MLE L5 – AR Veritas

Project overview

Job Title – Machine Learning Engineer

Type – Contract

Location – Berlin, Germany (Remote)

Duration – 12 Months (Extendable)

Key job responsibilities

Work directly with the science and engineering teams to build systems for provably correct AI reasoning with LLMs

Build a system that generates automatically annotated data with an existing reasoning engine (AI planner, simulator, proof planner)

Handle large-scale data annotations and automate pre/post-processing pipelines, including data lake management in S3 and compute resources.

Build pipelines for training and fine-tuning LLMs with data

Build an experimental test harness able to run experiments in multiple domains with the minimum of adaptation.

Take part in scrum development in an international setting (Berlin, Boston, and Seattle)

Basic qualifications

3+ years of experience with training/deploying deep learning/ML models (3+ years)

Strong knowledge of relevant ML tools (PyTorch, HuggingFace, SageMaker, vLLM )

Experience in scripting for automation (e.g. Python)

Experience using Cloud Storage and Computing technologies (AWS, EC2, S3, SageMaker, Lambda)

Capacity to independently lead and execute end-to-end insight projects, including asking the right questions, managing complex datasets, iterating on findings, and providing strategic guidance and recommendations to an engineering team

Ability to develop experimental and analytic plans for data modelling processes, use of strong baselines, ability to accurately determine cause and effect relations

Preferred Qualifications

Master’s degree in computer science

Experience with Reinforcement Learning and/or transformer-based models

Experience with theory and practice of design of experiments and statistical analysis of results

Experience programming to extract, transform, and clean large (multi-TB) data sets

Preferably located in or open to moving to Berlin

Project details

• Start: flexible
• Location: Berlin, GB