About this role
IND Staff Engineer - GCC094 We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
Responsibilities
• Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies. • Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage. • Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations. • Accountable for design, development and maintenance of Models as Service • Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences. • Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams • Delivery of critical milestones for model deployment in the AWS and GCP clouds. • Adopt and promote MLOps best practices to the Data Science community.
Minimum Requirements
• Development experience using both the AWS and GCP suite of tools. • Familiarity with SageMaker, Streamlit, web security, credentials and API management tools • Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns. • Experience building and deploying webservices in a cloud environment. • Experience building CICD pipeline using Jenkins or equivalent • Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or similar • Expert-level Github experience, including Github Actions • Strong object oriented development experience using Python, Java, C# • Familiarity with big data technologies (i.e. Hadoop, Spark, Hive, etc.) and RDBMS platforms such as Redshift, Snowflake or BigQuery • Experience in end to end model development lifecycle, from ideation through post production monitoring. • Experience with workflow automation platforms (Apache Airflow, Autosys, similar) • Experience with Solution Design and Architecture of data pipelines • Basic understanding of Data Science model development life cycle
Preferred Skills
• Fundamentally strong with Data Structures and algorithms. • Experience working with Docker, Kubernetes and EC2 environment. • Experience building ML and data pipeline and orchestration services • Basic understanding of ML frameworks i.e. Tensorflow, Anacoda, Scikit Learn, • Experience working in an Agile framework. Qualifications
• ML engineering, data manipulation and application development • Python development experience • Working with IAC, developing CICD pipelines • Experience in the insurance or broader financial services industry • SQL development experience • Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM’s into automated processes
About Us | Our Culture | What It’s Like to Work Here