Machine Learning Engineer - 1
IntuitIndia15 hours ago
Full-timeEngineering, Information Technology
Track This Job
Add this job to your tracking list to:
- Monitor application status and updates
- Change status (Applied, Interview, Offer, etc.)
- Add personal notes and comments
- Set reminders for follow-ups
- Track your entire application journey
Save This Job
Add this job to your saved collection to:
- Access easily from your saved jobs dashboard
- Review job details later without searching again
- Compare with other saved opportunities
- Keep a collection of interesting positions
- Receive notifications about saved jobs before they expire
AI-Powered Job Summary
Get a concise overview of key job requirements, responsibilities, and qualifications in seconds.
Pro Tip: Use this feature to quickly decide if a job matches your skills before reading the full description.
Overview
Come join our collaborative and creative group of AI scientists and machine learning engineers for Intuit Foresight! As AI Scientist, you'll get to design and build next generation AI systems that directly impact our customers deploying machine learning models in AI-native apps, using everything from analytical
algorithms to deep learning and generative AI. We're excited for you to join us and do some seriously awesome work.
The team is at the heart of building next generation AI systems and algorithms using state of the art algorithms, platform infrastructure and massive datasets unique to Intuit. Building these AI and GenAI systems involve the use of large language models, reinforcement learning, human prefernce learning, forecasting, optimization and in-depth knowlege of using experimentation methods and AI evaluations.
Responsibilities
Come join our collaborative and creative group of AI scientists and machine learning engineers for Intuit Foresight! As AI Scientist, you'll get to design and build next generation AI systems that directly impact our customers deploying machine learning models in AI-native apps, using everything from analytical
algorithms to deep learning and generative AI. We're excited for you to join us and do some seriously awesome work.
The team is at the heart of building next generation AI systems and algorithms using state of the art algorithms, platform infrastructure and massive datasets unique to Intuit. Building these AI and GenAI systems involve the use of large language models, reinforcement learning, human prefernce learning, forecasting, optimization and in-depth knowlege of using experimentation methods and AI evaluations.
Responsibilities
- Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
- Work with AI scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
- Partner with AI 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.
- 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, Torch, 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
- Minimum experience of 1 year on relevant technologies
Key Skills
Ranked by relevanceReady to apply?
Join Intuit and take your career to the next level!
Application takes less than 5 minutes