About the role

Senior Machine Learning Engineer at TheAppLabb designing and deploying production-grade ML systems with a focus on AI features and cloud infrastructure.

Responsibilities

Architect, build, and deploy end-to-end ML pipelines for production workloads.
Design scalable and resilient ML systems using frameworks such as PyTorch and TensorFlow.
Operationalize ML models using containerized environments (Docker, Kubernetes) and orchestration tools like Cloud Composer (Airflow) on Cloud Environments (AWS, Azure, GCP).
Integrate ML solutions with data warehouses like Snowflake, DataBricks or BigQuery for training and inference at scale.
Collaborate with cross-functional teams to define requirements and deliver impactful AI features.
Ensure CI/CD best practices for ML deployments, including monitoring, versioning, and rollback strategies.
Optimize model performance and system efficiency to meet production level SLAs.

5+ years of experience designing and deploying production-grade ML systems at scale.
Strong knowledge of PyTorch, TensorFlow, and modern ML model lifecycle management.
Hands-on experience with AWS, Azure or GCP.
Expertise in Kubernetes, Docker, and workflow orchestration tools such as Cloud Composer or Airflow.
Proficiency with SQL and experience working with Snowflake, DataBricks or BigQuery.
Solid understanding of MLOps practices: reproducibility, model monitoring, automated retraining.
Strong programming skills in Python; experience with LangChain, LangGraph, or related frameworks is a plus.
Excellent communication and leadership skills, with a proven ability to work in collaborative teams.

Competitive salary
Opportunities for career growth and continuous learning.
Acknowledge and recognize employee efforts by having awards (Employee of the month, Employee with Most Growth, Leadership Award etc.)
We encourage a healthy lifestyle by incorporating fitness challenge incentives in our Company.