IN_Senior Associate_AWS DevOps Engineer_Data and Analytics_Adbvsiory_Hyderabad

Job Description & summary 

We are seeking a highly skilled Senior Associate specializing in Azure ML Ops to join our team. This is a full-time onsite position where you will play a pivotal role in driving machine learning operations using Azure technologies. With a strong focus on deployment, management, and optimization of ML models, this role is critical in ensuring the seamless integration of AI solutions into business processes. 

Responsibilities 

• Azure ML Ops Development: Design, implement, and maintain scalable machine learning operations using Azure ML services. 

• Model Deployment: Manage end-to-end deployment pipelines for machine learning models to ensure efficient production environments. 

• Optimization: Continuously monitor and optimize model performance, resource usage, and operational processes. 

• Collaboration: Work closely with data scientists, engineers, and business stakeholders to align ML solutions with organizational goals. 

• Documentation: Maintain comprehensive documentation of ML pipelines, workflows, and processes. 

• Problem-Solving: Proactively identify and resolve technical issues related to ML Ops. 

Work Environment 

• Type: Onsite work environment. 

• Commitment: Full-time employment with 100% resource allocation to this role. 

Why Join Us 

• Opportunity to work on cutting-edge machine learning technologies in a dynamic and collaborative environment. 

• Be part of a high-impact team that drives innovation and delivers tangible results. 

• Competitive salary and benefits package tailored to attract top-tier talent. 

Mandatory Skill sets 

• Proficiency in Azure ML Ops is mandatory. 

Preferred Skill sets: 

Experience in industries where machine learning plays a key role in decision-making and automation is highly valued. 

Years of Experience Required 

• Experience: 6–10 years of relevant experience in machine learning operations, with hands-on expertise in Azure ML Ops. 

Education Qualification 

• : While no specific educational qualification is required, a background in Computer Science, Data Science, Engineering, or related fields is preferred.