2 days ago
Base Salary
$191k - $261k/yr
Responsibilities
- Productionize customer-tailored predictive models, configurations, and scoring workflows with validation, release, monitoring, and rollback paths.
- Build UI workflows and dashboards for training triggers, model refreshes, validation outcomes, model health, score changes, data quality, and troubleshooting.
- Develop and modify APIs, backend services, data contracts, orchestration workflows, and automated retraining, validation, promotion, and deployment processes.
- Create safeguards for data quality, score distributions, threshold changes, and production edge cases.
- Monitor models and services for drift, data shifts, reliability issues, and operational regressions.
- Turn repeatable customer solutions into reusable product, platform, deployment, and self-service capabilities.
- Improve Kubernetes workloads, compute, pipelines, deployment tooling, observability, runbooks, release checklists, audit trails, and support processes.
- Partner with customers and cross-functional Product, Data Science, and Platform Engineering teams to address technical needs and productize recurring solutions.
Requirements
- 6+ years of experience in MLOps, ML platform engineering, backend engineering, full-stack engineering, or related production engineering roles.
- Experience owning machine-learning systems in production, including training, deployment, monitoring, retraining, and incident response.
- Strong Python and SQL skills, including backend services, asynchronous workflows, testing, CI/CD, and observability.
- Experience building or materially contributing to internal tools, operational dashboards, or customer-facing product workflows.
- Ability to debug across UI, APIs, workflows, data pipelines, model artifacts, and production infrastructure.
- Experience releasing changes safely across multiple customers or production environments, including staged rollout, impact checks, and rollback.
- Working knowledge of Kubernetes and cloud infrastructure.
- Preferred experience with FastAPI, frontend development, Airflow, Spark, MLflow, model registries, feature pipelines, workflow orchestration, AWS, S3, Hive, distributed compute, multi-tenant SaaS, and forward-deployed or customer-facing engineering.
Benefits
- Remote US location and full-time employment with equipment and support for working from home or an office.
- Health coverage, life and disability insurance, paid parental leave, paid time off, paid holidays, quarterly self-care days, and a 401K employer matching program.
- Stock options may be available, along with wellness programs, employee resource group events, and LinkedIn Learning access.
Tech Stack
Categories
Forward Deployed
About 6sense
6sense builds a B2B revenue platform that uses intent data and AI to help marketing and sales identify in‑market accounts, run account‑based campaigns, and prioritize outreach. The company sells its software via SaaS subscriptions and integrates with common CRM and marketing automation tools. Founded in 2013 and headquartered in San Francisco, it is privately held and serves midmarket and enterprise B2B organizations.