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Amsterdam
1 day ago
ML Engineer - Life Sciences (Early Talent) logo

ML Engineer - Life Sciences (Early Talent)

Nebius

Amsterdam
1 day ago
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ML Engineer - Life Sciences (Early Talent)

Nebius is seeking an ML Engineer (Early Talent) for a 3-6 month paid program in Amsterdam. The role focuses on optimizing biological AI models for faster inference through profiling, model compression, and efficient pipeline building. Requires a background in computer science or AI, Python, and deep learning frameworks.

AIOn-siteFull-timeEntry LevelPythonDeep Learning

ML Engineer - Life Sciences (Early Talent)

Nebius is seeking an ML Engineer (Early Talent) for a 3-6 month paid program in Amsterdam. The role focuses on optimizing biological AI models for faster inference through profiling, model compression, and efficient pipeline building. Requires a background in computer science or AI, Python, and deep learning frameworks.

Apply
AIOn-siteFull-timeEntry LevelPython

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

On-site

Employment Type

Full-time

Experience Level

Early Talent (current student, recent graduate, or early career specialist)

Contract Length

6 months

Core Qualifications

Technical (Must-have)
PythonDeep LearningMachine LearningComputer ScienceModel CompressionQuantizationPruningDistillationInference OptimizationGPU ProfilingTransformer ArchitecturesLarge Language ModelsDistributed InferenceOpen Source
Soft Skills
Problem-solvingWillingness to learnClean code writing

Preferred Qualifications

Technical (Nice-to-have)
Large Language ModelsTransformer ArchitecturesGPU Workload ProfilingModel CompressionDistributed InferenceOpen Source ML Projects

Key Responsibilities

  • •Profile inference bottlenecks in selected biological models
  • •Implement and test optimization techniques (quantization, pruning, distillation)
  • •Explore efficient attention and architecture-level improvements
  • •Build and benchmark optimized inference pipelines
  • •Evaluate speed, memory, and accuracy trade-offs
  • •Write clean, well-documented experimental code
  • •Share results and practical deployment recommendations
ML EngineerLife SciencesEarly TalentInternshipAmsterdamAIModel OptimizationInferencePythonDeep Learning
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