Sr ML Engineer
Stori Card
A Machine Learning Engineer at Stori builds Artificial Intelligence (AI) / Machine Learning (ML) infrastructure to speed up the development, deployment, and execution of AI/ML solutions at scale and bring game-changing impact to our business decisioning. The role will collaborate with data scientists , data engineers, and software engineers to deliver AI/ML applications to market with innovation and automation.
Experience
Required
Strong background in software engineering, data engineering, machine learning, or data science
1+ years of experience of deploying ML solutions into production
1+ Experience with cloud environment, AWS preferred
Bachelor degree in Computer Science, Data Science, AI, Physics, or other quantitative fields.
Preferred
Advanced degree in Computer Science, Data Science, AI, Physics, or other quantitative fields.
3+ years of experience of deploying ML solutions into production
Advanced knowledge of building applications with genAI and LLMs
Advanced knowledge of ML frameworks such as TensorFlow, PyTorch, etc
Experience with distributed systems, such as Spark, Databricks, etc
Familiarity with compute and containerization services: EC2, EMR, ECS/EKS/Fargate
Experience in consumer-facing service industry with millions of customers
Desired Knowledge
Proficiency with Python and ML libraries (pandas, polars, sklearn, etc)
Expertise in large scale datasets in various data environments (Redshift, Snowflake, SQL databases, Databricks) and data formats (Parquet, Iceberg, Delta Lake, etc).
Solid understanding of ML concepts and Model Lifecycle
Solid coding skill in cloud engineering: Lambda, Step Function, CloudFormation/CDK, etc
Experience with MLOps stacks and tools such as SageMaker, EMR, Kubeflow, Docker, Airflow, etc
Knowledge of DevOps and CI/CD
A self starter and problem solver owning complex and impactful projects in a fast-paced environment
Collaborative and open minded in partnership with multiple roles and teams
Passion for continuous learning and self development, and willingness to share within organization
Required
Strong background in software engineering, data engineering, machine learning, or data science
1+ years of experience of deploying ML solutions into production
1+ Experience with cloud environment, AWS preferred
Bachelor degree in Computer Science, Data Science, AI, Physics, or other quantitative fields.
Preferred
Advanced degree in Computer Science, Data Science, AI, Physics, or other quantitative fields.
3+ years of experience of deploying ML solutions into production
Advanced knowledge of building applications with genAI and LLMs
Advanced knowledge of ML frameworks such as TensorFlow, PyTorch, etc
Experience with distributed systems, such as Spark, Databricks, etc
Familiarity with compute and containerization services: EC2, EMR, ECS/EKS/Fargate
Experience in consumer-facing service industry with millions of customers
Work closely with Data Scientists to understand their unique processes, identify pain points, and form effective solutions
Establish scalable, efficient, reusable, and automated pipelines for AI/ML model training, release, and execution
Deploy and operationalize models in both real-time applications and batch workflows
Execute best practices in version control and continuous integration/continuous delivery (CI/CD)
Establish, maintain, and administer AI/ML platforms and environments (e.g. AWS SageMaker, Azure ML, GCP Vertex AI) to empower Machine Learning Engineers and Data Scientists to research, experiment, and prototype
Develop tooling for data scientists to facilitate ML tasks from data exploration to model monitoring