FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Machine Learning Engineering and Data Science, with a strong focus on building and optimizing ML infrastructure, including LLM features and agentic systems. Proficient in Python and familiar with various technologies and methodologies that enhance model performance and reliability.
Highest-signal resume keywords
Machine Learning EngineeringPython ProgrammingLarge Language Models (LLMs)Agentic SystemsModel Evaluation Methods
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning FundamentalsModel OrchestrationData Science Best PracticesPrompt DesignCost/Performance Trade-offsObservabilityLoad BalancingScaling PatternsDeployment WorkflowsNLP Concepts
Soft Skills
Strong OwnershipCommunication SkillsIntellectual Curiosity
Tools & Technologies
LangChainLangGraphMCP (Model Context Protocol)DeepEvalFastAPIUvicorn
Industry Keywords
Conversational AgentsAutonomous AgentsEvaluation PipelinesDeterministic SystemsNon-Deterministic Systems
Tech Stack
Tools & technologiesJavaPythonVue.js
About the role
Key responsibilities & impact- Design, build, and optimize the agentic stack powering conversational and autonomous agents, with a focus on reliability, scalability, and low latency in production
- Architect and maintain end-to-end LLM features: model orchestration, routing, monitoring, logging, and evaluation
- Develop and improve ML infrastructure, including observability, load balancing, scaling patterns, and deployment workflows
- Build robust datasets and evaluation pipelines for deterministic systems (ASR) and non-deterministic systems (LLMs and agents)
- Collaborate with Software Engineers to build scalable, observable, and automated infrastructure around ML services
- Work with Product Managers to assess feasibility, refine specifications, and reliably deliver ML features
- Contribute to the technical strategy, including model and tooling selection, architectural decisions, and the agentic platform roadmap
- Stay up to date with research, frameworks, and open-source developments in LLMs, agentic systems, and evaluation methodologies
Requirements
What you’ll need- 2 to 5 years of experience in ML Engineering or Data Science
- Strong proficiency in Python; experience with lower-level languages such as Java or C is a plus. A purely scripting-focused profile will not be sufficient
- Solid understanding of ML fundamentals, including model types, data science best practices, and evaluation methods
- Strong command of LLMs, including prompt design, evaluation, and cost/performance trade-offs
- Experience with agentic systems, including tool execution, workflows, memory architectures, and LangChain, LangGraph, or equivalent technologies
- Familiarity with MCP (Model Context Protocol), DeepEval, FastAPI, and Uvicorn
- Understanding of NLP concepts, including transcription, embeddings, and language understanding
- Genuine intellectual curiosity: you stay informed, explore topics in depth, and develop your own perspectives
- Strong ownership and communication skills: you do not remain blocked, ask the right questions, and keep moving forward
Benefits
Comp & perks- 2 remote-working days per week and 9 to 11 additional paid leave days (RTT) per year
- Meal vouchers provided via a Swile card
- Transportation covered through the Navigo Pass, or a sustainable mobility allowance of up to €42 per month
- Gym membership through Gymlib and Alan Blue health insurance
- Access to Pluxee, the employee benefits platform provided by the works council
- Structured onboarding and supported professional development from day one
- Regular performance reviews to support your growth
- Parental Leave Soft Landing: upon returning from maternity or paternity leave, one day off per week during the first four weeks, with full pay