Your On-Demand Team Embedded in Your Cloud, Focused on Your Outcomes

Who You Get

• Mid-level MLOps engineer (~40 hours/month)
• Shared across 2-3 clients (cost-effective 'slice' model)

What We Do

• Convert notebooks to version-controlled Docker images
• Set up CI for unit and data tests on every commit
• Deploy models to AWS, GCP, or Azure with health-check endpoints
• Weekly office hours to support your data science team

Commitment

• Rolling 3-month agreement
• Cancel or upgrade anytime

Who You Get

• Dedicated mid-senior MLOps engineer (~80 hours/month)

What We Do

• Everything in Flex Starter, plus:
• Build reproducible pipelines (DVC, Kubeflow, or Flyte)
• Create Grafana dashboards (cost, latency, drift tracking)
• On-call support for next-business-day incident response

Commitment

• 6-month rolling contract
• Extend or pause with 30-day notice

Who You Get

• Full-time Lead MLOps Engineer or Architect (~160 hours/month)

What We Do

• Everything in Growth Partner, plus:
• Align MLOps roadmap with SRE and product teams
• Mentor internal engineers via pairing sessions and code reviews

Commitment

• 12-month service-level agreement
• Quarterly OKRs for accountability and alignment

Who You Get

What We Do

• Design and implement full ML platforms (or modernize legacy stacks)
• Round-the-clock monitoring & support with customizable SLA
• Deliver quarterly architecture reviews and cost-optimization roadmaps

Commitment

• 6- or 12-month engagement
• Renewable by quarter