ML Engineer

About CleanHarbors Clean Harbors Inc. (www.cleanharbors.com) is a NYSE listed US based $6.5 billion company. Clean Harbors was founded in 1980 near Boston by

Mr. Alan S. McKim . Everywhere industry meets environment, Clean Harbors is on-site, providing premier environmental, energy and industrial services. Clean Harbors employs a dedicated workforce of 25,000 employees and has over 750 service locations across the U.S., Canada and Mexico. Beyond addressing the environmental needs of its more than 300,000 customers, the Company has been on the front lines of addressing some of the largest emergency response events in North America of the past several decades including the BP Oil Spill in the Gulf of Mexico, the anthrax attacks in New York, the 2015 avian flu outbreak that devastated the poultry industry, Hurricanes Katrina, Rita and Sandy, and the oil pipeline breaks that affected the Yellowstone and Kalamazoo rivers, along with other major chemical releases into the environment. Clean Harbors India has been strategically established as the Global Capability Center (GCC) to serve our parent company. We take pride in serving some of the most tech savvy business stakeholders at Clean Harbors. The GCC employees form part of our globally integrated teams that provide cutting-edge IT solutions and production support across platforms. Our shared services teams work seamlessly with their global counterparts in providing critical 24x7 support in various functions including Finance, HR, Procurement, IT and Operations. Our aggressive growth plans open significant career advancement opportunities for our employees.

Job Title: Machine Learning Engineer Experience: 6+ Years

Location: Hyderabad – Work from Office Working Hours: 12.00pm to 9.00pm

Responsibilities

• Ensure that Health and Safety is the number one goal by following policies, processes, and always acting in a safe manner.
• 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 OnPrem 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.

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 VS Code 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.