Job Description
We are seeking a highly motivated and skilled AI/ML Engineer to contribute to cutting-edge research and development within our team. This role offers a unique opportunity to work on challenging projects, collaborate with business, and gain practical experience in the application of AI/ML techniques to real-world problems. The successful candidate will be involved in all stages of the machine learning lifecycle, from data preprocessing and feature engineering to model training, evaluation, and deployment. A strong theoretical foundation and hands-on coding experience are essential.
Responsibilities
- Bachelor's degree in Computer Science / Computer Engineering or a similar technical discipline.
- 2+ years of work experience as a backend Cloud software engineer with familiarity in at least one major cloud platform (GCP) and in Python
- Advanced working knowledge of object-oriented/object function programming languages: Python
- Advance query knowledge using SQL
- Experience/understanding in MLOps, Gen AI, AI agents, Chatbot.
- Experience with ML workflow orchestration tools: Airflow, Kubeflow etc.
- Experience in DevOps and CI/CD principles: Jenkins, Tekton, Cloud Build, GitHub Actions etc.
- Experience with scripting language: Bash, PowerShell etc.
- Operationalize machine learning models by building data infrastructure and managing structured and unstructured data, supporting AI/ML/LLM workflows, including data labeling, classification, and document parsing.
- Collaborate with data scientists, Data engineers, and other stakeholders to understand data needs and deliver solutions aligned with business objectives, security, and data governance.
- Utilize ML Services like Vertex AI.
- Document data processes, pipeline designs, and architecture, contributing to knowledge transfer and system maintenance.
- Experience with cloud services, preferably GCP Services like Vertex AI, Cloud Function, Cloud Run, BigQuery etc.
- Experience in container management solutions: Kubernetes, Docker.
- Experience with Infrastructure as Code: Terraform etc.
- Automate infrastructure and deployments using Infrastructure as Code (IaC) using tools like
- Monitor and troubleshoot data pipelines and systems to identify and resolve issues related to performance, reliability, and cost-effectiveness.
- DevOps & MLOps: Knowledge of DevOps methodologies, CI/CD pipelines, and MLOps practices, including integrating data pipelines with ML workflows.
- Data Engineering Fundamentals: Solid understanding of data modeling, data warehousing concepts, ETL/ELT processes, and big data architecture, Designing pipelines and architectures for data processing.
- Communication & Collaboration: Excellent communication and teamwork skills, with the ability to collaborate effectively with technical and non-technical stakeholders in agile environments.
Qualifications
- 2+ years experience
- GCP Expertise: Strong proficiency in GCP services, including BigQuery, Dataflow, Dataproc, Data Fusion, Air Flow, Pub/Sub, Cloud Storage, Vertex AI, Cloud Functions, and Cloud Composer, GCP based Big Data deployments (Batch/Real-Time) leveraging Big Query, Big Table
- Programming & Scripting: Expert-level skills in Python and SQL are essential.
- DevOps & MLOps: Knowledge of DevOps methodologies, CI/CD pipelines, and MLOps practices, including integrating data pipelines with ML workflows.
