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