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Contract Audio Machine Learning Jobs in Spanaway, WA

Account Executive

Seattle, WA · On-site

$150K - $160K/yr

TigerGraph is a platform for advanced analytics and machine learning on connected data. TigerGraph ... Experience formulating and selling large contracts Qualifications * Track record of closing sales ...

Senior Applied Scientist

Seattle, WA · On-site

$140K - $175K/yr

We operate at the intersection of machine learning, LLM-powered systems, and cloud-scale ... Experience with speech-to-text systems or real-time audio/voice processing. * Familiarity with ...

Senior Applied Scientist

Seattle, WA · On-site

$140K - $175K/yr

We operate at the intersection of machine learning, LLM-powered systems, and cloud-scale ... Experience with speech-to-text systems or real-time audio/voice processing. * Familiarity with ...

Machine Operator

Auburn, WA · On-site

$23 - $30/hr

The company offers a contract-to-hire path, creating a clear opportunity to move into a stable ... learning and advancement in a collaborative, team-oriented environment. Work Environment You will ...

The company offers a contract-to-hire path, creating a clear opportunity to move into a stable ... learning and advancement in a collaborative, team-oriented environment. Work Environment You will ...

Machine Operator

Auburn, WA · On-site

$23 - $28/hr

Demonstrate dependability, drive, and ambition by learning new machining processes and equipment ... The organization operates as a contract-to-hire environment, creating a clear pathway from ...

The team environment encourages learning from experienced machinists, building your skills in CNC ... Job Type & Location This is a Contract to Hire position based out of Kent, WA. Pay and Benefits The ...

Showing results 21-40

Contract Audio Machine Learning information

See Spanaway, WA salary details

$32

$52

$105

How much do contract audio machine learning jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for contract audio machine learning in Spanaway, WA is $52.18, according to ZipRecruiter salary data. Most workers in this role earn between $43.85 and $54.09 per hour, depending on experience, location, and employer.

What is the difference between Contract Audio Machine Learning vs Contract Data Scientist?

AspectContract Audio Machine LearningContract Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related field; experience with machine learning frameworksDegree in Data Science, Statistics, or related; strong programming skills
Work EnvironmentFocus on audio data, signal processing, and machine learning modelsBroader data analysis, statistical modeling, and data visualization
Industry UsageMedia, entertainment, speech recognition, audio analysisFinance, healthcare, marketing, and various industries requiring data insights

Contract Audio Machine Learning specialists focus on developing models specifically for audio data, while Contract Data Scientists handle a wider range of data types and analysis tasks. Both roles require strong technical skills, but their focus areas and industry applications differ.

What cities near Spanaway, WA are hiring for Contract Audio Machine Learning jobs?

Cities near Spanaway, WA with the most Contract Audio Machine Learning job openings:

Applied Scientist Intern - Trust and Safety (Multimodal Foundation Model) - Global Frontier Tech Rec

TikTok

Seattle, WA • On-site

$17 - $22.75/hr

Internship

Medical, Life

Re-posted 22 days ago


TikTok rating

8.2

Company rating: 8.2 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

107th of 245 rated software companies


Job description

Responsibilities
We are looking for talented individuals to join our team in 2027. As a intern, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company. Successful candidates must be able to commit to an onboarding during the summer 2027. Please state your availability clearly in your resume. About the team Our Trust and Safety team is fast growing and responsible for building machine learning models and systems to protect our users from the impact of negative content. Our mission is to protect billions of users and publishers across the globe every day. We embrace state-of-the-art machine learning technologies and scale them to moderate the tremendous amount of data generated on the platform. With our team's continuous efforts, TikTok can provide the best user experience and bring joy to everyone in the world. Project Overview, Challenges & Value With the rapid development of AIGC and the globalization of content ecosystems, content moderation faces three major challenges: evolving policies, surging complexity in multilingual and multimodal content, and upgraded generative adversarial attacks. The traditional "perception - classification" paradigm has reached its limit. This topic focuses on two frontier directions: (1) Multimodal moderation foundation model: We study large-scale MoE architecture training and routing optimization, cross-modal alignment and reasoning for multimodality (text/image/video/audio), Unified Understanding & Generation, and high-quality synthetic data generation for moderation scenarios (self-play / adversarial augmentation). (2) Agentic moderation system: Drawing on advanced agent learning paradigms, it uses reinforcement learning to enhance the agent's multi-step decision-making capabilities. It dynamically builds moderation context and integrates a flexible tool ecosystem, enabling autonomous planning, tool collaboration, and interpretable closed-loop reasoning. This drives a paradigm shift from passive classification to proactive intelligent decision-making in moderation. Key challenges include: 1. MoE-based multimodal safety foundation model: training stability and routing optimization for large-scale sparse MoE, cross-modal token alignment, and unified architecture design for understanding and generation 2. RL-driven agentic decision-making: end-to-end training of agent multi-step reasoning and tool-call strategies based on GRPO/PPO, overcoming bottlenecks in sample efficiency and training stability 3. Context engineering and tool collaboration: dynamic context assembly, MCP-based tool ecosystem construction, multi-source heterogeneous evidence fusion, and GraphRAG strategy retrieval 4. Generalization and adversarial robustness: generalization across 200+ languages/strategies, adversarial detection of AIGC content, and design of multi-dimensional reward signals for few-shot scenarios Project Value: 1. Technological leadership: The integration of RL, Agentic, and multimodal foundation models represents the frontier of AI today. This topic pioneers their application to large-scale content moderation scenarios, with unique advantages in data volume and real-world feedback loops that are impossible to reproduce in pure academic settings. 2. Business value: Serving content safety for billions of users globally and driving the evolution of moderation from dependance on humans and external APIs towards fully automated agentic moderation. This can directly reduce costs by hundreds of millions of US dollars while improving moderation consistency and response speed. 3. Industry leadership: Mature RL-driven agentic moderation systems do not yet exist in the industry. This topic could hopefully define the technological paradigm for this direction and produce research outcomes with significant industry influence.
Qualifications
Minimum Qualifications - Currently pursuing a PhD in Computer Science, Data Science, Artificial Intelligence, or a related field - Proficiency in programming languages such as Python, Rust, or C++ and a track record of working with deep learning frameworks (e.g., pytorch, deepspeed, megatron, vllm, etc.). - Strong understanding of distributed computing framework & performance tuning and verification for training/finetuning/inference; Preferred Qualifications - Excellent problem-solving skills and a creative mindset to address complex AI challenges. Demonstrated ability to drive research projects from idea to implementation, producing tangible outcomes. - Published research papers or contributions to the LLM community would be a significant plus. - Experience with inference tuning and Inference acceleration. Have a deep understanding of GPU and/or other AI accelerators, experience with large scale AI networks, pytorch 2.0 and similar technologies. - Experience with evaluation of AI systems, LLM application & agent development is desirable. - Strong understanding of cutting-edge LLM research (e.g., long context, multi modality, alignment research, agent ecosystem, etc.) and possess practical expertise in effectively implementing these advanced systems as a plus - Being familiar with PEFT, RL, MoE, CoT or Langchain is a plus.
Job Information
[For Pay Transparency]Compensation Description (Hourly) - Campus Intern
The hourly rate range for this position in the selected city is $71.25- $71.25.
Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
For Los Angeles County (unincorporated) Candidates:
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.
About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
TikTok Accommodation
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at

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