Senior Machine Learning Engineer

The job at a glance:

The three teams in our streamlined squad are currently working on several LLM-based use-cases to serve jobseekers better fitting jobs and recruiters better fitting talents via semantic search. We are using inhouse-tuned LLMs that we deploy on AWS together with Vector DBs to support retrieval.

This exciting role will be about designing, planning and implementing systems based on LLM-inference, including advanced RAG. To this end you will collaborate tightly between Data Scientists, Machine Learning and Big Data Engineers, as well as Cloud Software Engineers and DevOps in a Scrum environment. You can support streamlining deployment and establish best practices in MLOps for large models to build a better future where a new job is just a click away.

Your responsibilities:

Your role as Senior Machine Learning Engineer will encompass implementating and productionising ML-based services using Sagemaker, but also streamlining delivery of machine learning products in general. You will be a key figure in our team to establish and utilize best practices for MLOps, IaC and CI/CD best practices to increase efficiency in deployment, scalability and management of resources in LLM-based pipelines.

This role allows for direct impact on the experience of jobseekers and recruiters! Leverage your experience to build a framework for semantically matching talents to job profiles across the globe with a strong sense of ownership and a holistic understanding of ML-based systems. We are looking for a person who enjoys extensive collaboration, who is willing to learn and contribute to technical discussion, bringing bleeding edge technology and knowledge to our search and recommender solutions.

Showcase your track record of elevating processes, standards, and ways of working, and your background in coaching and mentoring more junior engineers. To thrive in our fast-paced environment you will contribute to our Chapters in Data Science and Machine Learning Engineering, able to work across teams to help everyone work together effectively. Demonstrate your growth mindset and systematic approach to problem-solving, as well as your experience in navigating the dynamics of an Agile environment. Fluent in English? Fantastic!

Requirements

Your skills and qualifications:

• 5+ years of experience in Machine Learning Engineering, Data Engineering, or a related field
• Proficiency in production-level Python (Clean, SOLID) and industry experience with Amazon Sagemaker deployment of LLMs
• Experience with LLM-related packages, such as PyTorch, Transformers etc.
• Experience with IaC (Terraform), CI/CD, and test automation best practices
• Bachelor's degree in Computer Science or a related field; Master's degree is preferred