Senior ML Engineer: Databricks AI Platform (Hybrid/Remote)

Curinos; United States; Hybrid; USD 130,000 - 147,000; Full time

Benefits offered by this job

Competitive benefits

Flexible work options

Unlimited PTO

Learning and development tools

DEI program

Employee assistance program

Job summary

Curinos seeks a Senior Machine Learning Engineer to operationalize production-grade ML/AI on a Databricks-native platform, owning deployments and monitoring pipelines for model performance and guardrails. You will collaborate with data scientists, data engineers, and product managers in a regulated FinTech environment.

Experience with Databricks workflows, Delta Lake, Unity Catalog, and MLflow is essential, as is strong communication and ownership of end-to-end ML/AI workflows.

Qualifications

• Strong hands-on experience with Databricks: Workflows, Delta Lake, Delta Live Tables, Asset Bundles, Unity Catalog, Genie Code.
• Proficiency with MLflow for experiment tracking, model registry, and deployments.
• Experience deploying models to Databricks Model Serving, REST APIs, or external endpoints.
• Familiarity with Python, Spark, and SQL for data and ML workflows.
• Solid understanding of CI/CD tools (e.g., Databricks Asset Bundles, Jenkins, etc.).
• Exposure to contemporary big data and AI stacks and technologies: Yarn, AWS, Spark, Databricks, distributed computing, chatGPT, Claude, Copilot
• Some experience with real‑time processing nice to have
• Solid understanding of data structures and algorithms
• Some experience with production support
• Self–discipline and willingness to learn
• Solid verbal and written communication skills
• Team player and ability to work well with others in an intellectually challenging environment

Responsibilities

• Manage and support ML and AI model lifecycle using Databricks and MLflow: training, tracking, packaging, deployment, monitoring, agentic AI safety and generative AI guardrails
• Build and maintain robust and scalable monitoring pipelines for ML model performance, agentic and generative AI guardrails and safety, and LLMs evaluators to ensure SLA adherence, scalability, reproducibility, and reliability
• Implement CI/CD pipelines for ML and AI workflows, including testing, version control, and rollback strategies
• Support governance and compliance requirements: model registry usage, auditability, and reproducibility
• Document processes, automation frameworks, and operational runbooks
• Bring best practices to bear on the team’s products and educate the team members

Skills

Databricks suite

MLflow

Python

Spark

CI/CD tools

Shell scripting

AWS

Big data stacks

Real-time processing

Data structures & algorithms

Production support

Communication skills

Team collaboration

Tools

Databricks

MLflow

REST APIs

Python

Spark

Unix/Linux

AWS

Databricks Asset Bundles

Unity Catalog

Job description

Curinos seeks a Senior Machine Learning Engineer to operationalize production-grade ML/AI on a Databricks-native platform, owning deployments and monitoring pipelines for model performance and guardrails. You will collaborate with data scientists, data engineers, and product managers in a regulated FinTech environment.

Experience with Databricks workflows, Delta Lake, Unity Catalog, and MLflow is essential, as is strong communication and ownership of end-to-end ML/AI workflows.