Senior Applied ML Engineer

Nix; España; Hybrid; EUR 85,000 - 120,000; Full time

Benefits offered by this job

Flexible working format

Competitive salary

Personalized career growth

Education reimbursement

Memorable anniversary presents

Corporate events

Job summary

N-iX is seeking a Senior Applied ML Engineer to support the Data Licensing team, building and productionising ML models to enrich metadata for data licensing opportunities.

You will collaborate with senior scientists and data engineers to evaluate models, deploy inference components, and ensure scalability across CPU and GPU environments on AWS and GCP. Strong Python and cross-cloud experience are essential; excellent communication is a must.

Qualifications

• 6+ years of experience in applied ML, ML engineering, data science or software engineering.
• Experience evaluating pretrained or third-party ML models with quality metrics and thresholds.
• Strong Python software engineering skills, including testing, packaging and dependency management.
• Hands-on proficiency with ML libraries such as PyTorch, TensorFlow, scikit-learn or Hugging Face.
• Experience deploying ML inference systems on CPU and GPU in AWS and GCP.
• Experience troubleshooting model execution in distributed, cross-cloud workflows.
• Clear communication skills and ability to build consensus with technical and commercial partners.

Responsibilities

• Partner with senior leaders to implement model-evaluation and productionisation standards.
• Evaluate candidate models on representative content using quality measures and thresholds.
• Develop Python inference components that conform to engineering frameworks and contracts.
• Validate outputs, estimate inference cost and throughput for backfills.
• Work with data engineers to move enrichment components to corpus-scale execution.
• Assess licensing, data-handling constraints and provenance for reproducibility.

Skills

Applied ML

Python

ML inference

Model evaluation

Cloud platforms (AWS/GCP)

Communication

Testing & packaging

Tools

PyTorch

TensorFlow

scikit-learn

Hugging Face

Job description

N-iX is looking for a Senior Applied ML Engineer to support our client's Data Licensing team, which develops training datasets for frontier AI labs. You will evaluate and productionise existing ML models and services to deliver customer-requested metadata enrichment for data licensing opportunities, supporting the next generation of AI applications.

Responsibilities:

• Partner with the Principal Data Scientist and Principal Data Engineers, senior technical leaders and data scientists to implement and evolve model-evaluation and productionisation standards; independently own assigned enrichment workflows from evaluation through production delivery.
• Evaluate candidate models on representative content, using appropriate quality measures and threshold analysis to support selection and release decisions.
• Develop tested, maintainable Python inference components that conform to shared engineering frameworks, metadata contracts and deployment standards.
• Support ad-hoc metadata backfills by validating model outputs, estimating inference cost and throughput, and resolving model-specific processing issues.
• Work with data engineers to move enrichment components from representative evaluation to reliable corpus-scale execution.
• Assess model licensing, data-handling constraints and provenance requirements, ensuring enrichment outputs are reproducible and suitable for commercial use

Requirements:

• 6+ years of experience in applied ML, ML engineering, data science or software engineering, including hands‑on experience delivering production ML inference systems.
• Experience evaluating pretrained or third‑party ML models, defining appropriate quality metrics and operating thresholds, while balancing model quality against inference cost, throughput and operational complexity.
• Strong Python software engineering skills, including testing, packaging and dependency management.
• Hands‑on proficiency with ML libraries and frameworks such as PyTorch, TensorFlow, scikit‑learn or Hugging Face.
• Experience developing, deploying and maintaining high‑performing, resilient and scalable ML inference systems across CPU and GPU environments in both AWS and GCP
• Experience troubleshooting and optimising model execution in distributed, cross-cloud workflows.
• Clear communication skills and experience building consensus with technical and commercial partners.

Nice to have:

• Model tracking and lifecycle tooling such as MLflow.
• Managed ML and batch‑inference platforms such as SageMaker, Vertex AI or Databricks.
• Experience evaluating models for image, video or audio content.
• Experience with Snowflake, DBT or Clickhouse

We offer*:

• Flexible working format - remote, office‑based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centres of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location‑specific benefits

*not applicable for freelancers