Senior MLOps, Data Systems Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Development of ML Pipelines & Data Systems: Conceive, construct, and uphold scalable pipelines that encompass data ingestion, annotation, validation, training, evaluation, and deployment, guaranteeing reproducibility, consistency, and traceability throughout the entire ML lifecycle.

• Integration of Data & Annotation Pipelines: Create and merge annotation workflows with upstream data ingestion and training systems, facilitating efficient task creation, labeling, quality assurance, and dataset updates that directly enhance model iteration.

• Data-Centric Iteration: Evaluate model performance and identify failures, driving specific data enhancements by linking production signals, data mining, and annotation workflows into ongoing feedback loops.

• Experimentation & Reproducibility: Establish systems for tracking experiments, versioning datasets, and managing model lineage to enable reliable comparisons and iterations across experiments.

• CI/CD for Machine Learning: Create and sustain CI/CD workflows specifically designed for ML systems, allowing for automated testing, validation, and deployment of models and pipelines.

• Support for Model Deployment: Collaborate with embedded and platform teams to assist in deploying models to edge environments, ensuring compatibility, performance, and reliability.

• Monitoring & Feedback Loops: Set up monitoring, logging, and feedback systems to oversee model performance in production and promote continuous improvement through data and model iteration.

• Optimization of Compute: Enhance training and inference workflows across cloud environments, ensuring efficient use of GPU and computing resources.

• Cross-Functional Collaboration: Partner closely with applied scientists, embedded engineers, and data teams to ensure coherence across data workflows, model development, and deployment systems.

• End-to-End Contribution: Engage in and enhance the entire ML lifecycle, from raw data ingestion and annotation to training, evaluation, deployment support, and post-deployment analysis.

⛳️ Requirements

• Over 5 years of professional experience in MLOps, ML infrastructure, data systems, Machine Learning Engineering, or similar roles.

• Proficient programming skills in Python, with experience in ML frameworks such as PyTorch or TensorFlow.

• Proven experience in building and maintaining complete ML pipelines, covering data ingestion, annotation, training, evaluation, and deployment workflows.

• Background in designing or integrating annotation and data curation workflows, along with an understanding of how labeled data influences model performance.

• Strong grasp of dataset versioning, data lineage, and reproducibility within machine learning systems.

• Familiarity with experiment tracking and management of the model lifecycle.

• Knowledge of CI/CD tools (e.g., GitHub Actions, GitLab CI, Jenkins) and their application in machine learning workflows.

• Experience with containerization (Docker) and workflow orchestration systems.

• Familiarity with cloud-based ML environments (e.g., AWS) and distributed training workflows.

• Deep understanding of real-world data challenges, including noisy inputs, edge cases, and variability across environments.

• Strong problem-solving and debugging capabilities, especially in complex, multi-stage systems.

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field (or equivalent practical experience).

🏝️ Benefits

• Comprehensive Health & Wellness: Options for medical, dental, and vision plans. Company-paid life and disability insurance, along with company-funded mental health benefits are also provided.

• Financial & Retirement Planning: 401(k) plan available with both pre-tax and Roth options, plus access to a Health Savings Account (HSA) with a monthly company contribution.

• Family & Fertility Support: Paid parental leave for both birthing and non-birthing parents, alongside fertility and family-forming benefits.

• Paid Time Off: Unlimited vacation, paid leaves, and 10 company holidays.

• Unique Lime Perks: Complimentary access to Lime vehicles in participating cities, a monthly phone allowance, dedicated learning and development days, and perks that include One Medical, Wellhub, and Headspace.