Machine Learning Engineer

Company: Hashone Careers

Website: Visit Website

Business Type: Startup

Company Type: Product

Business Model: B2B

Funding Stage: Pre-seed

Industry: Hospitality

Salary Range: ₹ 10-50 Lacs PA

Job Description

This is a permanent role with one of the product firm in Hospitality domain - A valued client of Hashone.

About The Role

We’re looking for a Machine Learning Engineer to join the Data Science & Machine Learning team at LodgIQ. Youll be responsible for building systems and frameworks that power our machine learning applications, working closely with team members to deploy and scale their solutions.

What You’ll Do

• Design and implement automated training and inference pipelines including building a model registry system to track model artifacts, versioning, and lineage
• Develop frameworks for on-demand model training and architect parallel processing systems for inference and event-driven architectures with multi-optimization support
• Design and develop sophisticated APIs that expose ML model capabilities
• Build ETL pipelines specifically tailored for ML applications and develop preprocessing frameworks
• Implement comprehensive monitoring solutions to identify system bottlenecks, optimize for enhanced scalability
• Create infrastructure for offline and online experimentation
• Build internal frameworks and tools that standardize ML workflows across the organization
• Stay current with developments in machine learning engineering and MLOps, evaluating and recommending new technologies and best practices
• Contribute to technical decision-making and architecture discussions to shape the future of our ML infrastructure
  
  

• Bachelors degree in Computer Science, Engineering, or related technical field (or equivalent experience)
• 3+ years of experience in software engineering with a focus on ML systems
• Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Experience building and maintaining production ML pipelines
• Proficiency with containerization technologies (Docker, Kubernetes)
• Experience with cloud platforms (AWS, GCP, or Azure) and their ML services
• Understanding of software engineering best practices including version control, CI/CD, and testing
• Experience with data processing frameworks
• Strong problem-solving skills and ability to work independently on complex technical challenges
• Excellent communication skills to collaborate with cross-functional teams