Senior Machine Learning Engineer - Data Modeling (4-6 yrs)

Position Title : Senior Machine Learning Infrastructure Engineer

Location : Chennai, Bangalore, Pune, Coimbatore

Experience : 4 to 6 Years

Position Summary :

We are seeking a Senior Machine Learning Infrastructure Engineer to lead the design, implementation, and optimization of end-to-end ML infrastructure. You will be responsible for providing technical leadership to a team of ML engineers and driving best practices for model development, deployment, and scaling.

This role involves collaborating closely with data scientists, software engineers, and other stakeholders to build high-quality, scalable, and reliable ML systems. Your work will include designing automated CI/CD pipelines, optimizing model performance, and leveraging cloud and containerization technologies for seamless deployment.

Responsibilities :

End-to-End ML Infrastructure :

- Lead the implementation of a cutting-edge ML infrastructure, ensuring best practices, scalability, and high-quality standards across the development lifecycle.

Technical Leadership & Mentorship :

- Provide exceptional technical guidance, mentorship, and leadership to a team of machine learning engineers, fostering continuous learning and innovation.

Project Ownership & Stakeholder Collaboration :

- Take ownership of critical projects, providing project leadership and ensuring successful delivery.

- Engage with stakeholders to understand their needs and navigate complex, conflicting goals.

Data Pipeline Optimization :

- Work closely with data scientists to translate complex model requirements into optimized data pipelines that ensure impeccable data quality, processing, and integration.

Model Versioning & Tracking :

- Establish best practices for model versioning, experiment tracking, and model evaluation, ensuring transparency and reproducibility.

Model Deployment & Scalability :

- Architect model deployment strategies using Docker for containerization and Kubernetes for orchestration to ensure scalability and reliability.

Automated CI/CD Pipelines :

- Design and engineer automated CI/CD pipelines to facilitate model deployment, monitoring, and continuous optimization.

Performance Optimization :

- Define performance benchmarks and continuously optimize models and infrastructure to achieve peak efficiency, scalability, and robustness.

Emerging Technologies :

- Stay updated with industry trends and emerging technologies, integrating advancements into the ML ecosystem.

Qualifications :

Extensive Experience :

- Proven experience in orchestrating the development of end-to-end machine learning infrastructure for large-scale applications.

Leadership Experience :

- Track record of leading technical teams to deliver high-quality, innovative ML solutions.

Problem-Solving & Analytical Skills :

- Strong problem-solving abilities and passion for solving complex technical and business challenges.

Mastery of ML Frameworks :

- Expertise in TensorFlow, PyTorch, or equivalent, along with strong Python programming skills.

Containerization & Orchestration :

- Deep knowledge of Docker and Kubernetes for deploying and managing complex ML applications.

Cloud Platforms :

- Expertise in cloud platforms like AWS or Azure, leveraging cloud-native services to build robust ML infrastructure.

DevOps & CI/CD :

- Experience integrating DevOps practices, continuous integration, and continuous deployment (CI/CD) pipelines.

Collaboration Skills :

- Excellent communication and interpersonal skills with the ability to work effectively in a team-oriented environment