MLOps Lead: End-to-End ML Infra & Team Mentor

Parser; España; Hybrid; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Triple-digit growth

Multicultural tech community

Competitive compensation

Hybrid working environment

Medical insurance

Job summary

Parser seeks a Tech Lead with a strong MLOps background to design, architect, and deliver ML infrastructure from backend to frontend. You will mentor a 5+ engineering team and drive MLOps best practices across model training, serving, and deployment.

You will collaborate with data scientists and engineers to deploy scalable ML systems and surface insights via React interfaces, in a hybrid, international environment (Spain remote or London hybrid).

Qualifications

• 10+ years of experience in Software, Data, or ML Engineering roles.
• Proven track record as a Tech Lead (managing teams 5+ people).
• Deep expertise in MLOps (model training pipelines, serving infrastructure, monitoring, CI/CD) and expert-level proficiency in Python.
• Strong hands-on experience with MLflow (mandatory) and solid experience with AWS and cloud-native architectures.
• Frontend proficiency in React, with the ability to deliver end-to-end product features.
• Hands-on experience with ETL/ELT pipelines, data engineering, and large-scale data processing.
• Experience with containerization (Docker) and scalable data systems (e.g., Spark, Kafka).
• Strong leadership presence, excellent communication, strategic thinking, and empathy with a hands-on execution mindset.
• Experience with AWS SageMaker or similar managed ML platforms.
• Background in safety-critical or regulated industries (aerospace, aviation, or similar).
• Familiarity with Kafka or event-driven architectures for real-time ML pipelines.

Responsibilities

• Own the end-to-end technical delivery of ML systems, from backend infrastructure to frontend integration.
• Lead architectural decisions across the ML stack, ensuring scalability, reliability, and alignment with business goals.
• Drive the ongoing migration from MLflow to AWS SageMaker, maintaining continuity and minimizing disruption.
• Define and enforce MLOps best practices across model training, serving, monitoring, and deployment.
• Design and maintain scalable ML infrastructure supporting batch and real-time environments, alongside robust ETL/ELT pipelines.
• Develop and maintain React-based frontend interfaces that surface ML insights to operational and engineering stakeholders.
• Lead, mentor, and provide structured feedback to a team of 5+ engineers, fostering a high-performance culture.
• Collaborate with cross-functional stakeholders across engineering, data science, and operations while proactively addressing technical blockers.

Skills

MLOps

Python

AWS

React

Docker

Data engineering

Spark

Kafka

CI/CD

Leadership

Tools

MLflow

AWS SageMaker

Job description

Parser seeks a Tech Lead with a strong MLOps background to design, architect, and deliver ML infrastructure from backend to frontend. You will mentor a 5+ engineering team and drive MLOps best practices across model training, serving, and deployment.

You will collaborate with data scientists and engineers to deploy scalable ML systems and surface insights via React interfaces, in a hybrid, international environment (Spain remote or London hybrid).