Machine Learning Engineer

The Machine Learning Engineer will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Machine Learning Services and Pipelines.

You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments.

• Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope
• Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities
• Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards
• Use big data technologies to help process data and build scaled data pipelines (batch to real time)
• Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines
• Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure
• Automate ML models deployments
• Work timing-11:30 AM-9:00 PM

• 8 years of overall experience that includes at least 4+ years of hands-on work experience data science / Machine learning
• Minimum 4+ year of SQL experience
• Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers (Azure preferred) is preferred

• BE/BS in Computer Science, Math, Physics, or other technical fields.

Skills, Abilities, Knowledge:

• Science Hands on experience and strong knowledge implementing & productionizing machine learning models supervised and unsupervised models. Deployment of models in am MLOps framework is required. Knowledge of Demand Forecast models is a plus.
• Programming Skills Hands-on experience in statistical programming languages like , R and database query languages like
• Statistics Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators is a plus
• Cloud (Azure) Experience in Databricks and ADF is required
• Familiarity with Spark, Hive, Pigis an added advantage
• Model deployment experience will be a plus
• Experience with version control systems like GitHub and CI/CD tools