Machine Learning Engineer (Azure + Databricks)

About the Role

We are looking for a skilled and passionate Machine Learning Engineer with expertise in Azure and Databricks to join our team. The ideal candidate will bring hands-on experience in building, training, and deploying ML models in real-world applications, along with strong proficiency in cloud platforms and advanced Python programming.

This role provides the opportunity to lead projects, mentor engineers, and contribute to Bizmetric’s AI & ML innovation journey.

Key Responsibilities

Lead ML Projects: Drive end-to-end lifecycle from problem definition, data collection, model development, to production deployment.

Algorithm Development: Design, implement, and optimize ML/DL algorithms (Deep Learning, NLP, Computer Vision, Reinforcement Learning).

Data Preparation: Pre process, clean, and transform large-scale datasets for model training.

Model Evaluation: Establish rigorous testing, validation, and performance optimization processes.

Deployment & Integration: Work with cross-functional teams to integrate ML models into production systems.

Collaboration with DevOps: Partner with DevOps teams on Git, CI/CD pipelines, containerization, and Terraform-based infrastructure.

Mentorship: Guide junior engineers and share best practices in ML & AI.

Required Skills (Must-Have)

Python DS | DE | ETL: 2+ years of hands-on experience.

Advanced Python: Strong coding proficiency and library knowledge.

Machine Learning: Proven track record of developing & deploying ML models.

ML Frameworks: Scikit-learn, TensorFlow, PyTorch.

Azure Cloud: Strong working knowledge of Azure services & tools.

Databricks: Expertise in big data pipelines and ML workflows.

DevOps Knowledge: Experience with Git, CI/CD, Terraform (basic level).

Deep Learning: Solid conceptual understanding.

NLP & Computer Vision: Practical exposure and applied understanding.

Image Processing: Experience with Python libraries like OpenCV.

Good to Have

Familiarity with Agile methodology.

Experience working in cross-functional, collaborative environments.