Senior Machine Learning Engineer, Socure

• 3+ years of experience building and maintaining production-quality software systems
• Background in software engineering, data engineering, MLOps, data science, or research
• Experience with popular ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Experience with containerization (e.g., Docker) and/or container-orchestration systems (e.g., Kubernetes, Argo CD)
• Proficiency in deep learning/machine learning deployment and inference systems
• Familiarity with ML engineering best practices and readiness to work in a fast-paced, dynamic environment
• Experience with databases and/or data warehouses (e.g., DynamoDB, Snowflake or Redshift)
• Experience with distributed data processing and streaming frameworks (e.g., Apache Spark, Apache Kafka)
• Experience with workflow orchestration tools (e.g., Apache Airflow)
• Ability to develop user-centric solutions and effectively translate stakeholder needs into technical requirements
• Experience with cloud platforms (experience with AWS and/or Terraform is a plus)

Desirable

• We are seeking a Senior Machine Learning Engineer to join our US-based Machine Learning (ML) Platform team
• Our team is dedicated to designing, building, and maintaining scalable infrastructure and tools that empower machine learning and deep learning projects at Socure
• As a key member of the ML Platform team, you will play a crucial role in the end-to-end ML lifecycle, from data collection and analysis to the development, deployment, and optimization of robust ML pipelines
• If you have a passion for building efficient, reliable infrastructure and developing tools that simplify and enhance the work of data scientists and ML engineers, we’d love to connect and discuss your background and experiences
• Develop feature engineering strategies and solutions to support machine learning models
• Design and implement robust and scalable systems for efficient model inference
• Build and maintain infrastructure supporting feature engineering, model serving, Gen-AI agents, and related components across the machine learning lifecycle
• Contribute to the development and enhancement of a comprehensive feature platform to streamline and optimize feature creation and management
• Demonstrate best practices in version control and continuous integration / delivery
• Own and drive initiatives from conception to deployment and monitoring
• Collaborate with data scientists, engineers, product managers, and other key stakeholders in a fast-paced cross-functional environment

• End Date: November 30, 2024