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Ml Data Associate Jobs in Bothell, WA (NOW HIRING)

... ML frameworks. This role involves driving the full software lifecycle, applying cloud-native ... Comprising software engineers, data scientists, and machine learning experts, the team drives ...

Source and recruit candidates for technical and strategic roles across AI/ML engineering, platform ... Build and maintain candidate pipelines in the ATS (Ashby), keeping data clean, status current, and ...

... For data Science/Data Analyst/AI/Machine learning Positions Preferred SKILLS Associate or Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering ...

... For data Science/Data Analyst/AI/Machine learning Positions REQUIRED SKILLS Associate or Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering ...

... data Science/Data Analyst/AI/Machine learning Positions Preferred SKILLS Associate or Bachelor's degree or Master's degree in Computer Science, Computer Engineering, Electrical Engineering ...

Machine Learning Engineer II

Seattle, WA

$111K - $151K/yr

... number of AI/ML systems to production, including machine learning systems, data pipelines ... More than 9,000 associates in 30+ offices around the world help our clients and each other grow and ...

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Ml Data Associate information

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$65.4K

$77.3K

$146.6K

How much do ml data associate jobs pay per year?

As of Jun 19, 2026, the average yearly pay for ml data associate in Bothell, WA is $77,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,100.00 and $67,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an ML Data Associate, and why are they important?

To thrive as an ML Data Associate, you need strong analytical skills, attention to detail, and a solid understanding of data annotation or labeling, often supported by a degree in a technical field. Familiarity with data labeling tools, basic programming (such as Python), and experience working with machine learning platforms are typically required. Excellent communication, problem-solving abilities, and the capacity to work efficiently in teams are important soft skills. These skills ensure high-quality, accurately labeled datasets that are essential for training effective machine learning models.

What are ML Data Associates?

ML Data Associates are professionals who support machine learning projects by preparing, labeling, and validating data used to train and evaluate algorithms. They often work with large datasets, ensuring data quality and accuracy, and may use specialized tools to annotate images, text, or audio. Their work is essential for enabling machine learning models to learn from high-quality, well-structured data, and they often collaborate with data scientists and engineers to optimize data pipelines.

What is the difference between Ml Data Associate vs Data Analyst?

AspectML Data AssociateData Analyst
Required CredentialsTypically a degree in computer science, data science, or related field; familiarity with machine learning conceptsUsually a degree in statistics, mathematics, or business analytics; strong Excel and data visualization skills
Work EnvironmentTech companies, AI startups, or organizations focusing on machine learning projectsBusiness, finance, marketing, and consulting firms analyzing data for insights
Employer & Industry UsageUsed in industries developing AI models, machine learning pipelines, and data infrastructureCommon across industries for reporting, trend analysis, and strategic decision-making

While both roles involve working with data, ML Data Associates focus on preparing and managing data specifically for machine learning models, whereas Data Analysts interpret data to generate business insights. The roles overlap in data handling skills but differ in their end goals and technical focus.

What are some common challenges faced by ML Data Associates when labeling complex datasets, and how can they be effectively addressed?

ML Data Associates often encounter challenges with ambiguous data, inconsistent labeling guidelines, or rapidly evolving project requirements. To address these, it's important to maintain open communication with data scientists and project leads, ask clarifying questions, and participate in regular calibration sessions to ensure consistency. Utilizing annotation tools efficiently and staying up-to-date with best practices can also help manage complexity and improve label quality. Collaboration and feedback within the team are key to overcoming these challenges and ensuring high-quality datasets.
What are popular job titles related to Ml Data Associate jobs in Bothell, WA? For Ml Data Associate jobs in Bothell, WA, the most frequently searched job titles are:
What job categories do people searching Ml Data Associate jobs in Bothell, WA look for? The top searched job categories for Ml Data Associate jobs in Bothell, WA are:
What cities near Bothell, WA are hiring for Ml Data Associate jobs? Cities near Bothell, WA with the most Ml Data Associate job openings:
Infographic showing various Ml Data Associate job openings in Bothell, WA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $77,343 per year, or $37.2 per hour.
Senior Associate, National Security-Cyber Security Governance

