We are seeking Mid-Level Machine Learning Engineers with experience in Microsoft Azure. The ideal candidate(s) will have a strong understanding of machine learning techniques and experience with Azure’s suite of data services. This role will involve designing and developing machine learning systems, conducting experiments, and staying updated with the latest developments in the field.

If you have a knack for problem-solving, a passion for data, and a desire to make a significant impact, we would love to hear from you.

Key Responsibilities:

• Ensure that Health and Safety is the number one goal by following policies, and processes, and always acting safely.
• Implement, configure, and manage various Microsoft Azure solutions and services: You will be responsible for implementing and managing a variety of Azure solutions and services, including but not limited to Azure Machine Learning, Azure Databricks, and Azure Data Factory.
• Collaborate with IT teams and business units to design Azure architectures: You will work closely with other IT teams and business units to design and implement Azure architectures that meet the needs of the organization.
• Assist in the migration of data and services to the Azure cloud platform: You will play a key role in migrating existing data and services to the Azure cloud platform and integration to both Cloud and On-Prem Applications.
• Design the data pipelines and engineering infrastructure to support enterprise machine learning systems at scale: You will be responsible for designing and implementing data pipelines and engineering infrastructure that can support machine learning systems at an enterprise scale.
• Take offline models data scientists build and turn them into a real machine learning production system: You will work with data scientists to take their offline models and turn them into production-ready machine learning systems.
• Develop and deploy scalable tools and services for handling machine learning training and inference: You will develop and deploy tools and services that can handle machine learning training and inference at scale.

Skills & Qualifications:

• A master’s degree in Computer Science, Statistics, Mathematics, or a related field is required. A bachelor’s degree with significant relevant experience would suffice.
• 6+ years working in the IT industry with 4+ years of experience in data science, machine learning, or a related field.
• Strong understanding of machine learning techniques and algorithms: You should have a strong understanding of various machine learning techniques and algorithms, including supervised and unsupervised learning, as well as deep learning.
• Experience with Microsoft Azure’s data services: You should have hands-on experience with various data services offered by Microsoft Azure, such as Azure Machine Learning, Azure Databricks, and Azure Data Factory.
• Familiarity with Azure Cognitive Services for integrating AI capabilities (like vision, language, and decision functionalities) directly into applications.
• Ability to work with large datasets and experience with data processing tools like SQL, Pandas, and big data technologies such as Apache Spark.
• Familiarity with version control systems like Git and development environments like Jupyter notebooks or VSCode and Azure DevOps (CI/CD) – MLOps process.
• Experience with data pipelines and engineering infrastructure: You should have experience designing and implementing data pipelines and engineering infrastructure for machine learning systems.
• Deep understanding of statistical models, machine learning algorithms, and big data technologies. Proven experience in deploying machine learning models into production.
• Proficiency in Python, .NET C#, API development.
• Experience with SQL, NoSQL databases, and Data Fabric architectures.
• Experience with machine learning frameworks like PyTorch, TensorFlow, or Scikit-learn preferred.
• Knowledge of GenAI preferred.
• Strong communication skills to effectively collaborate with team members and stakeholders.
• Strong problem-solving skills and ability to think algorithmically.
• Ability to translate complex findings into a compelling narrative for non-technical stakeholders.
• Certifications like Microsoft Certified: Azure Data Scientist Associate or Microsoft Certified: Azure AI Engineer Associate will be preferred.