ML Engineer

PradeepIt Global Consulting Pvt Ltd.; Bengaluru; On-site; INR 1,200,000 - 3,600,000; Full time

Job summary

PradeepIT Consulting Services Pvt Ltd in Bengaluru seeks an experienced ML Engineer/Data Scientist to own the complete ML lifecycle from data collection to deployment. You will build and validate models, align with business goals and monitor performance.

The role requires hands-on Python, ML/DL expertise, and strong mathematical foundations. You will work with Azure-based MLOps and collaborate with cross-functional teams to deliver production-ready solutions.

Qualifications

• 2–4 years of experience in Data Science and ML engineering.
• Hands-on experience in writing object-oriented Python code for ML workflows.
• Extensive knowledge of ML frameworks, libraries, data structures and software architecture.
• Strong foundation in mathematics, statistics and algorithms.

Responsibilities

• End-to-end ML lifecycle: data collection, cleaning, model building and deployment.
• Align models with business objectives and define metrics to monitor progress.
• Verify data quality and perform data cleaning as needed.
• Experiment with ML/DL models and deploy scalable solutions on cloud platforms.
• Collaborate with data scientists, data engineers and architects; document processes.

Skills

Python

Machine Learning

Deep Learning

Statistics

Data Visualization

Tools

TensorFlow

PyTorch

Keras

Docker

Kubernetes

Kubeflow

Airflow

Argo

Azure

Cosmos DB

Azure Functions

Job description

• Work on end-to-end ML Lifecycle from acquiring data, data cleaning, model building and deployment of models
• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• Verifying data quality, and/or ensuring it via data cleaning
• Experience in building Machine Learning and Deep Learning models either with predictive algorithms, Timeseries, NLP or Computer Vision and deployment of the same
• Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
• Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Finding available datasets online that could be used for training and data augmentation pipelines
• Defining validation strategies, defining preprocessing or feature engineering to be done on a given dataset
• Training models and tuning their hyperparameters
• Analyzing the errors of the model and designing strategies to overcome them
• Deploying models to production
• Ensure code paths are unit tested, defect free and integration tested
• Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.
• Design and implement cloud solutions, build MLOps on Azure
• Work with workflow orchestration tools like Kubeflow, Airflow, Argo or similar tools
• Data science models testing, validation and tests automation.
• Communicate with a team of data scientists, data engineers and architect, document the processes.

Mandatory Skills:

• 2 4 years of experience in Data Science and 1-2 years as ML Engineer
• Hands-on experience of 2+ years in writing object-oriented code using python
• Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
• In-depth knowledge of mathematics, statistics, and algorithms
• Experience working with machine learning frameworks like Tensorflow, Caffe, etc.
• Understanding of Data Structures, Data Systems and software architecture
• Experience in using frameworks for building, deploying, and managing multi-step ML workflows based on Docker containers and Kubernetes.
• Experience with Azure cloud services, Cosmos DB, Streaming Analytics, IoT messaging capacity, Azure functions, Azure compute environments, etc.

Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)