Senior Associate, National Security-Cyber Security Governance

Alvarez & Marsal

Seattle, WA • On-site

$113K - $146K/yr

Other

Medical, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Description
About Alvarez & Marsal
Alvarez & Marsal (A&M) is a global consulting firm with over 10,000 entrepreneurial, action and results-oriented professionals in over 40 countries. We take a hands-on approach to solving our clients' problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging work-guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity-are why our people love working at A&M.
The team
At A&M you will have the opportunity to work with a diverse team of supportive and motivated professionals that love to share their knowledge and depth of industry experience with others. A&M's Disputes and Investigations practice comprises professionals from a wide range of backgrounds, who bring and share their deep expertise in conducting investigations and delivering expert witness reports. We have an inclusive developmental environment where everyone has the opportunity to learn and grow. Our culture is characterized by openness and entrepreneurial thinking, with a foundation of mutual respect and high-quality standards for our work. We strive to remove bureaucracy in favor of recognizing effort and results through advancement opportunities and a motivating performance-based reward structure.
How you will contribute
With the rapid adoption of AI technologies and evolving regulatory landscape, demand for AI-focused security analysis and compliance expertise is growing exponentially. Our team supports organizations, investors and counsel in identifying, assessing, and mitigating risks associated with AI system deployment, algorithmic bias, data privacy, and model security. We focus on implementing secure AI/ML pipelines, establishing AI governance frameworks, conducting model risk assessments, and ensuring compliance with emerging AI regulations. Our approach integrates traditional cybersecurity with AI-specific security controls, leveraging automated testing, model monitoring, and adversarial robustness techniques. The team serves as trusted advisors to organizations navigating AI regulatory requirements, security certifications, and responsible AI implementation.
Responsibilities:
• Lead technical teams in executing AI security assessments, model audits, and compliance reviews related to AI Act (EU), NIST AI Risk Management Framework, ISO/IEC 23053/23894, and emerging AI governance standards. Develop AI risk assessment methodologies and implement continuous monitoring solutions for production ML systems.
• Design and implement secure AI/ML architectures incorporating MLOps security practices, including model versioning, data lineage tracking, feature store security, and secure model deployment pipelines. Integrate security controls for Large Language Models (LLMs), including prompt injection prevention, output filtering, and embedding security.
• Conduct technical assessments of AI/ML systems using tools such as:
• AI Security Tools: Adversarial Robustness Toolbox (ART), Foolbox, CleverHans for adversarial testing
• MLOps Platforms: MLflow, Kubeflow, Amazon SageMaker, Azure ML, Google Vertex AI
• Model Monitoring: Evidently AI, Fiddler AI, WhyLabs, Neptune.ai for drift detection and explainability
• LLM Security: Guardrails AI, NeMo Guardrails, LangChain security modules, OWASP LLM Top 10 tools
• Privacy-Preserving ML: PySyft, TensorFlow Privacy, Opacus for differential privacy implementation
• Implement AI compliance and governance solutions addressing:
• Regulatory Frameworks: EU AI Act, Canada's AIDA, US AI Executive Orders, Singapore's Model AI Governance Framework
• Industry Standards: ISO/IEC 23053, ISO/IEC 23894, IEEE 7000 series, NIST AI RMF
• Sector-Specific Requirements: FDA AI/ML medical device regulations, GDPR Article 22 (automated decision-making), SR 11-7 model risk management
• Develop and execute penetration testing specifically for AI systems, including:
• Model extraction attacks and defenses
• Data poisoning vulnerability assessments
• Membership inference and model inversion testing
• Prompt injection and jailbreaking assessments for LLMs
• Backdoor detection in neural networks
• Program and deploy custom security solutions using:
• Languages: Python (PyTorch, TensorFlow, scikit-learn), R, Julia
• AI Frameworks: Hugging Face Transformers, LangChain, LlamaIndex, AutoML tools
• Security Libraries: SHAP, LIME for explainability; Fairlearn, AIF360 for bias detection
• Infrastructure: Docker, Kubernetes, Terraform for secure AI deployment
