ML Engineer I

Role Description

Role Proficiency:

Under guidance from Senior ML Engineers develop ML models that provides accurate results with controls to solve the business problem identified using state of art techniques.

Outcomes

Executes relevant data wrangling activities related to the problem in order to create dataset
Conduct ML experiments to understand the feasibility and build baseline models to solve the business problem
Fine tune the baseline model for optimum performance
Test Models internally per acceptance criteria from business
Document relevant Artefacts for communicating with the business
Work with data scientists to deploy the models.
Work with product teams in planning and execution of new product releases.
Set OKRs and success steps for self/ team and provide feedback to goals for team members
Work with cross functional teams - business technology and product teams to understand the product vision; building ML solutions that provides value to the product

Measures Of Outcomes

Selection of the appropriate approach to the problem
Number of successful deployments of the model with optimised accuracy for baseline model
Adherence to project schedule / timelines
Personal and team achievement of quarterly/yearly objectives (OKR Assignments HIG Stretch goals)

Outputs Expected

Design to deliver Product Objectives:

Design ML solutions which are aligned to and achieve product objectives
Define data requirements for the model building and model monitoring; working with product managers to get necessary data

Updated on state of art techniques in the area of AI / ML :

Perform necessary research using the latest and state of art techniques to design scalable approaches
Explain the relevance of the technologies its pros and cons to the product team; enabling accurate design experiences

Skill Examples

Technically strong with the ability to connect the dots
Ability to communicate the relevance of technology to the stakeholders in a simple relatable language
Curiosity to learn more about new business domains and Technology Innovation
An empathetic listener who can give and receive honest thoughtful feedback

Knowledge Examples

Expertise in machine learning model building lifecycle

Clear understanding of various ML techniques with appropriate use to business problems
A strong background of statistics and Mathematics
Expertise in one of the domains – Computer Vision Language Understanding or structured data
Experience in executing collaboratively with engineering design user research teams and business stakeholders
Experience with data wrangling techniques preprocessing and post processing requirements for ML solutions
Good knowledge python and deep learning frameworks like Tensorflow Pytorch Caffe
Familiar with the machine learning model testing approaches
A genuine eagerness to work and learn from a diverse and talented team

Additional Comments

Role : ML Engineer I Band : B1 Location : Noida

Skills

Machine Learning,Software Engineering,Automation

Key Skills

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