Senior Machine Learning Engineer

Intuit Inc.; Bengaluru; On-site; USD 1,363 - 2,044; Full time

Job summary

An established industry player is seeking a skilled data scientist to join their dynamic team of AI experts. In this role, you will be instrumental in developing and deploying data science models at scale, leveraging cutting-edge tools and techniques. You will collaborate closely with data scientists and product managers to refine features and ensure models are machine learning ready. Your expertise in data wrangling, statistical analysis, and machine learning principles will be key to driving impactful insights and innovations. If you are passionate about data science and eager to work with a vibrant team, this opportunity is perfect for you.

Qualifications

• Minimum 5 years of experience in data science and machine learning.
• Strong knowledge of Python and relevant data science frameworks.

Responsibilities

• Discover and clean data sources to make them machine learning ready.
• Collaborate with data scientists to build and deploy models.
• Run A/B tests and perform statistical analysis on model performance.

Skills

Data Wrangling

Feature Engineering

Model Development

Statistical Analysis

Machine Learning Principles

Data Querying (SQL)

Deep Learning Architectures

GPU Acceleration

Education

BS in Computer Science

MS in Computer Science

PhD in Computer Science

Tools

Python

Scikit

NLTK

Numpy

Pandas

TensorFlow

Keras

R

Spark

Git

AWS

GCP

Job description

In this role, you’ll be embedded inside a vibrant team of AI scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics. Following are the Responsibilities and Qualifications sought.

Responsibilities

• Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
• Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
• Partner with data scientists to understand, implement, refine and design machine learning and other algorithms.
• Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
• Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.
• Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.

Qualifications

• BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
• Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
• Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
• Understand machine learning principles (training, validation, etc.).
• Knowledge of data query and data processing tools (i.e. SQL).
• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
• Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
• Mathematics fundamentals: linear algebra, calculus, probability.
• Interest in reading academic papers and trying to implement state-of-the-art experimental systems.
• Experience using deep learning architectures.
• Experience deploying highly scalable software supporting millions or more users.
• Experience with GPU acceleration (i.e. CUDA and cuDNN).
• Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP).
• Minimum experience of at least 5 years on relevant technologies.