• Integrate AI security with traditional security frameworks including Zero Trust architecture, IAM solutions, and SIEM platforms. Implement automated compliance monitoring using AI-powered security orchestration tools (SOAR platforms like Splunk Phantom, Palo Alto Cortex XSOAR).
• Assess and mitigate risks in:
• Foundation models and transfer learning implementations
• Federated learning systems
• Edge AI deployments
• Multi-modal AI systems
• Generative AI applications (GPT, DALL-E, Stable Diffusion implementations)
• Create technical documentation including AI system security architecture reviews, threat models specific to ML pipelines, compliance mappings, and remediation roadmaps aligned with both traditional security standards (NIST 800-53, ISO 27001) and AI-specific frameworks.
• Availability for up to 15% travel required to client sites and assessment locations.
Qualifications:
• 3+ years of experience in AI/ML development, deployment, or security assessment
• 2+ years of experience in information security, with focus on application security or cloud security
• Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face)
• Proficiency in Python programming with experience in AI/ML libraries and security testing tools
• Experience with cloud AI platforms (AWS SageMaker, Azure ML, Google Vertex AI, Databricks)
• Knowledge of AI compliance frameworks: NIST AI RMF, EU AI Act requirements, ISO/IEC 23053/23894
• Experience with MLOps tools and secure model deployment practices
• Understanding of adversarial machine learning and AI security threats (OWASP ML Top 10, ATLAS framework)
• Familiarity with privacy-preserving ML techniques (differential privacy, federated learning, homomorphic encryption basics)
• Experience with containerization (Docker, Kubernetes) and infrastructure as code
• Knowledge of traditional security frameworks (NIST CSF, NIST 800-53, ISO 27001)
• Ability to obtain a USG security clearance
Preferred Certifications:
• One or more AI/ML certifications: AWS Certified Machine Learning, Google Cloud Professional ML Engineer, Azure AI Engineer
• Security certifications: CISSP, CCSP, CompTIA Security+, CEH
• Specialized: GIAC AI Security Essentials (GAISE), Certified AI Auditor (when available)
Your journey at A&M
We recognize that our people are the driving force behind our success, which is why we prioritize an employee experience that fosters each person's unique professional and personal development. Our robust performance development process promotes continuous learning, rewards your contributions, and fosters a culture of meritocracy. With top-notch training and on-the-job learning opportunities, you can acquire new skills and advance your career.
We prioritize your well-being, providing benefits and resources to support you on your personal journey. Our people consistently highlight the growth opportunities, our unique, entrepreneurial culture, and the fun we have together as their favorite aspects of working at A&M. The possibilities are endless for high-performing and passionate professionals.
Regular employees working 30 or more hours per week are also entitled to participate in Alvarez & Marsal Holdings' fringe benefits consisting of healthcare plans, flexible spending and savings accounts, life, AD&D, and disability coverages at rates determined periodically as well as a 401(k) retirement savings plan. Provided the eligibility requirements are met, employees will also receive an annual discretionary contribution to their 401(k) retirement savings plan from Alvarez & Marsal. Additionally, employees are eligible for paid time off including vacation, personal days, seventy-two (72) hours of sick time (prorated for part time employees), ten federal holidays, one floating holiday, and parental leave. The amount of vacation and personal days available varies based on tenure and role type. Click here for more information regarding A&M's benefits programs
The salary range is $80,000 - $110,000 annually, dependent on several variables including but not limited to education, experience, skills, and geography. In addition, A&M offers a discretionary bonus program which is based on a number of factors, including individual and firm performance. Please ask your recruiter for details.
Alvarez & Marsal recruits on an ongoing basis. Candidates are considered as they apply, until the opportunity is filled. Candidates are encouraged to apply expeditiously to any role(s) that they are qualified for and that are of interest to them.
A&M does not require or administer lie detector tests as a condition of employment or continued employment. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
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