Applied ML Engineer: Open-Weight Model Verification

Lever, Inc.; Netherlands; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Healthcare

Flexible arrangements

Job summary

Lever, Inc. is seeking an Applied ML Engineer in the Netherlands to bridge ML research, experimentation, and production engineering. You will turn research ideas into rigorous experiments, build reproducible evaluation frameworks, and deliver production-grade tooling and APIs.

You will work across model evaluation, internals, inference infrastructure, backend systems, and user-facing experiences, ensuring rigorous verification as models evolve and are deployed at scale.

Qualifications

• Strong Python engineering skills with hands-on experience in PyTorch.
• Solid understanding of ML evaluation, including dataset design, baselines, metrics, calibration, false positives/negatives, and reproducibility.
• Ability to read ML research papers critically and implement methods from first principles.
• Professional software engineering experience beyond notebooks, including APIs, asynchronous jobs, databases, logging, testing, deployment, and documentation.
• Familiarity with open-weight models and practical understanding of modern LLM inference systems.
• Ability to work across backend and frontend boundaries with sufficient React/TypeScript knowledge to help make experiments and results understandable to users.

Responsibilities

• Reproduce and evaluate ML research methods using open-weight models.
• Design evaluation datasets, probes, scoring, baselines, calibration tests, and experiment harnesses.
• Work directly with model weights, logits, hidden states, activations, model APIs, and inference infrastructure as needed.
• Build and extend evaluation infrastructure covering runners, judges, persistence, orchestration, reporting, and reproducibility.
• Translate research workflows into product experiences including experiment config, execution, traces, and reports.
• Investigate how verification methods behave when models are modified (finetune, merge, quantize, distill, safety removal).
• Design controlled experiments to distinguish meaningful signals from artifacts and confounds.
• Produce clear technical reports separating evidence from interpretation and hypotheses.
• Deliver production-quality systems with APIs, asynchronous jobs, databases, observability, testing, deployment, and documentation.
• Contribute across research, experimentation, engineering, and product as priorities evolve.
• During six months, reproduce and document at least one proven model-provenance or verification method.

Skills

Python

PyTorch

Hugging Face Transformers

React

TypeScript

API development

Experimentation

Model provenance

Open-weight models

Inference systems

Tools

DSPy

LiteLLM

Temporal

Ray

vLLM

PostgreSQL/pgvector

Next.js

Job description

Lever, Inc. is seeking an Applied ML Engineer in the Netherlands to bridge ML research, experimentation, and production engineering. You will turn research ideas into rigorous experiments, build reproducible evaluation frameworks, and deliver production-grade tooling and APIs.

You will work across model evaluation, internals, inference infrastructure, backend systems, and user-facing experiences, ensuring rigorous verification as models evolve and are deployed at scale.