- Data Exploration and Analysis: Analyse large, complex datasets to uncover meaningful patterns, trends, and insights. Collaborate with stakeholders to understand business requirements and formulate data-driven solutions.
- Data Collection and Preprocessing : Design, develop and implement data preprocessing pipelines to collect, ingest, transform and serve data from multiple sources into a single storage solution to enable AI and ML-backed data products.
- Modelling: Compose frameworks to support the deployment, testing, monitoring and governance of AI/ML models.
- Evaluation and Optimization: Monitor and troubleshoot pipelines, ensuring continuous data flows from source applications to models.
- Deployment and Integration : Collaborate with AI engineers and software teams to integrate AI and machine learning solutions into Thrive products.
- Documentation and Communication: Document the AI and data workflow, including data collection, preprocessing, model development, and deployment. Communicate findings and results to both technical and non-technical stakeholders.
- AI Upskilling : Share the knowledge and expertise with the wider product development team, providing training sessions and resources to upskill team members in AI technologies.
- Oversee Thrives emerging data technologies.
- 4+ years of experience in data engineering with a focus on AI and machine learning projects.
- Strong proficiency in Python, Java, and SQL
- Familiarity interacting with AI frameworks including PyTorch and TensorFlow and AI libraries such as Huggingface and Scikit-Learn.
- Knowledge of Graph Databases , ontologies as well as non relational databases .
- Solid understanding of data structures, database systems, data modelling, and data warehousing concepts.
- Experience with data visualisation and data communications.
- Proficiency with MongoDB and cloud platforms (AWS)data operations and database technologies.
- Knowledge of AI Data governance and protocols and standards.
- Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
- Proven ability to work collaboratively in cross-functional teams.
- Strong problem-solving skills and lead initiatives independently.
- Ability to think creatively and propose innovative solutions.
- Ability to adapt to evolving technology and business requirements.
- Prior exposure to workplace learning technology or related fields and an understanding of the unique challenges and opportunities in this domain.
- Experience working within a R&D or innovation-focused team, contributing to the exploration of unconventional ideas and breakthrough innovations.
- Experience with Large Language Models (LLMs) and LLM APIs.
Data & Knowledge Engineer AI/Machine Learning · Hybrid Remote - United Kingdom - Thrive Learning Limited
Description
About this role What you'll be doing
At Thrive, we foster a culture of innovation and creativity, revolutionising workplace learning technology. As an Engineer on the ThriveAI team, you will be an integral part of a dynamic and innovative group, contributing to the advancement of breakthrough AI solutions in the workplace learning technology sector. Operating within a high-autonomy environment, ThriveAI will drive creativity, speed up AI innovation, and implement flexible approaches to project development.
The ideal candidate will have a strong background in data engineering and analysis. You will be responsible for designing, implementing, and maintaining scalable data solutions that support data ingestion, processing, and analysis.
You will collaborate closely with AI engineers and software developers to build robust data pipelines and infrastructure for our AI-powered software platform. You will collaborate with cross-functional teams to understand business requirements, gather and pre-process data, and develop scalable and efficient AI solutions.