SSE/Lead AI/ML Engineer

What Youll Be Doing

Backend & ML System Development

• Design, develop, and maintain scalable backend services using Python.
• Integrate ML models into production systems via REST/gRPC APIs and inference pipelines.
• Build reusable, efficient, and testable modules for ML workflows.
• Optimize model inference performance and reduce latency in production environments.

Machine Learning Engineering

• Collaborate with Data Scientists to deploy, monitor, and improve ML models.
• Work on feature engineering pipelines and data preprocessing workflows.
• Implement model versioning, logging, monitoring, and evaluation frameworks.
• Ensure reliability, scalability, and reproducibility of ML systems.

System Design & Architecture

• Contribute to system design discussions and architectural decisions.
• Design modular and extensible services that support AI/ML-driven features.
• Write clean, maintainable, and well-documented code.

Engineering Excellence

• Implement unit tests, integration tests, and automation pipelines.
• Use Git, CI/CD, and DevOps practices for reliable deployments.
• Participate in code reviews and mentor junior engineers when needed.
• Continuously explore improvements in performance, scalability, and security.

What Were Looking For

Core Technical Skills

• Strong proficiency in Python.
• Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Solid understanding of ML fundamentals (supervised/unsupervised learning, evaluation metrics, optimization basics).
• Experience building APIs using FastAPI / Flask / Django.
• Familiarity with SQL/NoSQL databases.
• Understanding of containerization tools like Docker.

Good to Have

• Exposure to LLM-based applications or agentic workflows.
• Experience with cloud platforms (AWS/GCP/Azure).
• Knowledge of MLOps practices (model monitoring, versioning, experiment tracking).
• Experience with distributed systems or data processing frameworks.