software engineer

software development engineer Jobs in Seattle

software development engineer

ai engineer (intern)

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

artificial intelligence researcher Jobs in Seattle

artificial intelligence researcher

adversarial machine learning engineer

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

Security Engineer - Investigator (High Severity Scams)

Apple

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

<div>
 
 Summary
 
 
 
 Are you excited to tackle some of the most ambitious technical challenges in Apple Intelligence? Be involved in collaborating closely with our machine learning researchers, engineers, and data scientists? Together, you will orchestrate groundbreaking research initiatives and develop transformative products designed to build a significant impact for billions of users worldwide!
 
 
 As part of Apple's AI and Machine Learning org, we encourage and create groundbreaking technology for large-scale ML systems, computer vision, natural language processing, and multi-modal understanding and generation. The Data and Machine Learning Innovation (DMLI) team is looking for Machine Learning Engineer to explore new methods, challenge existing metrics or protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges.
 
 
 
 Description
 
 
 
 As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state of the art research in ML to tackle complex data problems. The solutions you develop will significantly impact Apple Intelligence, future Apple products and the broader ML development ecosystem.
 
 
 You will work with a multidisciplinary team to actively participate in Apple Intelligence&rsquo;s data-model co-design and co-develop practice. Your responsibilities will extend to the design and development of a comprehensive data generation and curation framework for Apple Intelligence foundation models at Apple. You will also be responsible to build robust model evaluation pipelines, integral to the continuous improvement and assessment of Apple Intelligence foundation models.
 
 
 Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.
 
 
 Your work may span a variety of directions, including but not limited to:
 
 
 Develop and implement techniques for creating high-quality synthetic datasets across a variety of domains, including vision, text, and audio data.
 
 
 Innovate and experiment with new approaches for synthetic data generation to improve the diversity, realism, and representativeness of datasets.
 
 
 Collaborate with multi-functional teams to understand data requirements and ensure that synthetic datasets are optimized for training foundation models.
 
 
 Crafting and implementing semi-supervised, self-supervised representation learning techniques for growing the power of both limited labeled data and large-scale unlabeled data.
 
 
 Develop pipelines and tools to automate synthetic data generation for large-scale AI experiments.
 
 
 Stay updated with the latest research and industry trends in synthetic data generation, foundational model training, and large-scale data engineering.
 
 
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning.
 </li>
 <li>
 Deep understanding in multi-modal foundation models.
 </li>
 <li>
 Staying on top of emerging trends in generative AI and multi-modal LLM.
 </li>
 <li>
 Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality.
 </li>
 <li>
 Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, , etc)
 </li>
 <li>
 Strong problem-solving and communication skills.
 </li>
 <li>
 Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas
 
 
 </li>
 </ul>
 
 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 $147,400 and $272,100, 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&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 &mdash; 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.
 
 
 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.
 
 
 Apple accepts applications to this posting on an ongoing basis.
 
 
</div>

AIML - Machine Learning Engineer, Data and ML Innovation

Are you passionate about Generative AI and excited to work on groundbreaking modeling technologies that will enrich the lives of billions? The Intelligence System Experience (ISE) team within Apple&rsquo;s software organization is a multidisciplinary group operating at the intersection of Multimodal Foundation Models, Efficient and Scalable ML Infrastructure, and Personalized Intelligent Experiences. As a senior machine learning engineer on our team, you will design software systems and algorithms that enable performant, scalable training and inference for Apple&rsquo;s AI-driven experiences across both on-device and server environments. This role also includes opportunities to open source your work. Join our team of highly skilled, impact-focused engineers! 
 
Description 
 
We&rsquo;re seeking strong senior machine learning engineers to help build next-generation tools for large-scale deep learning. You&rsquo;ll join a team focused on accelerating training and inference speed, improving scalability, and advancing Apple&rsquo;s centralized ML platform. Candidates should bring polished coding skills and a passion for machine learning and computational science. We offer a respectful work environment, flexible responsibilities, and access to world-class experts and growth opportunities. 
 
