Senior Machine Learning Engineer

Posted 2 Days Ago
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11 Locations
Remote
Senior level
Software • Consulting
The Role
Design, build, deploy, and maintain scalable production machine learning systems. Responsibilities include developing end-to-end ML pipelines, distributed data workflows with PySpark and SQL, model deployment across AWS, Azure, GCP, and Databricks, and implementing MLOps practices such as versioning, monitoring, CI/CD, and lifecycle management. The role also manages Kubernetes-based workloads, optimizes model performance and reliability, and collaborates with data, product, and business teams.
Summary Generated by Built In

Job Title: Senior Machine Learning Engineer

Key Skills: Python, SQL, PySpark, Machine Learning, Scikit-learn, PyTorch, XGBoost, TensorFlow, ML Pipelines, MLflow, Databricks, AWS, Azure, GCP, Kubernetes, MLOps

Experience: 5+ YOE

Location: LATAM (Guatemala, Honduras, El Salvador, Nicaragua, Panama, Colombia, Perú, Mexico, Costa Rica, Brazil, Ecuador, Paraguay, Uruguay)

Modality: Remote


We at Coforge are hiring Senior Machine Learning Engineer (Job# 15311-1-1) with the following skill set.

Key Responsibilities

  • Design, develop, and deploy scalable machine learning solutions in production environments.
  • Build and optimize end-to-end ML pipelines, including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
  • Develop distributed data processing workflows using PySpark and SQL to support large-scale ML applications.
  • Collaborate with Data Scientists, Data Engineers, Product Teams, and business stakeholders to translate business requirements into ML solutions.
  • Deploy and manage machine learning models across cloud platforms such as AWS, Azure, GCP, and Databricks.
  • Implement MLOps best practices, including model versioning, experiment tracking, CI/CD, monitoring, and lifecycle management.
  • Design and maintain containerized ML workloads leveraging Kubernetes for model serving, batch processing, and orchestration.
  • Drive improvements in model performance, scalability, reliability, and operational efficiency.

Required Skills & Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent practical experience).
  • 5+ years of experience as a Machine Learning Engineer, focused on production-grade ML systems.
  • Strong programming experience with Python, SQL, and PySpark for large-scale data processing.
  • Hands-on experience with machine learning frameworks and libraries such as Scikit-learn, PyTorch, TensorFlow, and XGBoost.
  • Proven expertise building and maintaining robust ML pipelines using MLflow or similar MLOps platforms.
  • Experience deploying and managing machine learning solutions in cloud environments, including AWS, Azure, GCP, and Databricks.
  • Strong understanding of the complete ML lifecycle, from data preparation to production monitoring and maintenance.
  • Experience working with Kubernetes and containerized workloads for machine learning applications.
  • Excellent communication skills with the ability to collaborate effectively across cross-functional teams.

Preferred Skills

  • Experience with MLOps, CI/CD pipelines, and model governance frameworks.
  • Knowledge of model monitoring, observability, and performance optimization techniques.
  • Experience working in Agile development environments.
  • Familiarity with Docker, workflow orchestration tools, and large-scale distributed computing platforms.
  • Exposure to generative AI, LLMs, or advanced machine learning systems is a plus.

Posted On: Sept 23rd 2026

At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality. 

Skills Required

  • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent practical experience
  • 5+ years of experience as a Machine Learning Engineer focused on production-grade ML systems
  • Strong programming experience with Python, SQL, and PySpark
  • Experience with Scikit-learn, PyTorch, TensorFlow, and XGBoost
  • Experience building and maintaining ML pipelines using MLflow or similar MLOps platforms
  • Experience deploying machine learning solutions in AWS, Azure, GCP, and Databricks
  • Understanding of the complete machine learning lifecycle, including production monitoring and maintenance
  • Experience with Kubernetes and containerized workloads
  • Excellent communication and cross-functional collaboration skills
  • Experience with MLOps, CI/CD pipelines, and model governance frameworks
  • Knowledge of model monitoring, observability, and performance optimization
  • Experience in Agile development environments
  • Familiarity with Docker, workflow orchestration tools, and large-scale distributed computing platforms
  • Exposure to generative AI, LLMs, or advanced machine learning systems

Encora Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Encora and has not been reviewed or approved by Encora.

  • Healthcare Strength — Health coverage is described as employer-provided in multiple locations, with private plans and family coverage highlighted in Spain and Mexico. Medical insurance quality is presented as a recurring bright spot alongside standard coverage.
  • Leave & Time Off Breadth — Time off includes paid holidays and PTO, with regional materials indicating additional leave provisions in certain countries. Leave is generally portrayed as conventional to generous depending on location.
  • Flexible Benefits — Work-from-home flexibility is frequently highlighted as a plus, though it varies by role and client needs. Remote and hybrid options are positioned as part of the overall package.

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The Company
Chennai
7,456 Employees
Year Founded: 1980

What We Do

Headquartered in Santa Clara, California, and backed by renowned private equity firms Advent International and Warburg Pincus, Encora is the preferred technology modernization and innovation partner to some of the world’s leading enterprise companies. It provides award-winning digital engineering services including Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering. Encora's deep cluster vertical capabilities extend across diverse industries, including HiTech, Healthcare & Life Sciences, Retail & CPG, Energy & Utilities, Banking Financial Services & Insurance, Travel, Hospitality & Logistics, Telecom & Media, Automotive, and other specialized industries. With over 9,000 associates in 47+ offices and delivery centers across the U.S., Canada, Latin America, Europe, India, and Southeast Asia, Encora delivers nearshore agility to clients anywhere in the world, coupled with expertise at scale in India. Encora’s Cloud-first, Data-first, AI-first approach enables clients to create differentiated enterprise value through technology

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