ML Engineer

We are looking for a Machine Learning Engineer who excels at turning AI research into scalable, production-grade reality. You will be responsible for the "heavy lifting" building the frameworks that allow our AI models to reason, the pipelines that feed them, and the infrastructure that ensures they are fast, ethical, and cost-efficient. You will bridge the gap between Data Science prototypes and enterprise-scale deployment.

Key Responsibilities

AI Model design and build: Work closely with data scientists and business to design and implement AI algorithms,
frameworks and architectures.

AI model Data Preprocessing: Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and load
data from various sources.

AI model Feature Engineering: Integrate structured and unstructured data from internal and external systems into
centralized data platforms.

Performance Tuning of AI/ models: Optimize data workflows and queries for performance, scalability, and
cost-efficiency. Building Agentic Systems: Developing intelligent AI agents that can reason, plan, and execute tasks
autonomously using LLMs and other tools.

LLM application Development: LLM fine-tuning adapting pretrained LLMs for specific tasks using techniques like
parameterefficient fine-tuning (PEFT) (e.g., LoRA, QLoRA). Implementing Retrieval-Augmented Generation
pipelines to enhance the knowledge and accuracy of LLMs. Utilizing vector databases for efficient storage and
retrieval of embeddings generated by LLMs. rafting effective prompts to elicit desired responses from LLMs.
Connecting LLMs and generative models with other systems and APIs to create comprehensive solutions.

Communicate findings: Collaborate extensively with data scientists, and business during model development and
deployment. Maintain updated documentation with details of all aspects of model development lifecycle.

Responsible AI: Build AI systems which are trustworthy and beneficial considering ethical principles such as
fairness, transparency, accountability, privacy and reliability. Implement quantifiable metrics detecting bias,
explainability and adherence to regulatory compliance.

Randstad Technologies is acting as an Employment Business in relation to this vacancy.