AI Integration Engineer

• Standardization: Establish and enforce best practices for machine learning model development, testing, and deployment.
• Data Integration: Design and implement robust data integration pipelines to ensure seamless access to diverse data sources.
• Feature Store: Developing and maintaining a feature store for data features.
• EDA (Exploratory Data Analysis): Implementing and maintaining tools for exploratory data analysis.
• Enterprise VectorDB and Search Engine: Building and maintaining enterprise-level vector databases and search engines.
• API Interfaces and Gateway Integrations: Developing and maintaining API interfaces and gateways for seamless integrations.
• ETL Templates: Creating and maintaining templates for Extract, Transform, Load (ETL) processes.
• GDP Integration: Ensuring integration with Global data platform to feed data into AI feature stores.
• External Data Sourcing: Managing the sourcing and integration of external data.
• IDAM Integrations: Implementing and maintaining Identity and Access Management (IDAM) integrations.
• Onboarding Application for Users: Developing and maintaining applications for user onboarding, financial operations (FinOps), IT asset management (ITAM), and process integrations.
• Collaboration: Work closely with data scientists, software engineers, and platform engineers to deliver high-quality AI solutions.
• Innovation: Stay abreast of the latest advancements in AI and machine learning, and apply this knowledge to improve our platform and processes.
• Mentorship: Provide technical guidance and mentorship to junior engineers and team members.

• Experience: 3-5 years of experience in AI and machine learning engineering, with a proven track record of delivering complex AI projects.
• Technical Expertise: Strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch), MLOps tools (e.g., MLflow, Kubeflow), and cloud platforms and infrastructure as code (e.g., AWS, Azure).
• Programming Skills: Proficiency in programming languages such as Python, Java, or C++.
• Data Engineering: Strong skills in data engineering, including data integration, ETL processes, and working with large datasets.
• Problem-Solving: Excellent analytical and problem-solving skills, with the ability to think critically and creatively.
• Communication: Strong interpersonal and communication skills, with the ability to work effectively in a collaborative team environment.

• Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do
• Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well
• Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term

• Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations.
• Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum.
• Flexible working options based around home and office locations, with flexible working patterns.
• Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits
• A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning.
• Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.

Standard Chartered