Role description

We are looking for an AI / ML Engineer with strong software engineering fundamentals and handson experience building productiongrade Python systems scalable data pipelines and machine learning solutions in cloud environments The ideal candidate will have practical experience across the machine learning lifecycle including data preparation feature engineering model development evaluation deployment support monitoring and documentation

This role is well suited for an engineer who can work at the intersection of machine learning data engineering and cloudbased software development The candidate should be comfortable developing MLdriven automation solutions working with structured and semistructured data collaborating with crossfunctional teams and translating research or prototype ideas into reliable engineering solutions

Key Responsibilities

Design develop and maintain machine learning models and AIdriven systems using Python and modern ML libraries

Build and optimize data pipelines for heterogeneous data sources such as CSV JSON XML and relational databases

Perform data preprocessing feature engineering exploratory data analysis model training validation and performance evaluation

Develop ML solutions for use cases involving classification forecasting embeddings NLP computer vision similarity search and intelligent automation

Implement scalable ETLELT workflows using Python Snowflake and cloud services such as AWS S3 Lambda and Glue

Support deploymentready ML workflows including model monitoring data quality checks logging error handling and ing

Collaborate with data scientists software engineers product teams and business stakeholders to understand requirements and deliver practical AIML solutions

Conduct experiments compare model architectures tune hyperparameters analyze model performance and document findings clearly

Develop reusable maintainable and welltested code following software engineering best practices Git workflows and CICD standards

Stay current with advances in machine learning deep learning NLP computer vision embeddings and cloudbased AIML platforms

Required Skills and Experience

4 years of professional experience in software engineering data engineering machine learning engineering or related technical roles

Strong programming experience in Python with working knowledge of SQL and familiarity with R or C as an added advantage

Handson experience with scientific Python and ML libraries such as NumPy Pandas Matplotlib scikitlearn SciPy PyTorch TensorFlow HuggingFace and Transformerbased models

Experience developing machine learning models using algorithms such as Random Forest ensemble methods deep learning models NLP models computer vision models and embeddingbased retrieval systems

Strong understanding of data preprocessing feature engineering model evaluation metrics class imbalance handling validation techniques and statistical testing

Experience designing and maintaining scalable ETLELT pipelines and data workflows using Snowflake AWS and Python

Working knowledge of cloud services especially AWS services such as S3 Lambda Glue and cloudnative data infrastructure

Experience with data quality monitoring schema management anomaly detection logging and pipeline reliability practices

Familiarity with Docker CICD pipelines Gitbased collaboration technical documentation and production software development practices

Ability to communicate technical concepts effectively to both technical and nontechnical stakeholders

Preferred GoodtoHave Skills

Experience with MLOps concepts such as model versioning experiment tracking model deployment model monitoring and automated retraining workflows

Experience with multimodal AI imagetext embeddings semantic search contentbased retrieval or vector similarity search

Handson experience with computer vision use cases including CNNbased classification image feature extraction and dataset quality analysis

Experience with NLP use cases including BERT Transformer finetuning speech or text classification and emotion or intent detection

Exposure to largescale datasets data warehousing star schema design outlier detection and analyticsready data modeling

Research experience publication experience or demonstrated ability to convert research concepts into applied ML solutions

AWS certification or equivalent cloud certification

Experience building lightweight web applications or APIs for ML model serving such as Flaskbased applications

Education and Certifications

Bachelors or Masters degree in Computer Science Data Analytics Information Technology Artificial Intelligence Machine Learning Statistics or a related field

Advanced academic background in Computer Science or Data A