- Is an SME in Machine Learning
- Able to tech lead initiatives for Data Science and ML: task breakdown, project design, delegation, and review
- Produce "clean" and well-structured code, with detailed specifications. This means that your code is well-designed, simple, readable properly documented, well-tested, and is production ready
- Mentors junior engineers
- Improves foundational processes and promotes best practices
- Contributes to the hiring and interview process
- Customer driven: Attentive to our customers' needs and strive to deliver a seamless and delightful customer experience
- High Impact: Understand what the most important customer metrics are and find the right direction to impact them by working with Product Managers and through multiple agile iterations
- Ownership: Have ownership of projects from start to finish, make sure to have high quality implementation, and have urgency to move fast and find the most efficient ways to iterate
- Team Mentorship & Sharing: Able to up-level the team by sharing knowledge and best practices with the engineering team
- Agility: Organised and able to effectively plan and breakdown large projects into smaller tasks that are easier to estimate and deliver. Can lead fast iterations
- Speak and Act Courageously: Isn't afraid to fail, isn't afraid to challenge status quo, speak up for contrarian view
- Focus and Move with Urgency: Able to prioritise for impact and move fast to deliver experiments and features to achieve customer value
- Intelligence: Learns quickly. Demonstrates ability to quickly and proficiently understand and absorb new codebase and frameworks
- Bachelors or Masters in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
- 5+ years of experience building Machine Learning or AI systems
- Experience deploying and managing machine learning models in the cloud
- Strong analytical and problem-solving skills
- Proven software engineering skills in production environment, primarily using Python
- Experience with Machine Learning software tools and libraries (e.g., Scikit-learn, TensorFlow, Keras, PyTorch, etc.)
- Experience with Databricks, Google Cloud Platform, Snowflake, mlflow, and Airflow
- Experience with Large Language Models (LLMs) or similar technologies
- Experience with one or more of the following: natural language processing, deep learning, recommendation systems, search relevance & ranking, and speech-to-text conversion.
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Machine Learning Engineer - india, India - Apollo
Description
Responsibilities:
Competencies:
Required Qualifications:
Preferred Qualifications:
