MLops engineer

LTM; Bengaluru; Hybrid; INR 2,200,000 - 3,500,000; Full time

Job summary

LTM is seeking an MLOps Engineer in Bengaluru to design and operate end-to-end ML platforms, covering training, deployment, monitoring, and retraining workflows. You will implement scalable ML pipelines using Azure ML, Docker, and Kubernetes, and tackle large-scale data processing with Databricks and Spark.

The role emphasizes collaboration with stakeholders and applying ML techniques to real business problems, including models handling unstructured data in enterprise AI workflows.

Qualifications

• Hands on experience in Python for object oriented and/or functional programming.
• Proven experience delivering and supporting production scale ML systems.
• Hands on exposure to computer vision and/or cognitive services within production AI solutions.
• Ability to assess and apply machine learning techniques to solve real business problems.
• Experience integrating ML models on unstructured data as part of enterprise AI workflows.

Responsibilities

• Design, implement, and maintain end to end MLOps frameworks covering model training, experiment tracking, versioning and reproducibility.
• Deployment and monitoring, automated retraining workflows, and implementing MLflow or equivalent lifecycle management.
• Build custom APIs for ML model training and inference, supporting both batch and real time workloads.
• Develop cloud first solutions using Microsoft Azure and Azure ML, and manage containerized ML workloads with Docker and Kubernetes.
• Orchestrate large scale ML/DL workloads on cloud infrastructure and with big data tools (Databricks, Spark, ADF).
• Collaborate with technical experts and stakeholders to identify opportunities where ML enables data-driven decision making.

Job description

Job Summary

Job Description MLOps Engineer

Experience -7 Years
Location -Bellandur bangalore
Shift-1.30pm- 10.30pm

Key Skills MLOps, CI/CD, GIT hub, Python, Ansible, Azure DevOps.

• Hands on experience in object oriented and/or functional programming using Python
• Proven experience delivering and supporting production scale ML systems
• Hands on exposure to computer vision and/or cognitive services within production AI solutions
• Ability to assess and apply machine learning techniques to solve real business problems
• Experience integrating ML models on unstructured data as part of enterprise AI workflows

MLOps & ML Platform Engineering

• Design, implement, and maintain end to end MLOps frameworks covering:
• Model training
• Experiment tracking
• Versioning and reproducibility
• Deployment and monitoring
• Automated retraining workflows
• Implement and operationalize MLflow or equivalent frameworks for experiment tracking and lifecycle management
• Build custom APIs for ML model training and inference, supporting both batch and real time workloads

Cloud Native & Containerized ML Systems

• Develop cloud first solutions using Microsoft Azure, including:
• Azure Machine Learning
• Azure Fabric (as applicable)
• Hands on experience building and deploying ML pipelines using Azure Machine Learning SDK
• Design and manage containerized ML workloads using:
• Docker
• Kubernetes
• Orchestrate large scale ML/DL workloads, including distributed training and massively parallel model execution on cloud infrastructure

Data, Scale & Performance Engineering

• Proficient in orchestrating large scale ML and DL jobs using big data tooling and modern container orchestration platforms
• Experience with model optimization and hyperparameter tuning at scale for ML/DL models
• Working knowledge of mathematics and algorithms, including:
• Linear algebra
• Probability
• Statistics
• Strong understanding of data engineering tools and patterns, including:
• Databricks
• Apache Spark
• Azure Data Factory

Collaboration & Communication

• Ability to engage effectively with technical experts and stakeholders at all organizational levels
• Strong capability to identify opportunities where ML and analytics can:
• Improve business workflows Enable data driven decision making
• Excellent written and verbal communication skills, with the ability to convey complex technical concepts clearly and concisely

Skills

Mandatory Skills : MLOps, CI/CD, GIT hub, Python, Ansible, Azure DevOps.