Join Skild AI as a Software Engineer to optimize AI inference for robotic systems, enhancing their performance and adaptability.
Posted by employer 1 year ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
AI in the day-to-day
You will be responsible for optimizing AI inference processes from lightweight to billion-parameter models.
Requirements
- Experience
- 3+ years
- Education
- Bachelor's degree
Not disclosed in this posting: work arrangement, visa sponsorship.
Joblaze summary
In this role, the Software Engineer focuses on optimizing AI inference processes to enhance the performance of robotic systems in real-world applications. Key skills include proficiency in low-level programming languages and deep learning frameworks, alongside a solid understanding of machine learning techniques and systems concepts. This position is ideal for candidates with at least three years of industry experience, particularly those who thrive in innovative environments and are eager to tackle complex challenges in AI deployment.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Skild AI's career page.
- Skild AI has 63 other open roles including Manufacturing Engineering Manager, Senior Electrical Engineer , Operations Program Manager – Data Infrastructure - India.
- 6527 active Python roles on Joblaze right now.
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- Salary band is below the typical range for AI/ML roles (median ~$188,000).
- Pays more than 8% of the 3228 salaried Python roles we track (median $160,000). See Python salary trends
Quick facts
- What's the salary range?
- Skild AI lists $100,000–$300,000 for this role.
- How much experience is required?
- At least 3 years of relevant experience for this Software Engineer, AI Inference role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: C++, CUDA, Go, JAX, PyTorch, Python.
- What seniority level is this role?
- Skild AI targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Software Engineer, AI Inference role at Skild AI.
From the original posting
Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are looking for a Software Engineer to work at the forefront of deploying our cutting-edge AI models, enhancing the performance and capabilities of our embodied systems. You will be responsible for optimizing AI inference processes from lightweight to billion-parameter models, ensuring our robots operate with unmatched efficiency and intelligence in real-world environments. You will work at the intersection of systems and machine learning, directly contributing to making our AI models more powerful and adaptive by ensuring consistent performance in light of variable and perhaps unforeseen compute and hardware constraints.
Responsibilities
- Develop and optimize runtime AI inference pipelines for real-world robotic deployment.
- Build infrastructure, frameworks, and tooling to enable reliable integration of models into robotic systems and informative analysis of production models to drive the direction of architecture choice and deployment system design.
- Formulate specialized optimization solutions for various inference paradigms and scenarios (autoregressive models, denoising models, hierarchical models, state machines, multi-agent systems, cloud-based inference).
- Adapt optimization solutions to various compute, hardware, and networking constraints.
Preferred Qualifications
- BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
- Minimum of 3 years of industry experience.
- Proficiency developing in low-level systems languages (C, C++, Rust, Go), Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
- Deep understanding and practical experience with low-level systems concepts (multithreading, networking, embedded systems, memory management).
- Experience with CUDA.
- Deep understanding of state-of-the-art machine learning techniques and models.
- Experience optimizing various machine learning architectures.
- Experience with machine learning compilers.
- Experience optimizing model inference for robotic systems deployment.
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