Data Scientist / ML Engineer

Data Scientist / ML Engineer

Addepto

Hexjobs Insights

Addepto seeks a Data Scientist / ML Engineer to develop and implement AI solutions. Key tasks include architecture design, pipeline implementation, and client communication. Requires 3+ years in AI, strong Python skills, and cloud experience.

Schlüsselwörter

AI solutions
Machine Learning
Predictive Modeling
Cloud environments
Python
ML libraries
MLOps
SQL
NoSQL
Frontend frameworks

Vorteile

  • Reimbursement for prescription glasses or contact lenses
  • Sharing the costs of sports activities
  • Private medical care
  • Share costs of professional training & courses
  • Remote work opportunities
  • Flexible working time
  • Integration events
  • No dress code
  • Video games at work
  • Coffee / tea
  • Drinks
  • Christmas gifts
  • Birthday celebration
  • Employee referral program

Anforderungen

Proven commercial experience (+3 years) designing and implementing scalable AI solutions (Machine Learning, Predictive Modeling, Optimization, LLM, NLP, Computer Vision, GenAI)., Proficiency in developing ML algorithms from scratch to production deployment., Strong programming skills in Python: writing clean code, OOP design, extensive knowledge of ML libraries (Scikit-Learn, PyTorch / Tensorflow)., Proven expertise in deploying solutions in cloud environments (AWS or Azure)., Knowledge in applying LLMs (semantic search, prompt engineering, multimodal embeddings, RAG)., High proficiency in English (C1 level)., Excellent communication skills and consulting experience with direct interaction with clients., Working experience in SQL and NoSQL databases (MongoDB, Snowflake, Databricks)., Good knowledge of CI/CD principles (GitHub and GitHub Actions)., Familiarity with MLOps practices, Kubernetes and Docker., Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Physics, or a related field., Practical experience with frontend frameworks (e.g., React, Node.js, Nest.js, Typescript).

Vorteile

Reimbursement for prescription glasses or contact lenses, sharing the costs of sports activities, private medical care, sharing the costs of professional training & courses, remote work opportunities, flexible working time, integration events, no dress code, video games at work, coffee / tea, drinks, christmas gifts, birthday celebration, employee referral program

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Aufrufe: 31
Veröffentlichtvor 26 Tagen
Läuft abin 5 Tagen

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