Machine Learning Engineer
Melbourne, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Melbourne, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Melbourne, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Boca Raton, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Boca Raton, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Miami, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Miami, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Hialeah, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Hialeah, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Orlando, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
Orlando, FL ยท On-site
This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...
This role is designed for a high-drive engineer with a deep foundation in machine learning and its practical application to complex signal processing and SIGINT (Signals Intelligence). You will be ...
This role is designed for a high-drive engineer with a deep foundation in machine learning and its practical application to complex signal processing and SIGINT (Signals Intelligence). You will be ...
Sarasota, FL ยท On-site
This role is designed for a high-drive engineer with a deep foundation in machine learning and its practical application to complex signal processing and SIGINT (Signals Intelligence). You will be ...
Sarasota, FL ยท On-site
This role is designed for a high-drive engineer with a deep foundation in machine learning and its practical application to complex signal processing and SIGINT (Signals Intelligence). You will be ...
Sarasota, FL ยท On-site
This role is designed for a high-drive engineer with a deep foundation in machine learning and its practical application to complex signal processing and SIGINT (Signals Intelligence). You will be ...
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Sarasota, FL ยท On-site
This role is designed for a high-drive engineer with a deep foundation in machine learning and its practical application to complex signal processing and SIGINT (Signals Intelligence). You will be ...
Tampa, FL ยท On-site +1
AI Machine Learning Scientist AI Machine Learning Scientist Location: This role requires associates ... Help build reusable AI capabilities, evaluation frameworks, and governance processes that ensure AI ...
Tampa, FL ยท On-site +1
AI Machine Learning Scientist AI Machine Learning Scientist Location: This role requires associates ... Help build reusable AI capabilities, evaluation frameworks, and governance processes that ensure AI ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Search relevance and ranking - Improving search relevance by incorporating signals from various ...
$22K - $31.7K
16% of jobs
$36.1K is the 25th percentile. Wages below this are outliers.
$31.7K - $41.3K
19% of jobs
$41.3K - $51K
13% of jobs
The median wage is $52.1K / yr.
$51K - $60.6K
14% of jobs
$60.6K - $70.3K
10% of jobs
$74.7K is the 75th percentile. Wages above this are outliers.
$70.3K - $79.9K
6% of jobs
$79.9K - $89.6K
4% of jobs
$89.6K - $99.2K
5% of jobs
$99.2K - $108.9K
4% of jobs
$108.9K - $118.5K
8% of jobs
$118.5K - $128.2K
0% of jobs
$22K
$63.1K
$128.2K
To thrive in Audio Signal Processing Machine Learning, you need a strong background in digital signal processing, machine learning, mathematics, and programming (typically Python, MATLAB, or C++), often supported by a relevant degree in electrical engineering, computer science, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), audio processing libraries (like Librosa), and experience using version control systems are highly valuable. Creative problem-solving, strong analytical thinking, and effective collaboration skills will set you apart in this technical and interdisciplinary field. These skills are essential for developing innovative audio processing solutions that meet practical needs in industries like telecommunications, music, and voice recognition.
An Audio Signal Processing Machine Learning job involves applying machine learning techniques to analyze, process, and enhance audio signals. This includes tasks like speech recognition, music classification, noise reduction, and sound synthesis. Professionals in this role work with digital signal processing (DSP), deep learning models, and frameworks like TensorFlow or PyTorch to develop audio-based AI applications. They often collaborate with researchers, engineers, and data scientists to improve audio-related technologies in industries such as telecommunications, media, and healthcare.
Professionals in Audio Signal Processing Machine Learning roles often work on projects such as developing speech recognition systems, designing audio enhancement algorithms, or building music information retrieval solutions. Daily responsibilities may include data preprocessing, feature extraction, model design and training, and evaluating algorithm performance using large audio datasets. Collaboration with software engineers, product managers, or hardware teams is common, as solutions typically need to be integrated into larger products or platforms. These roles also require keeping up with the latest research and continuously tuning models for improved accuracy and efficiency. This variety ensures a dynamic work environment where innovation and technical growth are encouraged.
Full-time
Posted 8 days ago
About Us
We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.
We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.
What You'll Be Working On
You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments โ and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.
Must-Have Skills
3+ years of ML engineering experience โ model training, fine-tuning, or post-training pipelines in research or production
Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)
Hands-on experience with LLM post-training โ SFT, RLHF, PPO, DPO, or reward model training โ and understanding of how training data quality affects model behavior
Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives
Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)
Solid understanding of evaluation methodology โ held-out sets, benchmark design, avoiding train/eval contamination