Machine Learning Engineer

Deservely Technologies Pvt Ltd; Bengaluru; Hybrid; INR 1,800,000 - 3,000,000; Full time

Job summary

Deservely Technologies Pvt Ltd in Bengaluru seeks an expert-level Machine Learning Engineer with hands-on Python and production ML systems experience to design, build, deploy, and optimize ML solutions.

The role focuses on end-to-end ML lifecycle, model deployment, monitoring, and collaboration with data scientists and software engineers to deliver reliable, scalable AI capabilities.

Qualifications

• 8 years of professional experience in ML / ML Engineering.
• Expert-level Python programming skills.
• Strong understanding of ML algorithms, statistics, model evaluation, and feature engineering.
• Hands-on experience with scikit-learn, Pandas, NumPy, and ML frameworks such as PyTorch or TensorFlow.
• Strong experience building production-grade ML pipelines and inference systems.
• Solid understanding of MLOps, model deployment, monitoring, and lifecycle management.
• Strong knowledge of data structures, algorithms, software engineering, and system design.
• Experience with SQL and large-scale datasets.

Responsibilities

• Design, develop, and optimize machine learning models and production ML systems using Python.
• Own the end-to-end ML lifecycle including data preparation, feature engineering, model development, evaluation, deployment, and monitoring.
• Build scalable ML pipelines and inference services for production environments.
• Apply appropriate ML, statistical, and optimization techniques to solve complex business problems.
• Improve model accuracy, latency, scalability, and reliability through experimentation and performance optimization.
• Collaborate with Data Scientists, Data Engineers, Software Engineers, and Product teams to productionize ML solutions.
• Implement MLOps practices including model versioning, experiment tracking, CI/CD, monitoring, and automated deployment.
• Review technical designs and code, establish engineering best practices, and mentor other engineers.

Skills

Python

ML algorithms

Production ML pipelines

MLOps

Scikit-learn

PyTorch/TensorFlow

SQL

Big data handling

Education

Bachelor’s or Master’s in CS/Engineering

Tools

Docker

Kubernetes

Spark/PySpark

AWS/GCP/Azure

MLflow/Kubeflow

Job description

Machine Learning Engineer

Location: Bangalore (2 days/office)

Experience: 8 Years

Employment Type: Contract

Role Overview

We are looking for an expert-level Machine Learning Engineer with strong hands‑on expertise in Python to design, build, deploy, and optimize production‑grade ML systems. The ideal candidate should combine deep ML knowledge with strong software engineering, system design, and MLOps capabilities.

Mandatory Skills

• 8 years of professional experience in Machine Learning / ML Engineering.
• Expert‑level Python programming skills.
• Strong understanding of Machine Learning algorithms, statistics, model evaluation, and feature engineering.
• Hands‑on experience with scikit‑learn, Pandas, NumPy, and ML frameworks such as PyTorch or TensorFlow.
• Strong experience building production‑grade ML pipelines and inference systems.
• Solid understanding of MLOps, model deployment, monitoring, and lifecycle management.
• Strong knowledge of data structures, algorithms, software engineering, and system design.
• Experience working with SQL and large‑scale datasets.

Key Responsibilities

• Design, develop, and optimize machine learning models and production ML systems using Python.
• Own the end‑to‑end ML lifecycle including data preparation, feature engineering, model development, evaluation, deployment, and monitoring.
• Build scalable ML pipelines and inference services for production environments.
• Apply appropriate ML, statistical, and optimization techniques to solve complex business problems.
• Improve model accuracy, latency, scalability, and reliability through experimentation and performance optimization.
• Collaborate with Data Scientists, Data Engineers, Software Engineers, and Product teams to productionize ML solutions.
• Implement MLOps practices including model versioning, experiment tracking, CI/CD, monitoring, and automated deployment.
• Review technical designs and code, establish engineering best practices, and mentor other engineers.

Good-to-Have Skills

• Experience with LLMs, NLP, Generative AI, or RAG.
• Experience with PySpark / distributed ML processing.
• Knowledge of Docker, Kubernetes, and microservices.
• Experience with AWS, Azure, or GCP.
• Familiarity with MLflow, Kubeflow, Airflow, or similar ML orchestration tools.
• Experience with real‑time inference, model optimization, or distributed systems.

Educational Qualifications

• Bachelor's or master's degree in computer science**, Engineering, or a related technical field**.
• Advanced degree or strong research/open‑source contributions in ML is an advantage.