Description:

Shape.Construction is a company focused on digitizing the construction industry, which is one of the least digitized yet largest industries globally.
The company aims to improve construction project delivery through a suite of construction management software products.
The MLOps Engineer role requires a self-sufficient individual with hands-on experience in deploying Large Language Models (LLMs) into production.
The engineer will work autonomously while collaborating with product and engineering teams to ensure seamless implementation and optimization of LLMs.
Key objectives include effective deployment of LLMs, optimizing their performance, and integrating them into applications.
Responsibilities include collaborating on scope definition, overseeing the ML project lifecycle, optimizing LLMs for inference, enhancing applications with LLMs, and collaborating with the Site Reliability Engineering (SRE) team.
The ideal candidate should possess deep technical expertise, be an independent problem-solver, and have a commitment to continuous learning.

Requirements:

Extensive experience in deploying and managing Large Language Models, including fine-tuning and integration.
Strong skills in machine learning frameworks, cloud computing, and interacting with external applications.
Ability to tackle challenges autonomously and apply innovative solutions to complex problems.
Commitment to staying updated on the latest developments in LLMs and MLOps.
Nice to have skills include advanced model optimization techniques, a collaborative approach for seamless integration, and active participation in relevant tech communities.

Competitive salary based on location and capability.
Paid annual leave of 20 days plus statutory bank holidays.
In-house coaching sessions and a discretionary bonus scheme for all team members.
A 4-day work week, promoting work-life balance.
Flexibility in work hours, allowing employees to manage personal commitments without needing permission.
Opportunities for personal growth and development, with a focus on providing extensive learning experiences.
A meritocratic environment where fast progression is encouraged, and employees are surrounded by talented individuals.