AI / Machine Learning - Architect
Eagle Genomics Ltd, India

Reporting to Director-Engineering, this role will see you taking responsibility in architecting, implementing, and managing enterprise solutions around big data especially in cloud environments with distributed, scalable, fault tolerant and secure machine learning or AI implementations

You will be responsible for

Acting as the design authority within the engineering team and the platform development for AI / ML solutions

Designing secure AI / ML solutions with advanced analytics for data-intensive systems

Defining best practices, patterns and architectural styles for machine learning solutions and implementation

Mapping the product vision to the required machine learning solutions and technologies by ensuring genericity, performance, reliability, resilience and security models and sources

Recommend and implement secure and regulatory compliant practices and solution

Working with SME’s and data scientists to apply and build the architecture for AI/ML solutions across the business by domain

Work with SME’s , Data Strategy amp; Data science team to align with the product roadmap

Working with the ML engineers in implementing the ML solutions.

Continuously searching for advanced technical and architectural methods, practices and technologies and champion these practices across the organization

Ability to mentor and build high performing ML engineers

Ability think and implement strategic and tactical solutions to business

Ability to work with multi-location and mulit-cultural, multi-department teams in collaborative fashion with excellent communication skills, ability to present concepts lucidly to both CxO team and Engineering team

1. 10+ years of hands on experience in software development
2. 4+ years deploying Machine Learning pipelines in large cloud based enterprise production systems
3. Graduation level education in Engineering or MCA or M Sc (Computers) . PG level certification on AI or ML is an added advantage.
4. Architect secure AI / ML solutions with advanced analytics (machine learning, deep learning and statistical models) to extract insights from Big data
5. Experience in Natural Language processing solutions.
6. Experience in designing the data visualization solutions to build interactive dashboards.
7. Documentation of process, product, and analytics models using technical writing standards.
8. Experience in Deep Learning skills ( Multi-layered perceptron (MLP) , Convolutional Neural Network (CNN) , Recurrent Neural Network (RNN) )
9. Experience in Unsupervised Machine Learning skills ( Clustering (Partitional, Hierarchical, Spectral) , Density Estimation: Parzen Window, Mixture of Gaussian , Item Set Mining (Market-Basket Analysis))
10. Experience in Supervised Machine Learning ( Decision Tree , Random Forest , Classification and predictive analysis )
11. Experience in Data visualization
12. Experience in python programming
13. Experience with public cloud platforms (Azure, AWS, GCP)
14. Experience in Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform
15. Strong hands-on experience with statistical packages and ML libraries (e.g. Python scikit learn, Spark MLlib, etc.)

Requirements

Experience of working in an Agile environment, particularly Scrum and JIRA

Knowledge/Experience of working with data visualisation libraries like D3, Cytoscape or similar is a big plus

Understanding of microservices is desirable

Expert in modern software development practices; solid experience using source control management (CI/CD)

Knowledge/Experience in federated learning

Job Rewards and Benefits