aiml - machine learning engineer, data and ml innovation

content creator, owned & social channels , operations internal communications

merchandising/sales representative, seattle

software development engineer Jobs in Seattle

software development engineer

adversarial machine learning engineer Jobs in Seattle

adversarial machine learning engineer

ai engineer (intern)

ai research scientist - mllm training Jobs in Seattle

ai research scientist - mllm training

aiml - machine learning engineer, data and ml innovation Jobs in Seattle

machine learning engineer

MORSE Corp

<div>
 
 MORSE Corp is an employee owned, small business based in Cambridge, MA, Arlington, VA, and Seattle, WA with a history of fielding
 
 cutting-edge
 
 
 technology. MORSE boasts a specially selected team of scientists, engineers, and software developers to deliver best-in-class technical solutions that solve difficult multidisciplinary problems faced by the US National Security Ecosystem.
 
 
 &nbsp;
 
 
 
 
 We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE&rsquo;s AI &amp; ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE&rsquo;s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments.
 
 
 &nbsp;
 
 
 
 Responsibilities:
 
 
 &nbsp;
 
 <ul>
 <li>
 
 Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.&nbsp;
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Use MLOps tools for efficient experiment tracking, data management, and reproducibility
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Write robust, efficient, and maintainable code
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models
 
 
 &nbsp;
 
 
 </li>
 </ul>
 
 Skills and Requirements:
 
 
 &nbsp;
 
 <ul>
 <li>
 
 US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proven experience testing and validating the performance of AI technologies in real-world applications
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proficiency in Python
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with cloud platforms (AWS and Azure)
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with Docker
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc.
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Exceptional communication skills and the ability to work well with customers
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Understanding of Department of Defense requirements and standards is a plus
 
 
 &nbsp;
 
 </li>
 </ul>
 
 
 &nbsp;
 
 
 
 
 
 
 &nbsp;
 
 
 
 
 &nbsp;
 
 
 
 MORSE Corp&rsquo;s salary range for this role carefully considers a wide range of compensation factors, including but not limited to, prior experience, education, skills and expertise, location, internal equity, and other factors that are job related and consistent with business need. Therefore, final offer amounts may vary from the amount stated. Depending on role eligibility, total compensation may also include bonus, stock, 401(k) match, paid time off, medical, dental, vision and life insurance.Employees also receive 10 paid holidays per year. MORSE maintains an &ldquo;open&rdquo; leave policy that does not restrict exempt, regular full-time employees to a specific&nbsp;number of paid sick or vacation days. However, this policy is not an &ldquo;unlimited&rdquo; paid leave policy.&nbsp;
 
 
 Compensation: $90,000 USD - $210,000 USD
 
 
 The team at MORSE takes pride in being the smart team that is easy to work with. We focus on steady, long-term success while maintaining a collaborative, enjoyable work experience for our employees. Our team values work-life balance through flexibility and other programs, along with a comprehensive benefits package for employees and families. For more information, please visit www.morsecorp.com.
 
 
 
 &nbsp;
 
 
</div>

Machine Learning Engineer

Apple

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn&rsquo;t have imagined, and now, can&rsquo;t imagine living without. It&rsquo;s the diversity of those people and their ideas that inspires the innovation that runs through everything we do. 
 
Description 
 
APPLE INC has the following available in Seattle, Washington. Develop software to run innovative machine learning systems in the cloud. Implement performant ML based algorithms in a distributed system and keep up to date with best practices and new technologies. Work closely with ML engineers to ensure their algorithms can be deployed efficiently in the cloud. Build software to support batch inferences for new large language models. Analyze and improve the job success rates for batch inference jobs. Optimize efficiency of the pipeline to improve throughput for large scale inference solutions. Build a scalable and efficient system to improve utilization of high-performance GPU fleet. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 - $210,100/yr and your base pay will depend on your skills, qualifications, experience, and location. 
 
PAY &amp; BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple&rsquo;s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple&rsquo;s Employee Stock Purchase Plan. You&rsquo;ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. 
 
Preferred Qualifications 
 
N/A 
 
Minimum Qualifications 
 
Bachelor&rsquo;s degree or foreign equivalent in Software Engineering, Computer Science, or related field and 2 years of experience in the job offered or related occupation. 
 
2 years of experience with each of the following skills is required: 
 
Applying Golang to design and develop large language model batch inference service codebase. 
 
Utilizing docker containerization and Kubernetes orchestration including AWS EKS or GCP to run batch inference service on the cloud infrastructure. 
 
Ensuring performance, scalability, security and maintainability when designing robust, large scale batch inference service. 
 
Utilizing ML Framework including PyTorch or TensorFlow to develop and optimize large language models. 
 
Applying foundation model architectures including Transformers, Encoder/Decoder to train, and fine-tune large language models. 
 
Utilizing MapReduce to develop efficient large scale data pipelines. 
 
Applying MLOps best practice to automate model deployment, monitoring, and continuous integration / continuous delivery. 
 
Utilizing hardware accelerators including GPUs or TPUs to maximize computational efficiency and reduce inference time. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

Join Apple&rsquo;s Information Security Machine Learning (ISML) team, where we are redefining cybersecurity through data-driven intelligence. Our mission is to transform traditional reactive security measures into autonomous systems that proactively detect and defend against threats. We achieve this through cutting-edge research, applied science, and robust infrastructure development. We are seeking a highly motivated and talented Machine Learning Engineer to join our dynamic and growing team. You will play a pivotal role in designing, developing, and deploying machine learning models that power our advanced security products and services. This is an incredible opportunity to make a real world impact by building intelligent systems that detect and prevent advanced threats, enhance critical security processes, and protect Apple and our customers. 
 
Description 
 
The Security ML Engineer will bring their expertise in machine learning to the problems and opportunities facing Information Security at Apple. You will contribute to the Autonomous Security program by developing production ready AI/ML systems using Apple&rsquo;s internal platforms, cloud services, and local compute environments. 
 
You will translate research to design, building and deploying machine learning models for security use cases, leveraging generative AI, statistical modeling, reinforcement learning, and data science to address complex security challenges. You will collaborate with cross-functional teams including security teams, software engineers, and researchers to prototype and scale AI/ML driven security solutions. You will own end-to-end ML workflows: data exploration, model development, evaluation metrics design, deployment, and monitoring. 
 
Preferred Qualifications 
 
Ph.D. in a technical field such as Computer Science, Engineering, Statistics, or related disciplines. 
 
In-depth knowledge of ML algorithms, including supervised/unsupervised learning, deep learning (CNNs, RNNs, LSTMs), and large language models. 
 
Industry experience in deploying ML and generative AI solutions in cybersecurity contexts. 
 
Familiarity with cloud platforms (e.g., AWS, GCP) and their security offerings is a plus. 
 
Experience with large scale data processing and analysis using tools such as Apache Spark. 
 
Experience working in a key security process, such as Incident Response, Threat Intelligence, or Vulnerability Management. 
 
Experience with specific security tools and technologies (e.g., SIEM, IDS/IPS, endpoint security solutions). 
 
Contributions to open-source security or machine learning projects. 
 
Publications or talks at top-tier ML or security conferences. 
 
Additional proficiency in C++ or Swift is a plus 
 
Minimum Qualifications 
 
BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field. 
 
Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn. 
 
Hands-on experience with full ML model lifecycle: from experimentation to deployment and monitoring. 
 
Solid grasp of security fundamentals including network security, incident response, threat modeling, and vulnerability management. 
 
Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences. 
 
Familiarity with CI/CD workflows and ML pipelines . 
 
Experience operating, and scaling production services in cloud native environments. 
 
Experience deploying models on CUDA devices using tools like TensorFlow or Torch. 
 
Proven experience building generative AI applications for real-world use cases. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer, Information Security

GEICO

<div>At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers&rsquo; expectations while making a real impact for our company through our shared purpose.
When you join our company, we want you to feel valued, supported and proud to work here. That&rsquo;s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.
At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers' expectations while making a real impact for our company through our shared purpose. When you join our company, we want you to feel valued, supported and proud to work here. That's why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers
GEICO is seeking a Senior Staff Machine Learning Engineer to help shape how Generative AI enhances customer and associate experiences across the enterprise. This is a hands-on technical role who will be leading the strategy, architecture, and delivery of ML systems for the Claims organization&mdash;designing predictive models, robust data/feature pipelines, and production-grade MLOps to drive measurable business outcomes. 
You will work alongside engineering teams, data scientists, and product leaders to design, build, and integrate AI-powered capabilities that automate workflows, improve decision-making, and elevate user experience. You will contribute to a culture of learning, curiosity, and innovation while growing your expertise in cutting-edge AI technologies
About the role<ul><li>
Staff+ individual contributor role focused on end-to-end ML: data and feature engineering, modeling, deployment, monitoring, and continuous improvement.</li><li>
Partner with Claims Operations, Product, and Engineering to deliver ML capabilities such as severity/triage predictions, claim outcome forecasting, and automation accelerators.</li><li>
GenAI (e.g., LLMs and agentic workflows) may be leveraged where it augments ML systems; strong ML depth is primary.</li></ul>
What you&rsquo;ll do<ul><li>
Own ML platform architecture: data/feature pipelines, experiment tracking, model registries, serving layers, offline/online evaluation, and observability.</li><li>
Define standards for reliability, performance, cost efficiency, security, governance, and model risk management across ML services.</li><li>
Lead design and implementation of models across classical ML and deep learning (e.g., gradient boosted trees, sequence models, Transformers for tabular/time-series/NLP where relevant).</li><li>
Translate business goals into measurable ML objectives and experiment plans; ensure robust offline metrics and real-world impact.</li><li>
Build scalable training and inference pipelines; establish CI/CD for ML, automated evaluations, canary releases, and rollback strategies.</li><li>
Implement monitoring for data quality, drift, fairness, latency, reliability, and cost; lead incident response and postmortems.</li><li>
Partner with Claims, Product, Data Science, Platform/SRE, Security, and Legal/Compliance to gather requirements, define scope, and prioritize backlogs.</li><li>
Maintain pragmatic technical roadmaps balancing business outcomes, release timelines, and engineering excellence.</li><li>
Own build-vs-buy decisions and tooling/service selection (speed to market, extensibility, TCO); guide platform evolution with clear architectural principles.</li><li>
Lead experienced engineers through complex platform implementations; drive system-wide architectural improvements and reliability practices.</li><li>
Mentor engineers and junior tech leads; codify best practices; contribute to internal documentation and promote enterprise-wide ML standards.</li><li>
Where appropriate, collaborate on retrieval-augmented workflows, prompt/context management, and LLM evaluation and safety guardrails to complement ML systems.</li></ul>
Minimum qualifications<ul><li>
Bachelor&rsquo;s degree or above in Computer Science, Engineering, Statistics, or related field.</li><li>
10+ years of professional software development experience using at least two general-purpose languages (e.g., Java, C++, Python, C#).</li><li>
10+ years architecting, designing, and building multi-component ML platforms leveraging open-source/cloud-agnostic components:<ul><li>
Search/vector: ElasticSearch, Qdrant (as applicable to ML features and retrieval)</li><li>
Data warehouse/lakehouse: Snowflake; familiarity with Parquet/Delta/Iceberg</li><li>
Streaming: Kafka; plus Flink/Spark Streaming experience</li><li>
Datastores: PostgreSQL; NoSQL (MongoDB, Cassandra)</li><li>
Distributed compute: Spark, Ray</li><li>
Workflow orchestration: Airflow, Temporal</li></ul></li><li>
6+ years managing end-to-end SDLC for ML systems: version control, CI/CD, Kubernetes, testing (unit/integration/data/ML eval), monitoring/alerting, production support.</li><li>
6+ years working with cloud providers (Azure and/or AWS) in production ML contexts.</li></ul>
Preferred qualifications (GenAI as a plus)<ul><li>
Experience leveraging or fine-tuning LLMs (e.g., GPT, Llama, Mistral, Claude) to augment ML workflows, retrieval, or claims-facing tooling.</li><li>
Hands-on with MLOps tooling: MLflow/Kubeflow, model registries, feature stores (e.g., Feast), experiment tracking, A/B testing and online evaluation frameworks.</li><li>
Observability: Prometheus/Grafana, OpenTelemetry; SLO-driven operations and incident management.</li><li>
Model safety, fairness, explainability (e.g., SHAP/LIME), and regulatory compliance; familiarity with model risk management practices.</li><li>
Insurance/financial services domain experience: claims automation, fraud detection, risk modeling, subrogation, severity/triage, and regulatory stewardship.</li><li>
Experience with high-throughput, low-latency inference and real-time feature pipelines.</li></ul>
#LI-JK1 
Annual Salary
$150,000.00 - $300,000.00
The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate&rsquo;s work experience, education and training, the work location as well as market and business considerations. 

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position. 
The GEICO Pledge:
Great Company: At GEICO, we help our customers through life&rsquo;s twists and turns. Our mission is to protect people when they need it most and we&rsquo;re constantly evolving to stay ahead of their needs.
We&rsquo;re an iconic brand that thrives on innovation, exceeding our customers&rsquo; expectations and enabling our collective success. From day one, you&rsquo;ll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people&rsquo;s lives.
Great Careers: We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career &ndash; and your potential &ndash; in mind. You&rsquo;ll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.
Great Culture: We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives. Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.
As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.
Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.<ul><li>
Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family&rsquo;s overall well-being.</li><li>
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.</li><li>
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.</li><li>
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.</li></ul>
The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.
GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.</div>

Senior Staff Machine Learning Engineer

The Applied Machine Learning team builds production multimodal systems that understand and transform large-scale image, audio, and video content. Our work spans diffusion-based image generation, transcription and diarization, face and object detection, OCR and image description for search, and automated quality control of media pipelines. 
 
We are looking for a Staff Machine Learning Engineer to strengthen our diffusion and video models, adapt small and mid-sized LLMs, and turn our uniquely large corpus of weakly labeled media into a durable product advantage. This is an opportunity to shape the next generation of multimodal experiences end-to-end, from data and models to evaluation and user impact. 
 
Description 
 
The Staff Machine Learning Engineer - Multimodal Generation &amp; Post-Training will be a senior individual contributor on a small, applied ML team focused on production multimodal systems. The role will lead fine-tuning and adaptation of diffusion and emerging video models, as well as post-training of small and medium LLMs for captioning, moderation, and retrieval-friendly descriptions. 
 
The engineer will design data and evaluation workflows that use our large archive of weakly labeled music, podcast, film, TV, and short-form content to drive measurable quality and efficiency improvements. The role includes close collaboration with partner infra teams for model serving and with adjacent product and research groups to bring new capabilities into production. 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, or a related technical field. 
 
8+ years of industry experience with production multimodal systems spanning image, audio, and/or video. 
 
Deep expertise with diffusion and video generation techniques (e.g., ControlNet/IP-Adapter, temporal consistency methods, sampling and latency optimization). 
 
Experience with PEFT/QLoRA and post-training approaches such as DPO or related preference-based methods for small and mid-sized LLMs. 
 
Background in ASR/VAD/diarization, OCR, multimodal retrieval, or face recognition with fine-grained temporal alignment. 
 
Familiarity collaborating with infra/platform teams on model serving (e.g., batching strategies, quantization, observability) and translating requirements into reliable production deployments. 
 
Demonstrated ability to define metrics, build evaluation harnesses, and communicate results clearly to cross-functional partners. 
 
Track record of publications, patents, or open-source contributions in relevant areas of machine learning or multimodal modeling. 
 
Minimum Qualifications 
 
Master&rsquo;s degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience. 
 
5+ years of hands-on industry experience building and shipping machine learning systems to production. 
 
Proven experience training and fine-tuning diffusion or other image/video generative models, including adapter-based methods such as LoRA. 
 
Proficiency in Python and at least one major deep learning framework such as PyTorch. 
 
Experience designing and operating ML pipelines for noisy or weakly labeled data, including offline evaluation and monitoring in production. 
 
Strong software engineering skills, including code quality, experimentation discipline, and debugging/profiling of model performance. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $201,300 and $302,200, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Staff Machine Learning Engineer, Apple Services Engineering

From our origins in iPhone keyboard input, the Input Experience NLP team has expanded to a broad charter: improve the user experience with robust language understanding and personalized text composition, across languages and Apple platforms. We build the ML models that underlie Summarization, Smart Reply, Writing Tools, and other features deeply integrated into Apple products. Generative AI is a transformative technology that we have only just begun to incorporate into our digital lives, to help everyday people digest the deluge of information they receive and express themselves more clearly. On our team, you will help build the future and have a voice in the shape it takes. 
 
We are looking for a Machine Learning Engineer to develop the next generation of our ML models, so that they better serve the full range of our customers, across languages, writing styles, and other personal context, in a privacy-preserving way. You will build, run, and refine the training and evaluation pipelines that define our slice of Apple Intelligence, driving the focused experimentation and iteration that makes the user experience magical. You will join an ambitious, organized, and collaborative team. We&rsquo;re in a unique position to integrate the latest innovations from the ML community and work on features that reach everyday users, including your family and friends. You&rsquo;ll work closely with teams across Apple, collaborating on human interfaces, user studies, internationalization, ML technologies, system integration, and more. 
 
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other&rsquo;s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It&rsquo;s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you&rsquo;ll do more than join something-you&rsquo;ll add something. 
 
Description 
 
As a Machine Learning Engineer on our team, you will enable next-generation AI applications by building toolkits and workflows that scale to increasingly sophisticated modeling tasks. You will design the abstractions and implement the algorithms that facilitate efficient data synthesis, data curation, prompt engineering, and model evaluation. You will contribute to a company-wide effort to build robust modeling pipelines that optimize our ability to iterate rapidly and continuously deliver improvements to our customers. Finally, you will help define and refine new features that expand both the depth of Apple Intelligence&rsquo;s capabilities and the breadth of its support for the full spectrum of Apple customers&quot;,&quot;responsibilities&quot;:&quot;Development and maintenance of data and model pipelines that scale to deployment in production 
 
Building toolkits for iterating on model quality via data synthesis and prompt engineering 
 
Definition of robust automated evaluation mechanisms to facilitate hillclimbing on model quality 
 
Failure analysis from user feedback to understand shortcomings of our models and evaluation data 
 
Research into state-of-the-art techniques for improving model quality and robustness 
 
Implementation of experiments and simulations to assess the value of model changes 
 
Preferred Qualifications 
 
Familiarity with LLMs, such as SFT, RHLF, prompt engineering, data synthesis, automatic evaluation, and RAG 
 
Expertise in MLOps and a passion for software quality, based on CI/CD principles 
 
Excellent written and verbal communication skills 
 
Background in linguistics, fluency in multiple languages, or a passion for scaling NLP features for global audiences 
 
History of developing Python packages and supporting users and other teams 
 
Minimum Qualifications 
 
MS or PhD in Computer Science or related field with at least 2 years of industry experience 
 
Strong Python programming skills, with experience developing production-quality Python modules 
 
Experience building and maintaining model pipelines end-to-end, from data curation to evaluation 
 
Solid background in machine learning, data science, natural language processing, or statistics 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer, Natural Language Generation

C-Serv

<div>The Opportunity 
We are building a dedicated AI Red Team to rigorously test and harden enterprise-scale AI products.
We are looking for an adversarial machine learning specialist who thinks like an attacker.
This role focuses on identifying vulnerabilities in LLM-driven systems, breaking model guardrails, exploiting data pathways, and stress-testing AI deployments before they reach enterprise customers.
This is a hands-on technical role at the core of AI security. 

What You&rsquo;ll Do<ul><li>
Conduct adversarial testing across LLM and AI-based systems</li><li>
Execute real-world attack simulations, including:</li><li>
Prompt injection</li><li>
Jailbreaking and guardrail bypass</li><li>
Data exfiltration attempts</li><li>
Model inversion and evasion techniques</li><li>
RAG manipulation</li><li>
Develop scripts and tooling to automate attack scenarios</li><li>
Analyse model behaviour under adversarial pressure</li><li>
Identify systemic vulnerabilities in:</li><li>
APIs</li><li>
Embedding pipelines</li><li>
Vector databases</li><li>
Fine-tuned model implementations</li><li>
Collaborate with engineering teams to validate remediation</li><li>
Document findings clearly and concisely</li></ul> 
You will help ensure AI systems are resilient before they are deployed at scale. 
Requirements 
 
What We&rsquo;re Looking For 

Core Technical Skills<ul><li>
Strong experience in adversarial ML or AI security research</li><li>
Experience working with LLM-based systems (OpenAI, Anthropic, open-source models, etc.)</li><li>
Deep understanding of:</li><li>
Prompt injection techniques</li><li>
Model jailbreak methodologies</li><li>
AI system exploitation vectors</li><li>
Strong Python skills</li><li>
Experience building custom attack tooling or experimentation frameworks</li></ul> 

AI Systems Knowledge<ul><li>
Familiarity with:</li><li><ul><li>
RAG architectures</li><li>
Vector databases</li><li>
Model fine-tuning workflows</li><li>
API-based model deployments</li><li>
Understanding of model safety mechanisms and guardrails</li></ul></li></ul> 

Nice to Have<ul><li>
Background in cybersecurity or penetration testing</li><li>
Familiarity with OWASP LLM Top 10</li><li>
Experience working in enterprise environments</li></ul> 

Who You Are<ul><li>
Curious and relentless</li><li>
Comfortable thinking like an attacker</li><li>
Creative in finding non-obvious vulnerabilities</li><li>
Detail-oriented but fast-moving</li><li>
Comfortable operating in ambiguity</li><li>
Independent but collaborative</li></ul> 
You don&rsquo;t just run test cases &mdash; you design new ones. 
Benefits 
<ul><li>
Comprehensive Private Medical Coverage</li><li>
Support for Mental Health Expenses</li><li>
Life Insurance Options</li><li>
Attractive Compensation Package</li></ul></div>

Adversarial Machine Learning Engineer

Explore 169+ Machine learning engineer in Seattle this March. Find roles across top companies and apply now to boost your career.

169 machine learning engineer jobs In Seattle

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer, Information Security

Senior Staff Machine Learning Engineer

Staff Machine Learning Engineer, Apple Services Engineering

Machine Learning Engineer, Natural Language Generation

Adversarial Machine Learning Engineer