About Rocket Lawyer
We believe everyone deserves access to affordable and simple legal services. Founded in 2008, Rocket Lawyer is the largest and most widely used online legal service platform in the world. With offices in North America, South America, and Europe, Rocket Lawyer has helped over 30 million people create over 50 million legal documents, and get their legal questions answered.
We are in a unique position to enhance and expand the Rocket Lawyer platform to a scale never seen before in the company’s history, to capture audiences worldwide. We are expanding our team to take on this challenge!
About your role
We are seeking a highly skilled and passionate Data Engineer to join our growing team focused on building and deploying cutting-edge AI/ML solutions. As a Data Engineer, you will play a crucial role in designing, building, and maintaining the data infrastructure powering the AI models for Rocket Copilot, our AI legal assistant. You will work closely with Machine Learning Engineers, Data Scientists, and Product Managers to ensure the availability of high-quality data for training, fine-tuning, and evaluating generative models. This role requires a strong understanding of data engineering principles, experience with large-scale data processing, and a passion for pushing the boundaries of AI.
We value a fun, collaborative, team-oriented work environment, where we celebrate our accomplishments.
How you will make a difference day to day
- Design, develop, and maintain robust, scalable, and efficient data pipelines for ingesting, processing, transforming, and storing large datasets used for training and evaluating generative AI models.
- Perform data cleaning, normalization, transformation, and feature engineering to prepare data for model training. This includes handling unstructured data like text, images, and audio.
- Build and manage the data infrastructure, including data lakes, data warehouses, and databases, optimized for AI workloads.
- Implement data quality checks and monitoring systems to ensure data accuracy, completeness, and consistency.
- Contribute to the development and implementation of MLOps best practices for data management and model deployment.
- Work with GCP and Snowflake and their data and AI offering.
- Optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness.
What you’ll need
- 5+ years of python and SQL experience.
- 3+ experience of leveraging technologies such as Airflow, Apache Spark.
- Experience working with large language models (LLMs), diffusion models, or other generative models.
- Experience with MLOps tools and practices.
- Strong understanding of data architectures and patterns.
- Experience with containerization technologies (e.g., Docker, Kubernetes).
- Contributions to open-source projects.
- Strong understanding of data architectures and patterns.
- Experience in DataOps implementation and support.
- Experience in MLOps implementation and support.
- Experience in building and supporting AI/ML platform.
Benefits & Perks
- 25 days holiday plus banks holidays
- 10 days sick pay
- 5% employer contribution Pension and 3% employee, 8% in total
- Private health & dental insurance (after 2 years service)
- Cycle to work
- Flexi time
- Discounted gympass
- Employee referral program
- Free Rocket Lawyer account with online access to an extensive legal documents library and brilliant licensed attorneys at discounted rates
Interview Process:
- Recruiter Phone Screen
- Role Assessment(s)
- Hiring Manager Interview
- Panel Interviews
- Final Interview
We welcome applications from candidates who may require future sponsorship after six months (e.g., those currently on student/graduate visas). However, due to processing timelines, we are unable to consider applicants needing immediate sponsorship at this time. Please note that we only provide sponsorship for engineering roles.
Actual compensation packages are determined by various factors unique to each candidate, including but not limited to skill set, depth of experience, certifications, specific work location, and performance during the interview process.
£77,674—£106,820 GBP
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