We are seeking a hands-on AI/ML Engineer who enjoys transforming real-world business problems into intelligent, scalable solutions. This role is ideal for someone who understands that AI is not just about models, but also about data pipelines, deployment, performance, and impact.
At Bizinso, you’ll work on real-world AI use cases across domains like ERP, CRM, finance, operations, analytics, automation, and decision intelligence—not toy projects or academic experiments.
Design, build, and optimise machine learning and AI models for real production use
Develop and maintain end-to-end ML pipelines (data ingestion training evaluation deployment)
Work extensively with Python to implement AI/ML solutions
Apply supervised, unsupervised, and semi-supervised learning algorithms
Implement NLP, recommendation systems, forecasting, classification, clustering, and anomaly detection models
Collaborate with backend and frontend teams to integrate AI models into live products
Optimise models for performance, scalability, and reliability
Conduct model validation, tuning, monitoring, and retraining
Document model logic, assumptions, and performance for business and technical stakeholders
Stay updated with the latest trends in AI/ML, LLMs, and applied data science
Strong proficiency in Python for AI/ML development
- Having a minimum 3-4 years of experience.
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Solid understanding of machine learning algorithms:
Linear & Logistic Regression
Decision Trees, Random Forest, Gradient Boosting
SVM, KNN
Clustering (K-Means, DBSCAN, Hierarchical)
Dimensionality Reduction (PCA, t-SNE)
Hands-on experience with ML libraries & frameworks:
NumPy, Pandas, Scikit-learn
TensorFlow / PyTorch (at least one)
Experience working with structured and unstructured data
Strong grasp of statistics, probability, and data analysis
Experience with Natural Language Processing (NLP)
Familiarity with Large Language Models (LLMs) and prompt engineering
Experience with recommendation engines or predictive analytics
Understanding of MLOps concepts (model deployment, monitoring, retraining)
Exposure to REST APIs for model serving
Knowledge of Docker, cloud platforms (AWS/GCP/Azure/DigitalOcean) is a plus
Experience working with SQL databases (MySQL, PostgreSQL)
Familiarity with NoSQL / analytical databases (optional but valuable)
Understanding of data pipelines, ETL processes, and data validation
Ability to work closely with backend systems (Java / Laravel / Node / Python APIs)
Someone who thinks beyond notebooks and understands production realities
Strong problem-solving mindset, not just model fitting
Ability to explain complex AI concepts in simple business language
Ownership mindset—you build it, you improve it, you scale it
Curiosity, learning agility, and a passion for applied AI
Work on real, high-impact AI projects (not demos)
Exposure to enterprise-grade platforms (ERP, CRM, finance, analytics)
Opportunity to shape AI strategy and architecture, not just code
Collaborative, growth-focused environment
Direct interaction with founders, architects, and decision-makers
Learn how AI actually drives business outcomes
Send your resume and/or GitHub/portfolio to: [email protected]
