Lead ML ops

Smarthyre

You will architect and scale AI solutions to deliver millions of customer predictions.

Compensation:

INR 5M - 6M/year

Location:

Remote: India

Mission of Smarthyre:

"Connecting startups with expert recruiters who understand their industry, tech, and culture—fast, efficient, and tailored."

What makes you a strong candidate:

• You have +5 years experience in Machine learning.
• You are proficient in scikit-learn, TensorFlow, Python, PyTorch, MLOps, Lambda architecture, Kubernetes, Keras.
• English - Conversational

Responsibilities and more:

Key Responsibilities:

* Lead MLOps Strategy: Architect and implement machine learning pipelines capable of handling millions of customer predictions.

* Build Scalable Infrastructure: Design and build highly scalable and reliable cloud-based infrastructure on AWS to support the training, deployment, and monitoring of machine learning models at scale.

* Cost and Resource Management: Optimize the use of cloud resources, ensuring cost-effective scaling while maintaining high availability and performance standards.

* CI/CD Pipeline Implementation: Develop and optimize CI/CD pipelines specifically for ML models, ensuring smooth transitions from development to production.

* Automation and Optimization: Implement automation tools for model lifecycle management, model retraining, and data pipeline management.

* Model Monitoring and Performance: Oversee the development and implementation of robust monitoring solutions to track model performance, identify issues, and ensure that models continue to meet business objectives.

* Collaboration: Work closely with cross-functional teams to ensure alignment between business needs, model performance, and infrastructure capabilities.

* Documentation: Document processes, methodologies, and findings comprehensively and ensure that all documentation is kept up-to-date and accurate.

* Innovation and Research: Stay up to date with new machine learning techniques, tools, and technologies, and apply this knowledge to improve existing solutions.

Qualifications:

* Bachelor's, Master's, or PhD in Computer Science, Engineering, AI, or a related field.

* At least 5+ years of experience in machine learning operations.

* Extensive experience deploying, managing, and scaling AI/ML workloads for large-scale data on AWS services such as EC2, SageMaker, Lambda, and other AWS offerings.

* Proficiency in Docker, Kubernetes, and container orchestration, with experience in deploying machine learning models in these environments.

* Proven track record in designing and implementing CI/CD pipelines for ML models.

* Experience in performance tuning, cost optimization, and managing resources in cloud-based environments.

* Strong understanding of machine learning concepts, including supervised and unsupervised learning and deep learning.

* Strong programming skills in Python, and experience with frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, and Keras.

* Excellent problem-solving and analytical skills.

* Strong communication and collaboration skills.

* Nice to have: Prior experience working in a fast-paced startup environment.