In this role, you will develop core components for our scalable ML platform, push the limits of existing training technologies, and create new techniques to overcome system constraints. Your work will be deployed on high-impact tasks across teams building Apple Intelligence products, with opportunities to open-source your contributions. We are especially looking for a PyTorch-focused ML efficiency expert to optimize training and inference performance, improve distributed training throughput, and drive system-level efficiency for large-scale models. If you have deep experience with PyTorch internals and high-performance ML infrastructure, we&rsquo;d love to hear from you. 
 
Preferred Qualifications 
 
Experience developing model parallel and data parallel training solutions and other training optimizations 
 
Experience with parallel training libraries such as torch.distributed, DeepSpeed, or FairScale 
 
Experience with CUDA-level optimization 
 
Experience building ML models targeting Apple Silicon 
 
Experience building large-scale deep learning infrastructure or platforms for distributed model training 
 
Publication record at Machine Learning conferences such as MLSys, NeurIPS, etc. 
 
Minimum Qualifications 
 
PhD or Master's degree in the area of Computer Science, or equivalent years of industry experience 
 
3+ years working with AI/ML technologies in production or research settings 
 
Strong Python programming skills 
 
Understanding software design principles, and algorithms 
 
Experience with deep learning frameworks, such as PyTorch 
 
Experience building large-scale distributed systems 
 
Familiarity with parallelization algorithms for large model training 
 
Familiarity with recent developments in foundation model architectures 
 
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 $171,600 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.

Senior Machine Learning Efficiency Engineer - SIML, ISE

University of Washington

<div>
 
 Job Description
 
 
 
 
 Columbia Basin Research has an outstanding opportunity for a Software Engineer to join their team
 
 .
 
 
 The Software Engineer will work with a small team of statisticians at Columbia Basin Research (CBR; www.cbr.washington.edu). CBR is a research center within the School of Aquatic and Fishery Sciences, College of the Environment, University of Washington. CBR conducts basic and applied research on the impacts of regulated river operations on the freshwater and marine survival of salmon in a changing environment. As part of its mission, CBR develops desktop and web-based applications (https://www.cbr.washington.edu/analysis) to perform statistical analyses relevant to fish, dam, water, and natural resource management.
 
 
 The Software Engineer will play a lead role in the development and maintenance of desktop applications to implement statistical analysis for effective monitoring and research related to salmon survival and migration in tributaries, past dams, and in the marine environment. These analysis tools are used by researchers and managers throughout the Columbia River Basin and California&rsquo;s Central Delta to design field studies of salmon and steelhead migration and analyze the resulting tagging data.
 
 
 The Software Engineer will also be instrumental in redeveloping, implementing, and maintaining a web-based application to forecast salmon run-timing from a long time series of past migration data combined with data from the current migration season (&ldquo;in-season forecasts&rdquo;). These forecasts are used by managers of hydroelectric projects to schedule their dam operations throughout the year to protect endangered salmon and steelhead, while also providing visualizations of salmon populations&rsquo; response to hatchery practices and climate change.
 
 
 This position offers great opportunities for professional and personal growth in a stimulating research environment on applied ecology and endangered salmon and steelhead.
 
 
 
 Responsibilities
 
 
 
 The position&rsquo;s major duties and responsibilities include: (1) developing and maintaining desktop applications to implement statistical analyses, including back-end, user interface, and data storage; (2) redeveloping, implementing, and maintaining a web-based application of in-season forecasts of salmon runs; (3) working with internal databases; and (4) interfacing with statisticians to develop software to analyze complex environmental data in a user-friendly computing environment.
 
 
 
 Develop and Maintain Statistical Tools and Programs: 50%
 
 
 
 <ul>
 <li>
 Collaborate with statisticians in the design, development, debugging, documentation, and maintenance of a suite of statistical applications for design and analysis of salmonid survival studies, including the Parameter Estimation programs on the Tools webpage.
 </li>
 <li>
 Design, develop, implement, and document user-friendly interfaces for the statistical applications, programs, and tools. Primary programming languages: C#, C/C++, and Python. Primary UI frameworks: XAML, Qt.
 </li>
 <li>
 Maintain best practices programming with source control (Git), issues tracking (Git), unit testing, test plans, quality assurance applications (C#, R statistical package), and release testing.
 </li>
 <li>
 Backup all statistical tools and programs.
 
