Our company description
Mission is a platform for hiring, vetting and managing software development talents. It enables our clients to connect with the world’s best talent to build mission-critical software products.
About the client
Founded in 2015 and headquartered in Boston, this fully remote company helps brands acquire and engage customers by matching people with gifts they will love. By creating a new way for performance marketing professionals to discover and reach new consumers, the company is disrupting digital advertising. The customer base spans retail media networks, commerce media networks, consumer brands, and advertisers across ecommerce, entertainment, travel, consumer packaged goods, subscription, and streaming.
About the Role
As an MLOps/Data Engineer, you’ll report to the Data Science Manager and work closely with both our Data Science and Product teams. You’ll architect storage and compute, harden training/inference pipelines, and make our ML code, data workflows, and services reliable, reproducible, observable, and cost-efficient. You’ll also set best practices and help scale our platform as we grow.
What you will do:
- Architecture & storage: Design and implement our data storage strategy (warehouse, lake, transactional stores) with scalability, reliability, security, and cost in mind.
- Pipelines & ETL: Build and maintain robust data pipelines (batch/stream), including orchestration, testing, documentation, and SLAs.
- ML platform: Productionize training and inference (batch/real-time), establish CI/CD for models, data/versioning practices, and model governance.
- Feature & model lifecycle: Centralize feature generation (e.g., feature store patterns), manage model registry/metadata, and streamline deployment workflows.
- Observability & quality: Implement monitoring for data quality, drift, model performance/latency, and pipeline health with clear alerting and dashboards.
- Reliability & cost control: Optimize compute/storage (e.g., spot, autoscaling, lifecycle policies) and reduce pipeline fragility.
- Engineering excellence: Refactor research code into reusable components, enforce repo structure, testing, logging, and reproducibility.
- Cross-functional collaboration: Work with DS/Analytics/Engineers to turn prototypes into production systems, provide mentorship and technical guidance.
- Roadmap & standards: Drive the technical vision for ML/data platform capabilities and establish architectural patterns that become team standards.
What You Bring:
- Experience: 5+ years in data engineering/MLOps or related fields, including ownership of data/ML infrastructure for large-scale systems
- Software engineering strength: Strong coding, debugging, performance analysis, testing, and CI/CD discipline; reproducible builds
- Cloud & containers: Production experience on AWS, Docker + Kubernetes (EKS/ECS or equivalent)
- IaC: Terraform or CloudFormation for managed, reviewable environments
- Data engineering: Expert SQL, data modeling, schema design, modern orchestration (Airflow/Step Functions) and ETL tools
- ML tooling: MLflow/SageMaker (or similar) with a track record of production ML pipelines
- Warehouses & lakes: Databricks, Redshift and lake formats (Parquet)
- Monitoring/observability: Data/ML monitoring (quality, drift, performance) and pipeline alerting
- Collaboration: Excellent communication, comfortable working with data scientists, analysts, and engineers in a fast-paced startup
- PySpark/Glue/Dask/Kafka: Experience with large-scale batch/stream processing
- Analytics platforms: Experience integrating 3rd party data
- Model serving patterns: Familiarity with real-time endpoints, batch scoring, and feature stores
- Governance & security: Exposure to model governance/compliance and secure ML operations
- Mission-oriented: Proactive and self-driven with a strong sense of initiative; takes ownership, goes beyond expectations, and does what’s needed to get the job done
What you get:
- Competitive compensation, comprehensive benefits (401K, Medical/Dental/Vision), and we offer all full-time employees the potential to hold company equity
- Flexible remote work
- Unlimited Responsible PTO
- Great opportunity to join a growing, cash-flow-positive company while having a direct impact on revenue, growth, scale, and future success
- $130-$200k per year depending on experience
