Machine Learning Engineer

JJob Title – Machine Learning Engineer
Type – Contract
Location – Berlin, Germany
Duration – 12 Months (Extendable)

Our client is seeking a Machine Learning Engineer to join our dynamic, cross-functional group. In addition to crafting comprehensive solutions for developing, deploying, and optimising machine learning models.

You will join a team that spearheads the foundational infrastructure and resources critical for the success of machine learning initiatives. They facilitate seamless collaboration among machine learning researchers, data scientists, and software engineers, empowering them to innovate and implement cutting-edge ML systems both in controlled environments and real-world settings.

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
Strong knowledge of relevant ML tools (PyTorch, TensorFlow, Keras, SageMaker ecosystem)
Experience in scripting for automation (e.g. Python) and advanced SQL skills.
Experience using Cloud Storage and Computing technologies (AWS Redshift, EC2, S3, SageMaker, Lambda)
3+ years of experience in Analytics, and Data Engineering (DE) experience with evidence of increasing responsibility
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 modeling processes, use of strong baselines, ability to accurately determine cause and effect relations

Preferred Qualifications
Master’s degree in statistics, data science, computer science, or an equivalent quantitative field
Experience with training/deploying deep learning/ML 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