AI/ML Engineer

Randstad Enterprise

At Randstad Enterprise, the Engineering team is driven by a talent-centric culture. We
believe in bringing together passionate engineers who are enthusiastic about programming,
emerging technologies, and building impactful solutions. As part of Randstad, a global leader
in flexible work and human resources services, our team supports the digital transformation
of enterprise solutions across the organization. Randstad helps over two million candidates
find meaningful work annually, and our engineering team plays a crucial role in enabling this
mission through cutting-edge, scalable, and intuitive digital platforms.
the world around us
We live in extraordinary times. Technology, society, and the job market - they’re all rapidly
advancing, and opening up previously unimagined opportunities. With innovation driving the
world of work even faster, many of us are left wondering: how can I find a job that works
for me?

people at the heart of everything we do
We build modern, cloud-based solutions that power Randstad’s talent mobility, career
development, and workforce management offerings. With a strong focus on innovation, user
experience, and performance, our engineers contribute to the development of digital
products that deliver superior outcomes through expert insights, seamless user experiences,
and actionable analytics. Our work is recognized globally for its innovation and impact by
respected organizations such as Gartner, Bersin by Deloitte, Brandon Hall Group, and
Fortune magazine.

job purpose and responsibilities

purpose of the job
We are seeking an AI/ML Engineer who will play a key role in designing, developing, and
integrating intelligent AI solutions across our platform. The role involves working on a
variety of AI initiatives — from model experimentation and fine-tuning to building intelligent
agents and retrieval-augmented generation (RAG) systems. You will collaborate closely with
cross-functional teams to bring AI capabilities into production and ensure seamless
integration within our orchestration and application layers.

responsibilities
● Design, implement, and optimize AI agents leveraging frameworks such as
LangChain, LlamaIndex, or Haystack.
● Build and maintain RAG (Retrieval-Augmented Generation) pipelines combining LLMs,
embeddings, and vector search.
● Develop and fine-tune ML and NLP models for internal use cases, work with vector
databases and design efficient retrieval workflows.
● Collaborate with other product teams to integrate AI components into the
orchestration layer and business systems.
● Implement APIs and microservices that expose AI functionalities for broader system
use.
● Experience of context & prompt engineering, model evaluation, and response
optimization.
● Evaluate, benchmark, and monitor models using standard metrics and observability
tools.
● Stay up to date with the latest trends in AI frameworks, LLMs, and orchestration
technologies.

job requirements

education & experience
● 5+ years of experience in Product development and AI/ML or NLP solution
development.
● Strong coding proficiency in Python with practical experience in libraries like FastAPI,
Pandas, PyTorch, TensorFlow, or Transformers.
● Experience with LLM frameworks and strong understanding of retrieval systems,
embeddings, and vector databases.
● Hands-on experience with RESTful API development, microservices, and
containerized deployments (Docker/Kubernetes).
● Familiarity with cloud AI services such as GCP Vertex AI (preferred) or AWS Bedrock,
Azure OpenAI etc..
● Exposure to data pipelines, preprocessing, and production-grade model deployment.
good to have skills
● Experience building multi-agent systems or orchestrated AI workflows.
● Familiarity with MLOps, CI/CD, and model lifecycle management.
● Contributions to open-source AI/ML projects or custom toolkits.
● Understanding of monitoring, cost optimization, and performance tuning for AI
workloads.

soft skills
● Strong analytical and problem-solving skills.
● Clear communicator with the ability to collaborate across teams.
● Self-driven with a continuous learning mindset.
● Comfortable working in dynamic, fast-paced environments.