Company Overview

10Pearls is an end-to-end digital technology services partner helping businesses utilize technology as a competitive advantage. We help our customers digitalize their existing business, build innovative new products, and augment their existing teams with high-performance team members. Our broad expertise in product management, user experience/design, cloud architecture, software development, data insights and intelligence, cyber security, emerging tech, and quality assurance ensures that we are delivering solutions that address business needs. 10Pearls is proud to have a diverse clientele including large enterprises, SMBs, and high-growth startups. We work with clients across industries, including healthcare/life sciences, education, energy, communications/media, financial services, and hi-tech. Our many long-term, successful partnerships are built upon trust, integrity, and successful delivery and execution.

Role
We are seeking a skilled and experienced MLOps Engineer to join our team. The ideal candidate will be responsible for managing the entire lifecycle of machine learning models, from development to production deployment and maintenance.

Responsibilities

• Support and coordinate technical and business aspects of software development activities, including requirement analysis, design and implementation of applications 
• As a seasoned resource and principal developer in project teams, provide expert opinion and guidance on business & technical matters
• Takes on additional responsibilities as and when required and encourage cohesion & team building 
• Acts as a point of contact for technical issues for specific work streams across multiple projects 
• Proactively plan and strategize with team on possible issues and suggest workable alternatives 
• Mentors the other technical staff, assists them where needed and leads the effort in resolving technical challenges 
• Guide and participate in recruiting best technical talent for the team

Requirements

• Proficiency in Python and/or R - Strong knowledge of containerization tools (Docker, Kubernetes)
• Experience with CI/CD tools (Jenkins, GitLab CI) - Solid understanding of machine learning algorithms and techniques 
• Familiarity with machine learning frameworks (PyTorch, cuML, scikit-learn, etc.) 
• Experience with cloud platforms (AWS, GCP, Azure) 
• Knowledge of infrastructure-as-code tools (Terraform, CloudFormation) 
• Proficiency in software engineering practices (version control, code reviews, testing) 
• Experience with version control systems (Git) 
• Familiarity with monitoring and logging tools (Prometheus, Grafana) 
• Experience with experiment tracking tools (Weights & Biases, MLflow)