Machine Learning Engineer

Clevertech Partners, LLC
New York, NY, United States
13 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Automation of Tests Continuous Integration Information Engineering DevOps Distributed Computing Environment Machine Learning Azure Machine Learning Management of Software Versions Machine Learning Operations Databricks

Job description

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

  • 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.

Requirements

  • 3-5+ years in MLOps, ML platform engineering, or DevOps for ML, with proven production ML deployments.
  • Hands-on expertise with MLflow for tracking, registry, and project management within Databricks or standalone environments.
  • 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., This is a fully remote position open to candidates based in Latin America (LATAM). While location is flexible, candidates must be willing to maintain at least a 6-hour overlap with core business hours, which are primarily aligned with the Pacific, Central, or Eastern U.S. time zones to ensure effective collaboration with project teams.

About the company

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., Why Lumenalta is an amazing place to work at

At Lumenalta, you can expect that you will:

  • Be 100% dedicated to one project at a time so that you can innovate and grow.
  • Be a part of a team of talented and friendly senior-level developers.
  • Work on projects that allow you to use leading tech.

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This job is hosted externally. Click below to view the full posting and apply.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

5:28 min

Defining MLOps and its role in production systems

Hauke Brammer · World Congress 2023

54 sec

Generating multiple hook options for outreach A/B testing

Leandro Gomes da Silva Leandro Gomes da Silva · World Congress 2025

2:27 min

Managing traffic and tracking costs with Databricks Unity Catalog

Viktoria Semaan Viktoria Semaan · World Congress 2026 Europe

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

2:15 min

Bridging the gap between model management and devops

Joy Joy · World Congress 2024

56 sec

Performing local A/B testing across multiple AI agents

Julia Kasper · Coffee With Developers

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