Shippo · 3 hours ago
Principal Machine Learning Engineer, ML Platform
United States
Full-time
Remote
Lead/Staff
$212K/yr - $287K/yr
15+ years expShippo is a company focused on revolutionizing the shipping industry by providing world-class logistics technology and infrastructure. The Principal Machine Learning Engineer will play a crucial role in building a standardized ML platform to enhance shipping logistics and improve model reliability and operational efficiency.
B2BE-CommerceLogisticsSoftwareSupply Chain Management
Responsibilities
Set technical strategy and drive a multi-quarter roadmap for ML platform capabilities aligned to Shippo’s business priorities
Own cross-team architecture decisions, RFCs, and design reviews for ML lifecycle and inference
Raise the engineering bar through mentorship, production readiness standards, and reusable platform primitives
Be accountable for platform adoption, reliability, and cost-performance outcomes
Build and operate core ML platform components:
ML lifecycle foundation (experiment tracking, reproducibility, artifact management, model registry, versioning, and controlled promotion workflows using MLflow or equivalent)
Training and experimentation enablement (standardized environments, reusable pipelines/templates, evaluation harnesses, and repeatable workflows that let data scientists move from exploration to production with confidence)
Kubernetes-native model serving for real-time inference (safe rollout and rollback, autoscaling, reliability practices, and cost controls)
Batch inference and scoring pipelines (repeatable backfills, retraining triggers, consistent packaging between training and inference)
Observability for ML systems (service health metrics, alerting, and model-quality signals such as drift and data quality)
Developer experience (templates, reference implementations, documentation, and self-service workflows)
Evaluate and recommend inference frameworks and deployment patterns, and document tradeoffs for Shippo’s workloads
Identify and resolve performance bottlenecks across the inference stack (model runtime, compute utilization, networking, serialization, and autoscaling behavior)
Establish ML engineering standards across training, evaluation, testing, model packaging, CI/CD, production readiness, and incident response
Partner with Data Science teams to bridge research and production environments by creating repeatable frameworks, shared standards for code quality and reproducibility, and self-serve paths to deploy models safely
Collaborate with Data and Engineering teams to ensure the platform supports real workflows, drives adoption, and meets reliability expectations
Mentor engineers through design reviews, architecture guidance, and shared best practices across platform and ML development
Qualification
Required
15+ years of software engineering experience, including ownership of production systems (platform, infrastructure, or distributed systems)
4+ years owning ML systems end-to-end in production, including on-call and incident response, and making architecture decisions based on operational constraints (latency, throughput, availability, and cost)
Strong experience building and running services on Kubernetes, including deployments, autoscaling, and observability
Hands-on experience with ML lifecycle tooling such as MLflow or equivalent (tracking, registry, packaging, and promotion workflows)
Demonstrated ability to evaluate inference tradeoffs across batch and real-time serving, CPU versus GPU, latency and throughput, cost, and operational complexity
Demonstrated Staff-level technical leadership, including setting technical direction, driving cross-team alignment via RFCs/design reviews, and delivering multi-quarter roadmaps
Proven ownership of reliability and operational outcomes for production systems (SLOs, incident response, and measurable improvements in stability and performance)
Demonstrated ability to ship incrementally, prioritize production reliability over perfect solutions, and drive adoption through pragmatic platform design
Experience working with or evaluating managed ML platforms (Databricks, SageMaker, Vertex AI, or similar), with clear judgement on strengths, limitations, and build-vs-buy decisions
Preferred
Databricks experience (useful, not required), including Databricks workflows and ML tooling integration
Experience with inference and serving frameworks
Experience with feature store patterns, online and offline consistency, and model evaluation at scale
Experience supporting optimization systems and decision engines in production
LLM or agent workflow experience, especially evaluation harnesses, deployment patterns, guardrails, and monitoring
Benefits
Healthcare coverage for medical, dental, and vision (90% covered by the company, incl. dependents). Pets coverage is also available!
Take-as-much-as-you-need vacation policy & flexible working
One week-long company wide winter slow down
3 Volunteer Days Off (VTOs)
WFH stipend to set up your home office
Charity donation match up to $100
Dedicated programs, coaching, tools, and resources for your professional and career growth as well as an individual learning stipend for your personal and focused growth
Fun team in person time through our Shippos Everywhere program which includes regular team and company off-sites throughout the year as well as local Shippos gatherings
Company
Shippo
Shippo is a shipping platform with tools for label creation, tracking, and carrier comparisons, saving time and cost.
201-500 employees
H1B Sponsorship
Shippo has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (1)
2024 (5)
2023 (8)
2022 (14)
2021 (11)
2020 (10)
Funding
Current Stage
Late StageTotal Funding
$154.28MKey Investors
Bessemer Venture PartnersD1 Capital PartnersUnion Square Ventures
2021-06-02Series E· $50M
2021-02-23Series D· $45M
2020-04-07Series C· $30M
Leadership Team
Simon Kreuz
Co-Founder
Olivier Adler
CFO
Recent News
Uncorkcapital.com
2026-02-05
Digital Commerce 360
2026-01-17
2026-01-16
Company data provided by crunchbase