PA
PartSpaceMachine Learning Engineer – m/f/d
Machine Learning Engineer responsible for optimizing AI pipelines at Easy2Parts. Join a growing team to revolutionize component sourcing with AI technology.
About the role
- Design, implement, and optimize sophisticated Generative AI and Machine Learning models and systems
- Serve as a thought leader driving innovative vision across products and platforms
- Lead the full software development lifecycle (design, testing, deployment, operations)
- Develop high-performance, production-ready ML code and extend ML libraries/frameworks
- Collaborate with engineers and scientists to accelerate model development, validation, and experimentation
- Integrate models and algorithms into production systems at scale
- Occasionally travel to customer sites as needed
Requirements
- Serve as a thought leader and forward thinker—drive innovative vision across products and platforms
- Lead the full software development lifecycle (design, testing, deployment, and operations)
- Guide technical discussions and strategy; participate in design reviews, code reviews, and implementation
- Develop high-performance, production-ready ML code for next-generation real-time ML platforms
- Extend existing ML libraries and frameworks
- Collaborate closely with engineers and scientists to accelerate model development, validation, and experimentation cycles
- Integrate models and algorithms into production systems at scale
- Degree in Computer Science, Mathematics, or a related field
- 8+ years of full SDLC experience (design, coding, reviews, testing, deployment, operations)
- 5+ years of experience building and deploying end-to-end ML solutions or platforms in production
- Hands-on experience developing Generative AI solutions (RAG, AI Agents, LLM fine-tuning) in production
- Experience with large-scale distributed systems on cloud platforms (AWS, Azure, GCP)
- Strong ability to solve complex, ambiguous problems
- Preferred: MS/PhD in Computer Science, Machine Learning, or a related discipline
- Preferred: Experience with Graph ML and Graph technologies (e.g., GNNs, GraphRAG)
- Preferred: Experience with distributed Big Data technologies (e.g., Spark, Flink, Kafka, PySpark, Lakehouse, Druid, Hudi, Glue)
Benefits
- Collaborative and inclusive work environment
- Remote work within Europe with occasional travel to customer sites
Job title
Job type
Experience level
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Not specified
Degree requirement
Tech skills
Location requirements
NO
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