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Machine Learning Engineer - Azure & Databricks

5 hours, 18 minutes ago
Bolivia, Peru, Colombia, Costa Rica
Full-time
Senior
Machine Learning Engineer
DevOps and Infrastructure
Apache Spark Azure CI/CD Databricks Docker FastAPI Flask Kubernetes Machine Learning Microservices MLOps Python REST API
Apply Now
Coforge

Coforge

Coforge is a global digital services provider specializing in transforming businesses through technology and industry expertise, powering growth with innovative solutions and platforms.

IT Services
10K-50K
Founded 1992
View All Jobs 52

Description

  • Deploy and operationalize machine learning and AI models developed by data scientists.
  • Design and develop APIs and services that expose machine learning models, predictions, and curated datasets.
  • Build scalable batch and real-time inference pipelines.
  • Develop low-latency systems for AI and machine learning workloads.
  • Build and maintain data pipelines within Azure and Databricks environments.
  • Implement model-serving patterns using REST APIs and microservices architectures.
  • Productionize LLM-powered solutions, semantic search, and retrieval systems.
  • Implement monitoring, logging, alerting, model versioning, and CI/CD practices.
  • Optimize performance, scalability, and cost efficiency across ML services and data platforms.
  • Collaborate with data scientists, data engineers, and business stakeholders to deliver production-ready AI solutions.

Requirements

  • 5 to 8+ years of experience in machine learning engineering or backend/platform engineering with ML exposure.
  • Strong programming skills in Python.
  • Experience building APIs using FastAPI, Flask, or similar frameworks.
  • Proven experience deploying machine learning models into production environments.
  • Experience building inference services and scalable APIs.
  • Knowledge of both batch and real-time machine learning systems.
  • Hands-on experience with Azure and Databricks or similar platforms.
  • Familiarity with Lakehouse architectures and distributed processing technologies such as Spark.
  • Experience designing RESTful APIs and scalable backend services.
  • Strong understanding of low-latency system design and microservices architecture.
  • Experience with CI/CD pipelines, Docker, and Kubernetes.
  • Knowledge of monitoring, observability, and DevOps best practices.
  • Experience with LLM deployment and integration (preferred).
  • Knowledge of embeddings, semantic search, and Retrieval-Augmented Generation (RAG) (preferred).
  • Familiarity with prompt engineering workflows (preferred).
  • Exposure to insurance domain data such as policy, claims, or underwriting (preferred).
  • Experience working in financial services or regulated industries (preferred).

Interested in this position?

Apply directly on the company website

Apply Now

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