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.

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