Talenthop
United States
ML Platform Engineer
Machine Learning Full-time Mid-Senior level 1h ago
- AI
- Artificial Intelligence
- C++
- Cloud
AI Summary
Seeking an experienced MLOps Engineer to operationalize machine learning at scale on the Databricks platform. This role involves building infrastructure and workflows for model deployment, from experimentation to production. Requires 3-5+ years of MLOps experience with hands-on Databricks and MLflow expertise.
Key Highlights
Operationalize machine learning at scale on the Databricks platform.
Design and maintain MLflow-based workflows and Feature Store infrastructure.
Implement CI/CD pipelines for ML and monitor deployed models.
Key Responsibilities
Design and maintain MLflow-based workflows for experiment tracking, model registry, versioning, and lifecycle management.
Build and manage Feature Store infrastructure to enable reusable, consistent feature pipelines across teams and use cases.
Develop model deployment pipelines, including serving infrastructure, A/B testing support, versioning, and rollback strategies.
Implement CI/CD pipelines tailored for ML workflows, including automated testing, validation gates, and deployment triggers.
Orchestrate distributed model training on Databricks, optimizing for compute efficiency, reproducibility, and cost.
Monitor deployed models for data drift, performance degradation, and system health, triggering automated retraining workflows as needed.
Collaborate with Data Scientists and Data Engineers to reduce friction between experimentation environments and production.
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Technical Skills Required
Benefits & Perks
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Nice to Have
Experience building and consuming Feature Store solutions (Databricks Feature Store or equivalent).
Proven experience deploying and serving ML models at scale, including real-time and batch inference patterns.
Ability to design automated pipelines for model training, validation, and deployment using modern CI/CD tooling.
Strong familiarity with Databricks for distributed training, job orchestration, and cluster management.
Knowledge of model monitoring practices, including drift detection, alerting, and retraining triggers.
Job Description
At Lumenalta, we partner with forward-thinking organizations to build technology solutions that scale, delight users, and accelerate business growth. Our global teams bring curiosity, commitment, and technical excellence to every project. We value transparency, autonomy, and impact—empowering every team member to do their best work.
We’re seeking an experienced MLOps Engineer responsible for operationalizing machine learning at scale on the Databricks platform. This role bridges data engineering and ML, building the infrastructure and workflows that take models from experimentation to reliable production deployments.
What You'll Be Doing
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