ABOUT THIS ROLE
As a senior ML-OPs engineer you will work on automating AI/ML Workflow. You will solve problems related to massive cybersecurity and IT data sets. You will collaborate closely with our ML/AI Engineers, Data Scientists and Data Engineers to solve real-world problems plaguing cybersecurity. This role requires basic knowledge of ML and excellent knowledge of automation of ML Processes.
You will:
- Design and implement automation of model training/handling feedback loop process (continuous training)
- Implement solutions for continuous observability of ML models and their performance
- Implement solutions for automation of ML Pipeline components deployment process with appropriate support for quality gate
- Implement solutions for end to end tracking of model KPIs for a given dataset that support model versioning
- Develop Platform and Modular approach in assisting quicker development of ML Models, including solutions for feature store, parameter store and time series data
- Design solutions that are scalable and reduce time for ML model migration to prod
- Build production quality solutions that are highly scalable and meet acceptance criteria of technical requirements
- Interface with multiple teams, including ML, UI, backend and data engineering to ensure seamless data sourcing, handling, processing and visualizations.
You are:
- Driven to experience and learn more about design, architecture, understanding end to end requirements and delivering solutions that can add value to the work
- Collaborative and comfortable working across teams including data engineering, front end, Product Management, ML and DevOps
- Responsible and like to take ownership of challenging problems
- An effective communicator, including good documentation practices and articulating thought processes in a team setting
- Comfortable with working in an agile environment
- Curious about technology and the industry, and a constant learner
You have:
- MS/BS +3 years in Computer Science or a related field
- Expert programming experience with Python or Java
- 2 years experience in one of the ML OPs tools like Apache Airflow(Preferred)/Luigi/Argo/ML Flow/Kube Flow/Sage Maker
- 2+ experience in working with any of the public cloud AWS(preferred)/Azure/GCP
- Knowledge of SQL databases such as Postgres and NoSQL databases such as MongoDB, Cassandra, Redis
- Experience working with Columnar Databases and JSON/Parquet/ORC message formats
- Experience with search engine database such as ElasticSearch is added bonus