 
 </li>
 </ul>
 
 Redevelop, Implement, and Maintain Web-based Application for In-season Forecasts: 20%
 
 
 
 <ul>
 <li>
 Implement and maintain web-based application of in-season forecasts of salmon runs on the CBR Predictions webpage.
 </li>
 <li>
 Collaborate with statisticians to redevelop in-season forecasts to use AI approaches such as machine learning or neural networks; implement and test online against existing forecasts.
 </li>
 <li>
 Work with internal relational databases using SQL.
 
 
 </li>
 </ul>
 
 Data Processing and Analysis: 10%
 
 
 
 <ul>
 <li>
 Analyze tagging data using a combination of Python, SQL, and R.
 
 
 </li>
 </ul>
 
 Customer Service: 10%
 
 
 
 <ul>
 <li>
 Provide support to the public and to the fisheries community in the Pacific Northwest, which includes members of local, state, and federal government agencies, First Nations and Tribes, environmental organizations, and consulting organizations. Provide instruction on the use of our programs in training sessions to fisheries community.
 
 
 </li>
 </ul>
 Learning New Technologies: 10%
 
 
 <ul>
 <li>
 Keep up to date on advancements in scientific computing.
 </li>
 <li>
 Learn to implement new programming approaches and software to ensure continued maintenance and improvement of existing analytical tools and development of new tools.
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 Bachelor&rsquo;s degree in Computer Science, Mathematics, Statistics, Data Science, or related field and three years of relevant experience in software development.
 
 
 Equivalent education and/or experience may substitute for minimum qualifications except when there are legal requirements.
 
 
 
 Additional Qualifications
 
 
 
 <ul>
 <li>
 Programming experience in C# or C/C++
 </li>
 <li>
 Working knowledge of relational databases using SQL
 </li>
 <li>
 Working knowledge of numerical optimization
 </li>
 <li>
 Working familiarity with version control using Git
 </li>
 <li>
 Working familiarity with Python and R
 </li>
 <li>
 Experience with web design and Linux
 </li>
 <li>
 Demonstrated ability to work in a collaborative setting with an interdisciplinary research team
 </li>
 <li>
 Strong written and oral communication skills
 </li>
 <li>
 Demonstrated problem-solving skills
 </li>
 <li>
 Demonstrated ability to exercise logical judgment and work independently
 </li>
 <li>
 Demonstrated ability to prioritize work to complete deliverables in a timely manner
 </li>
 <li>
 Demonstrated ability to learn new software frameworks, understand complex quantitative methods quickly, and innovate independently and collaboratively
 </li>
 <li>
 Demonstrated ability to establish and maintain positive, ethical, and professional interpersonal relationships
 
 
 </li>
 </ul>
 
 Desired Qualifications
 
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Computer Science, Mathematics, Statistics, Data Science, or related field and at least three years&rsquo; experience in software development or equivalent combination of education/experience
 </li>
 <li>
 Academic training in Mathematical Statistics or Data Analysis
 </li>
 <li>
 Two years&rsquo; experience in Qt, XAML, Java, and Perl
 </li>
 <li>
 Two years&rsquo; experience programming machine learning, neural networks, or other AI for time series forecasting
 </li>
 <li>
 At least three years of experience programming with a collaborative team
 </li>
 <li>
 Outstanding interpersonal skills, including team ethics and relationship-building, and critical thinking skills
 </li>
 <li>
 Interest in biological/ecological subjects and the desire to develop user-friendly software to investigate environmental issues
 </li>
 <li>
 Knowledge of Pacific Salmon and Steelhead ecology
 
 
 </li>
 </ul>
 
 WORKING ENVIRONMENTAL CONDITIONS
 
 
 
 The majority of the work will be conducted within an office setting. Occasional business trips to train users in software or attend conferences may be required (approximately 1 trip per year).
 
 
 
 Compensation, Benefits And Position Details
 
 
 
 
 Pay Range Minimum:
 
 
 
 $87,624.00 annual
 
 
 
 Pay Range Maximum
 
 
 
 $98,400.00 annual
 
 
 
 Benefits
 
 
 
 
 Other Compensation:
 
 
 
 For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-uw-staff/
 
 
 
 Shift
 
 
 
 First Shift (United States of America)
 
 
 
 Temporary or Regular?
 
 
 
 This is a regular position
 
 
 
 FTE (Full-Time Equivalent)
 
 
 
 100.00%
 
 
 
 Union/Bargaining Unit
 
 
 
 Not Applicable
 
 
 
 About The UW
 
 
 
 Working at the University of Washington provides a unique opportunity to change lives &ndash; on our campuses, in our state and around the world.
 
 
 UW employees bring their boundless energy, creative problem-solving skills and dedication to building stronger minds and a healthier world. In return, they enjoy outstanding benefits, opportunities for professional growth and the chance to work in an environment known for its diversity, intellectual excitement, artistic pursuits and natural beauty.
 
 
 
 Our Commitment
 
 
 
 The University of Washington is committed to fostering an inclusive, respectful and welcoming community for all. As an equal opportunity employer, the University considers applicants for employment without regard to race, color, creed, religion, national origin, citizenship, sex, pregnancy, age, marital status, sexual orientation, gender identity or expression, genetic information, disability, or veteran status consistent with UW Executive Order No. 81.
 
 
 To request disability accommodation in the application process, contact the Disability Services Office at 206-543-6450 or dso@uw.edu.
 
 
 Applicants considered for this position will be required to disclose if they are the subject of any substantiated findings or current investigations related to sexual misconduct at their current employment and past employment. Disclosure is required under Washington state law.
</div>

Software Engineer

Uber

<div>About the Role
 
 
Earner Incentives is one of the fastest-growing products at Uber. As an Engineer on the Earner Incentives team you will work on the latest backend technologies developing highly scalable, Customer facing services and features, platforms and control panel tooling used by our operations on a daily basis.
 
 
Incentives Platform is used for generating efficient incentives for drivers, measuring progress of drivers towards achieving those incentives and then paying once incentive goals are achieved. It plays a critical role in ensuring adequate supply to meet the market demands across time and space. The combination of technical challenges and cross functional work will allow you to grow as a software engineer in any dimension.
 
 
Join us to work on some of the most exciting challenges on this journey.
 
 
What the Candidate Will Need / Bonus Points
- What the Candidate Will Do - 
 
 
<ul><li>As a backend engineer, you will architect, design and build software solutions to help with all aspects of capacity planning/management/engineering to scale Uber's infrastructure across a variety of sophisticated workflows and business processes.
</li><li>Design end-to-end features and systems to build high quality consumer-facing products.
</li><li>Write code, test, and maintain production services for high availability, reliability, and performance.
</li><li>Work with ML engineers and scientists to develop ML models to improve product performance.
</li><li>Work with Product Managers to understand product requirements and lead product rollout plans.
</li><li>Mentor junior team members.
</li><li>You will collaborate with other teammates to maintain the health of our systems and codebase, refactor and make improvements, and keep our systems robust and resilient.
</li></ul>- Basic Qualifications - 
 
 
<ul><li>2+ years experience working on the full software life cycle including gathering requirements, project planning, solution design, coding/implementation, testing, rollout/deployment and best practices as an individual contributor.
</li><li>Experience coding using general purpose programming language (eg. C/C++, Java, Python, Go, C#)
</li><li>Fast and passionate learner. Strong collaboration, documentation and communication skills.
</li></ul>- Preferred Qualifications - 
 
 
<ul><li>Experience building consumer-facing products.
</li><li>Experience designing and implementing large-scale service with excellent quality.
</li><li>Experience working with Machine Learning engineers and scientists on ML model productionization.
</li>Experience collaborating with other engineers and non-tech stakeholders, both to meet short-term goals and to create long-term partnerships. 
<li>
</li></ul> 
 
For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Software Engineer II - Earner Incentive

Explore 123+ Adversarial machine learning engineer in Seattle this March. Find roles across top companies and apply now to boost your career.