Profile Overview

We are looking for a Machine Learning Engineer who can help us drive value for our clients through in a data driven approach. They will work with the Data Science team implement various data driven solutions developed for clients which help add relevant value. They will understand the data architecture of clients and help analysts to extract, process, and prepare data efficiently on a planned as well ad hoc basis. They will work with data scientists to implement solutions developed using the appropriate and latest technology frameworks by owning the architecture design and execution. They will help design and execute Unit and Integration User Acceptance Testing (UAT) frameworks before deploying and managing applications in production environments.

They will also help set up DevOps frameworks for clients.

Skills & Qualifications

• Ideal candidate should have a problem solving bent of mind, and had have worked in the Data Science field for 3 or more years
• Candidate should have had written robust, production-level code and deployed machine learning solutions / applications in real-world contexts, using modern cloud infrastructure and microservices components
• Candidate should be proficient in R and / or Python and / or SQL, particularly the various relevant machine learning libraries; knowledge of other languages such as Java, JS, C, C++ etc. would be considered a bonus
• Candidate should be proficient at understanding and conceptualizing data models / architectures (including various types of databases such as NoSQL), and developing and working with data pipelines based on the data models / architectures
• Candidate should have a deep understanding of technology components needed for deployment and management of machine learning solutions, such as cloud infrastructure ecosystems (AWS, Microsoft Azure, GCP), containerization (Docker, Kubernetes), API development (using frameworks such as Flask, Plumber, Django, Celery etc.), code versioning tools (GitHub, GitLab, CodeCommit etc.), Continuous Integration/Continuous Deployment (CI/CD)
• Experience of working with Big Data frameworks such as Hadoop, Spark etc. would be considered a bonus; experience of working with data science tools such as H2O.ai, Data Robot would be considered a bonus
• Candidate should have a basic understanding of various supervised and unsupervised learning algorithms used to solve most real-world problems
• Candidate should have excellent communication, comprehension, and critical thinking skills; collaborative nature would be considered a bonus
• Candidate should have a deep and nuanced understanding of technology, software, algorithms, and should be keen to stay up to date with the latest developments in the space across different service providers, open-source developments etc.