Job Overview
We are looking for a highly skilled AI & Machine Learning (AI/ML) Engineer to join our expanding technology team. In this role, you will be responsible for designing, building, and deploying scalable machine learning models and intelligent data solutions that drive core business value. You will bridge the gap between data science prototypes and production-ready applications, ensuring our AI architecture is secure, cost-effective, and highly reliable.
Key Responsibilities (Job Description)
- Model Development & Engineering
- Build and Train: Design, validate, and train machine learning models for predictive analytics, classification, computer vision, or NLP based on business problems.
- Generative AI Integration: Implement and fine-tune generative AI technologies, large language models (LLMs), and Retrieval-Augmented Generation (RAG) frameworks.
- System Design: Write clean, production-grade, and scalable code (primarily in Python) to deploy models into real-world applications.
- Data & MLOps Pipeline Management
- ML Pipelines: Build, automate, and manage end-to-end MLOps pipelines to monitor model drift, system degradation, and retraining workflows.
- Cloud Infrastructure: Deploy and optimize machine learning systems within major cloud ecosystems such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.
- Data Collaboration: Partner with data engineers to construct robust ETL/ELT data pipelines and connect model inferences to enterprise data warehouses.
- System Optimization & Governance
- Performance Tuning: Conduct model evaluation and hyperparameter tuning to reduce inference costs and processing times.
- Security & Ethics: Ensure all AI models adhere to strict data privacy guidelines, data security best practices, and ethical standards.
- Stakeholder Collaboration
- Cross-functional Alignment: Work alongside Product Managers, Data Scientists, and Business Analysts to translate local market needs into technical executions.
- Technical Translation: Present complex architectural approaches and model insights clearly to both technical and non-technical stakeholders.
Qualifications
- 3 years of proven experience in software engineering, data science, or specialized AI/ML model deployment.
- Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical quantitative field.
- Programming Languages: Deep proficiency in Python is mandatory, along with structural familiarity with Java, C++, or SQL.
- AI/ML Frameworks: Hands-on mastery of frameworks such as PyTorch, TensorFlow, Keras, and Scikit-learn.
- GenAI Ecosystems: Experience with LangChain, LlamaIndex, Vector Databases (e.g., Pinecone, Chroma), and OpenAI/Claude API integrations.
