Senior ML Engineer @ Themathcompany

We are seeking a skilled MLOps Engineer to design, implement, and scale end-to-end machine learning operations (MLOps) platforms. This role bridges the gap between data science and software engineering, ensuring robust, efficient, and scalable deployment of machine learning models into production environments.

 

As Sr. ML Oops Engineer, you will be responsible for a wide range of engagements listed below:

Can build scalable MLOps platform and work with business architects to implement and expand the MLOps set up
Has worked on deploying an ML model to production and has worked on model monitoring, inferencing, drift concepts, feature stores etc. for a project
Has good understanding of how ML algorithms work and how to debug in case of any issues in the code
Has deployed an application using container and container orchestration
Manages conversation with the client stakeholders to understand the requirement and translate it into technical outcomes
Responsible for bridging the gap between machine learning and software engineering, focusing on the deployment, scaling, and management of machine learning models in production environments
Is a developer who is focused on streamlining the process of developing, deploying, and maintaining machine learning systems, ensuring they are efficient, scalable, and reliable
Has strong conceptual understanding of ML lifecycle and different ML algorithms
Has worked on at least one cloud platform and related ML as a Service platform

 

Roles & Responsibilities

Required Skills (Must have) Tech
Has strong understanding of DevOps practices and is skilled to develop end-end CI/CD pipelines
Has strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc.
Has experience in one of the ML as a service platform, such as Azure devops, DataikuI (or equivalent open-source)
Proficient in at least one programming language used in data engineering, such as Python
Has strong snowflake knowledge
Has worked on at least one cloud platform Non-tech
Business Understanding
Logical thinking and problem-solving skills along with an ability to collaborate
Ability to analyze problems and develop actionable and appropriate tactical plans quickly
Has good managerial skills and can lead a team
Good at verbal and written communication
Has good stakeholder management skills
Exercises independent judgment within defined practices and procedures to determine appropriate action
Demonstrated ability to provide mentorship to junior Required Skills (Good to have)

Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras
Proficiency in natural language processing (NLP) techniques and tools
Knowledge of computer vision and image processing algorithms
Experience with large-scale data processing and distributed computing frameworks like Apache Spark
Familiarity with data engineering and data manipulation techniques
Ability to work with big data technologies like Hadoop or Apache Kafka
Ability to communicate complex concepts to both technical and non-technical stakeholders