Senior Machine Learning Engineer

$160,000 - $190,000/Yr

Socure

Full-time - Mid Level

Remote

501-1,000 employees

Professional, Scientific, and Technical Services

About the position

The Senior Machine Learning Engineer will be a key member of Socure's Machine Learning Platform team, responsible for designing, building, and maintaining scalable infrastructure and tools that support machine learning and deep learning projects. This role encompasses the entire ML lifecycle, from data collection and analysis to the development, deployment, and optimization of robust ML pipelines, with a focus on enhancing the efficiency and reliability of ML systems.

Responsibilities

• 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

Requirements

• 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)

Nice-to-haves

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
• Experience with advanced feature engineering and feature store platforms
• Knowledge of security best practices in ML deployment and data handling
• Experience with CI/CD pipelines specifically tailored for ML applications
• Proficiency in optimizing for latency, scalability, and high availability in production environments
• Strong design skills for developing effective and efficient ML systems
• Hands-on experience with monitoring and observability tools for ML systems (e.g., Prometheus, Grafana)
• Strong communication skills for collaborating with non-technical stakeholders
• Ability to contribute to and foster a positive team culture

Benefits

• Market competitive salary
• Equity
• Comprehensive benefits
• Commissions plans or an annual discretionary performance bonus
• Remote work options for North America
• Hybrid work options for teams in India