Senior Software Engineer (ML Ops) 

Key Skills

AWS, Azure, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, DevOps, Google Cloud Platform (GCP), Machine learning techniques, MLOps tools, Optimization, Software Development

Job Description

Soroco is on a mission to change how the world gets work done. Powered by multiple patents, its flagship product, the Scout AI model, generates a work graph - a map of hidden pains teams experience at work and their impact on business outcomes. Today, this graph drives productivity improvements in 100s of organizations globally, including several Fortune 500 companies. Soroco has been featured in Harvard Business Review, Forbes, Fortune, and was listed on Bloomberg’s list of ideas that defined 2022. With operations spanning Boston, London, and Bangalore, Soroco was founded by alumni of Harvard, MIT, and Carnegie Mellon.

Scout, our multi-modal transformer model, uncovers hidden workplace pains and their impact on business outcomes. By autonomously generating solutions and empathizing with teams, Scout enables enterprises to foster happier, more productive teams today. 

 Visit www.soroco.com to learn how we help teams discover their work graph. 

What we are looking for: -    

The ideal SSE for this role is passionate about working with and guiding a team to help create the infrastructure in Soroco that is responsible for deploying, updating, training, and running inference on our machine learning models in our product Scout. Knowledge of how to build and train common model tasks such as classification, summarization, question answering, and generation will help someone be successful in this role.  

The role purpose and scope: -   

The Senior Software Engineer (SSE) will drive the company’s technical growth and delivery by working with engineering teams. An SSE will typically work in, and mentor, product development to create and deliver complex proprietary systems.  

• Design, architect, and build high-quality scalable systems.  
• Review system design and architecture, code, and test plans.  
• Handle technical questions on our ML systems, debug hard technical issues with them.  
• Own projects end-to-end, including gathering requirements, solutioning and designing architecture, developing, testing, deploying, and maintaining systems.   
• Interact and collaborate with our high-quality technical team across India and the US.  

Experience and skills:-   

• 4-7 years of work experience in ML Lifecycle management.    
• Experience of designing and implementing cloud solutions, building MLOps on cloud (AWS, Azure, or GCP)  
• Build CI/CD pipelines orchestration by Azure DevOps.  
• Experience in various model optimization techniques like Quantization, Pruning etc.  
• Experience with Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.  
• Familiar with common model evaluation metrics to express the quality of pre-trained models and fine-tuned tasks.  
• Data science models testing, validation and tests automation.  

Bonus factors: -   

• Ability to learn and grasp any problem quickly.    
• Comfort and confidence in solving unstructured problems.    
• Appreciation for good design and architecture    
• Desire to design and build large, enterprise-grade software systems from scratch.   
• Ability to communicate and collaborate with experts in the field.