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
- Partnering with stakeholders to scope problems and identify the right solution - whether leveraging existing AI tools or building custom workflows & solutions.
- Designing and implementing agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP-first stack.
- Building and maintaining production ML pipelines and services for non-GenAI use cases e.g. recommender systems, customer segmentation models, marketing optimisation modules, leveraging supervised, unsupervised and/or econometric modelling approaches.
- Developing APIs and microservices for AI/ML solutions, ensuring security, scalability, and observability.
- Implementing CI/CD for ML services, writing infrastructure as code, and monitoring for model/data drift and performance.
- Establishing robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and compliance with privacy regulations.
- Driving and evangelizing best practices, reusable templates, and documentation to scale AI/ML delivery across the business.
- Collaborating with data engineers, data scientists, front & back-end engineers, product managers, legal & infosec colleagues to deliver impactful solutions end-to-end.
- Line management of AI/ML Engineers setting goals, developing skills, and mentoring for high performance
Requirements
- Strong Python engineering skills FastAPI, testing, typing and experience with cloud-native development GCP preferred.
- Hands-on experience with GCP Vertex AI model endpoints, pipelines, embeddings, vector search or equivalent cloud-native AI/ML platforms e.g. AWS SageMaker, Azure ML and agent orchestration frameworks e.g. LangChain, LangGraph.
- Solid understanding of MLOps CI/CD, IaC Terraform, experiment tracking, model registry, and monitoring.
- Proven experience deploying and operating ML systems in production batch and real-time.
- Familiarity with RAG architectures, prompt engineering, and evaluation techniques.
- Strong grasp of security, privacy, and governance principles IAM, secrets, PII handling.
- Proven experience operating as a player-coach, hands-on engineering manager who both builds and leads.
- Demonstrable ability to weigh up build/buy/configure decisions in the LLM space.
- Bachelor’s or Master’s degree in Computer Science/Engineering/related field, or demonstrable relevant experience.
Benefits
- 25 days holiday plus bank holidays with an additional day to celebrate your birthday
- Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey
- Financial security and planning with our pension and life assurance for all
- Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues
- Bring your furry friend to work with you on our allocated dog friendly days and spaces
- Generous product discount and gifting!
Job title
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NO
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