Machine Learning Engineer

Modjo

. Design, build, and optimize the agentic stack powering conversational and autonomous agents .

Posted 9/18/2026full-timeParis • FranceJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Machine Learning Engineering and Data Science, with a strong focus on Python programming, LLMs, and agentic systems. Capable of architecting and optimizing ML infrastructure while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Machine Learning EngineeringPython ProgrammingLarge Language Models (LLMs)Agentic SystemsModel Evaluation Methods

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData Science Best PracticesModel TypesPrompt DesignCost/Performance Trade-offsObservabilityLoad BalancingScaling PatternsEvaluation PipelinesNLP Concepts

Soft Skills

Strong OwnershipCommunication SkillsIntellectual Curiosity

Tools & Technologies

LangChainLangGraphMCP (Model Context Protocol)DeepEvalFastAPIUvicorn

Industry Keywords

Conversational AgentsAutonomous AgentsModel OrchestrationMonitoringLogging

Tech Stack

Tools & technologies

JavaPythonVue.js

About the role

Key responsibilities & impact

Design, build, and optimize the agentic stack powering conversational and autonomous agents
Architect and maintain end-to-end LLM features, including 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 establish scalable, observable, and automated infrastructure around ML services
Work with Product Managers to assess feasibility, refine specifications, and reliably deliver ML features
Contribute to technical strategy, including model and tool selection, architectural decisions, and the agentic platform roadmap
Stay current 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 foundations in ML, including model types, data science best practices, and evaluation methods
Strong understanding 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, dig deeply into topics, and form your own perspective
Strong ownership and communication skills: you do not remain blocked, ask the right questions, and move things forward

Benefits

Comp & perks

2 remote days per week and up to 9–11 additional leave days per year
Meal vouchers provided through a Swile card
Public transportation costs covered (Navigo pass) or a sustainable mobility allowance of up to €42/month
Gym membership through Gymlib and Alan Blue health insurance
Access to Pluxee, the employee benefits platform
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, at full pay