Python Engineer & ML Infrastructure

Worldwide | Sept. 1, 2026

Report as Closed

Company: Improving

Country: Worldwide

Type: Remote

Employment: Full-time

Description: Improving is an IT services firm focused on AI, data, and applications. We modernize legacy systems, build cloud-native platforms, and deliver future-ready solutions through collaborative, long-term partnerships that drive measurable outcomes.

• Python 3.12+ (required) — Solid Python production experience, not just scripting level
• Snowflake (required) — Comfortable writing and optimizing SQL against Snowflake as a data source and destination for pipeline outputs
• Docker (required) — Building and optimizing container images, including packaging ML model artifacts and their runtime dependencies into deployable images
• Kubernetes (required) — Deploying and operating workloads on Kubernetes; understanding of pods, deployments, resource limits, and basic cluster networking
• Ability to take a research-level prototype and turn it into proven, maintainable, and scheduled production code
• Intermediate-advanced or advanced English (required)

Preferred:

• Specific experience with Kubernetes CronJob (scheduling, concurrency policy, retry limits, failure history handling)
• Experience with the KServe model serving platform or an equivalent (Seldon, BentoML, or similar), as building a KServe cluster is the next defined phase of this role
• Familiarity with clustering/statistical concepts used in the prototype: K-means with auto-K via silhouette score, Jenks Natural Breaks for tiering, feature normalization/weighting
  Authoring Helm charts for packaging Kubernetes workloads
• Experience with model artifact formats and packaging conventions (e.g., ONNX, PyTorch/scikit-learn models in pickle, MLflow model logs) even without having directly trained the models

• Design and maintain production data pipelines using Python and Snowflake
• Dockerize ML models and complex artifacts for containerized deployment
• Orchestrate and scale workloads on Kubernetes, including model-serving services
• Transform research prototypes into robust, tested, and versioned code
• Configure and manage KServe (or equivalent platforms) to serve models in production
• Automate ML processes using Kubernetes CronJobs and scheduled workflows
• Optimize SQL queries in Snowflake to maximize pipeline performance
• Document and maintain infrastructure using Helm charts

• Long-term contract.
• 100% remote.
• Vacation and PTO.
• Potential for two bonuses per year.
• Two salary reviews per year.
• English classes.
• Apple equipment.
• Online course platform.
• Budget for purchasing books.
• Budget for purchasing work materials.
• Much more...

Apply here:

Web: Apply here

Emails: