AI/ML Engineer

For a challenging project with one of our clients, a global leader in audio and media streaming, we are looking to expand the current teams. Our client is a leading global technology company that builds a large-scale digital platform serving millions of users daily. The company operates in a data-first culture, leveraging user interaction data and content metadata to drive innovation across its products, including personalized recommendations, content ranking, search, and user behavior modeling.

Project 1: AI Engineer

Responsibilities:

• Design, select and wire frameworks; enforce latency, cost, and safety budgets.
• Build automated unit, integration and tests for agent flows using AgentBench, LangChain-Bench, OpenAI Evals, RAGAS, and custom simulators; create CI gates that catch regression in reasoning, tool usage, and hallucination rates
• Stand up high-throughput RAG pipelines (BM25 + embeddings + re-rank); tune vector DBs (Qdrant, Weaviate, Milvus, pgvector)
• Ship microservices (Python/FastAPI), containerize with Docker, deploy to K8S or serverless; instrument tracing and observability.

Requirements:

• 5+ years building backend or data systems in production (3+ years Python and Java);
• Work experience with LLM-powered features (chatbots, copilots, summarizers, etc.).
• Hands-on with LangChain, OpenAI Agents SDK, AutoGen, or CrewAI.
• Experience writing automated tests/evals for LLM or agent workflows and integrating them into CI pipelines.
• Solid grasp of RAG, vector search, chunking strategies, embeddings, and evaluation Methodology.
• Comfort with SQL/NoSQL, containerization, and CI/CD.
• Familiarity with cloud infra (GCP) and Declarative Infra practices.
• Experience with TensorFlow, pyTorch, and/or other scalable Machine learning frameworks Experience with building data pipelines and getting the data you need to build and evaluate your models, using tools like Apache Beam / Spark.

Nice to have

• Orchestrated multi-agent systems (hierarchical/cooperative).
• Experience designing synthetic user simulators or adversarial evaluation suites.
• Knowledge of guardrails and safe-completion patterns.
• Event-driven architectures (Kafka, Pub/Sub) or real-time streaming.
• OSS contributions to agent, RAG, or eval libraries.

Project 2: Machine Learning Engineer

The focus is on building reliable ML systems and infrastructure to support personalized and scalable product features—running on cloud-native architectures with cutting-edge tools and frameworks.

Activities

• Design, develop, and deploy machine learning models that are production-ready and scalable.
• Collaborate with product, engineering, and data teams to identify opportunities for ML-driven improvements.
• Build and maintain robust data pipelines to support ML experimentation, training, and inference.
• Implement experiments and A/B tests to evaluate model performance and feature impact.
• Contribute to technical designs, architecture discussions, and system improvements for ML infrastructure.

Responsibilities

• Apply machine learning techniques to real-world problems across domains such as personalization, content discovery, and predictive analytics.
• Build, deploy, and monitor ML models in a production environment using Python and modern ML frameworks such as TensorFlow or PyTorch.
• Architect and implement end-to-end data pipelines using tools like Apache Beam, Spark, or Dataflow.
• Work with cloud platforms (GCP or AWS) to scale training, evaluation, and model serving workflows.
• Ensure model reproducibility, performance monitoring, and retraining mechanisms.
• Follow agile development practices and collaborate in cross-functional teams to deliver data-driven features.

Requirements

• Professional experience in applied machine learning, ideally in a product-focused environment.
• Proficiency in Python (required), with working knowledge of Scala, Java, C++, or SQL.
• Experience with cloud platforms like Google Cloud Platform (GCP) or Amazon Web Services (AWS).
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
• Proven ability to design and build scalable data pipelines using Apache Beam, Spark, or Dataflow.
• Familiarity with agile development, data-driven decision making, and experiment-driven iteration.

Nice to Have

• Experience with real-time or streaming ML applications.
• Exposure to large-scale experimentation platforms and A/B testing tools.
• Familiarity with ML model versioning, CI/CD for ML, and model performance monitoring tools.
• Previous work in personalization, recommendation systems, or content-based filtering.
• Contributions to open-source ML tools or participation in academic/industry ML research.

Benefits

• Attractive salary package according to your experience and seniority bonus;
• The 13th salary depending on company’s performance;
• Bonus for internal recommendations;
• Meal tickets;
• Private health insurance, including dental services and psychological consultations;
• Flexible working hours (core-hours system);
• Access to over 600 sports centers in the 7Card network;
• Online language courses: English and French;
• Access to the e-learning platform;
• Access to technical training programs / workshops, as well as other technical events (both as a participant and as a speaker);
• Development opportunities through involvement in internship & mentoring programs;
• Access to soft-skills programs and workshops;
• Access to various internal events and team-buildings;
• Access to international opportunities for career development with challenging and exciting projects in a dynamic international working environment;
• Paid days off offered for involvement in volunteering activities and for bank holidays occasion.

Kindly note that only suitable candidates will be contacted.

Randstad Digital Romania has offices in Sibiu and Bucharest, and works with clients on a vast range of projects across diverse industries, among which Automotive, Heavy industry, Transportation, Finance, Services, Security & Biometrics, Tourism, Platforms & IoT, Telecom & Mobile and more.

At Randstad Digital Romania, we aim to be the specialized global delivery center to support our customers in transforming complex projects into reality, leveraging our expertise to create solutions that improve the customers’ experience.

How do we really make the difference? It’s all about our team!

Randstad Digital Romania is founded on the excellence of our engineers and we consider our crew to be our most valuable asset. Our Agile software team consists of over 400 highly skilled specialists spread all over the country. We rely our success on our talented, determined and creative colleagues.

With our talent-first approach, we are committed to providing challenging opportunities and supporting our talents' growth and development. Our culture encourages our people to innovate, challenge, explore and grow!

We are dedicated to providing the best features based on our partners' needs, to integrate and manage the right mix of services for a hybrid customized solution. Our goal is to keep the quality of our expertise at a top level and keep our partners’ costs in the right balance.