Sr Engineer, ML, SMAI

Description

The company makes memory and storage products. This role sits in a team that applies machine learning and generative AI to company data and products.

The work runs from building data pipelines through to monitoring models in production.

Responsibilities

• Build and maintain data pipelines that feed model training and deployment, on a dependable and scalable setup.
• Mine existing company data sets for patterns, trends and insights that can improve model development.
• Design, build and refine machine learning models for specific business problems and to improve product features.
• Work with others on data preprocessing and feature design to raise the quality of model inputs.
• Shape data structures in Snowflake, GCP and Azure so that AI and ML solutions can run on them.
• Write custom software components and analytics applications.
• Plan and carry out how models move into production.
• Choose models that balance performance against compute cost.
• Set up and run monitoring that tracks deployed models and guides ongoing improvement.
• Build and maintain CI/CD pipelines for machine learning solutions in the cloud.
• Work with product and engineering to find where generative AI can be added to projects and the platform.
• With the product team, draft a practical roadmap for adopting generative AI technologies, paradigms and frameworks, in line with organisational best practice.
• Build enterprise-grade applications on generative AI, including LLMs, multimodal architectures and prompt engineering.
• Fine-tune pre-trained models on domain datasets, add retrieval-augmented generation (RAG) to ground answers in company knowledge, and build agentic systems that run autonomous workflows and connect to domain APIs.

Requirements

• A Master's in computer science, machine learning, data science, statistics, industrial engineering or a closely related discipline, with 1 year of experience in this job or a related occupation; or a Bachelor's in one of those areas with 3 years of experience in this job or a related occupation.
• Experience delivering complete enterprise ML systems hosted in the cloud.
• Understanding of generative AI, reinforcement learning and deep learning, plus classic regression and classification methods.
• Event-driven pipelines built with Pub/Sub, Solace or Kafka.
• Docker and Kubernetes.
• ETL or ELT pipelines built with Kubeflow, Dataflow or Airflow.
• SQL.
• Ability to develop RESTful APIs that serve ML models.
• Familiarity with large language models, multimodal designs, prompt design and agent-based systems.
• Fine-tuning of domain-tailored models and retrieval-augmented generation (RAG).
• Experience with large volumes of semiconductor manufacturing data.

Conditions

The posting links to information on right to work.

Candidates never pay recruitment fees to the company, and it bans child labour under all applicable laws and standards.

Benefits

• Medical, dental and vision plans available in all locations, so you can choose what suits your family.
• Income protection if illness or injury keeps you from working.
• Paid family leave.
• Paid time off and paid holidays.