the value you bring to our team.
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