935 IT & Software Developer jobs in the US
Software Engineer, Generative AI/ML Frameworks
$141,000 - 202,000
Google
Amphitheatre Parkway 1600, Mountain View
$141,000 - 202,000
Requirements
Must:
- Bachelors degree or equivalent practical experience.
- Minimum of 2 years in software development in one or more programming languages or 1 year with an advanced degree.
- At least 1 year of experience with machine learning infrastructure, encompassing model deployment, evaluation, optimization, data processing, and debugging.
- Familiarity with advanced GenAI methodologies (such as LLMs, multi-modal, large vision models) or related concepts (like language modeling and computer vision).
- Proficiency in applying machine learning algorithms and techniques using frameworks (e.g., Jax, PyTorch, Triton, etc.).
- Preferred: Masters degree or PhD in Computer Science or similar technical domains.
- Preferred: 2 years of experience with data structures and algorithms.
- Preferred: Experience in developing accessible technologies.
Technologies
AI
Machine Learning
PyTorch
UX UI Design
Responsibilities
- Write and develop product or system code.
- Address product or system issues, resolving them by analyzing their sources and their effects on hardware, network, or service operations.
- Implement GenAI solutions, employ ML infrastructure, and assist in data preparation, optimization, and performance improvement.
- Design and create multi-agent solutions to significantly reduce time during complex ML training pipeline migrations, collaborating with ML infrastructure teams and specific product areas like YouTube and Search.
- Contribute to the frameworks roadmaps, implementing ML model architectures, post-training techniques, and inference optimizations.
Description
We are Googles software engineers, dedicated to developing cutting-edge technologies that transform the way billions of users connect, explore, and engage with information. Our innovative products cater to extensive data handling, transcending traditional web search. We are on the lookout for engineers who can bring diverse insights from fields such as information retrieval, distributed computing, AI, and more. As a software engineer with us, you will focus on vital projects that meet Googles dynamic needs, with chances to navigate different teams as our fast-paced environment evolves. The AI and Infrastructure team is pioneering new capabilities, delivering innovation to Google customers and users with unmatched efficiency and speed. Our roles play a crucial part in advancing AI models and providing the robust computing resources necessary for developing future technologies. The US base salary for this full-time position is between $141,000 and $202,000, plus bonuses, equity, and benefits. Salary specifics depend on role, level, and location, and further details can be discussed during the hiring process.
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You can find Machine Learning Engineer salaries in the United States here.
How many Machine Learning Engineer jobs are in the United States?
Currently, there are 935 ML, AI openings. Check also: TensorFlow jobs, Python jobs, Computer-Vision jobs - all with salary brackets.
Is the US a good place for Machine Learning Engineers?
The US is one of the best countries to work as a Machine Learning Engineer. It has a vibrant startup community, growing tech hubs and, most important: lots of interesting jobs for people who work in tech.
Which companies are hiring for Machine Learning Engineer jobs in the United States?
Sched LLC, Jump, Snaplii, D3 Security Management Systems, DataAnnotation, DefenTec, Accenture Federal Services among others, are currently hiring for ML, AI roles in the United States.
The company with most openings is DataAnnotation as they are hiring for 19 different Machine Learning Engineer jobs in the United States. They are probably quite committed to find good Machine Learning Engineers.
The company with most openings is DataAnnotation as they are hiring for 19 different Machine Learning Engineer jobs in the United States. They are probably quite committed to find good Machine Learning Engineers.