machine learning engineer

2026 phd scientist intern (competitive intelligence) Jobs in Seattle

ai engineer (intern)

ai research scientist

artificial intelligence consultant Jobs in Seattle

artificial intelligence consultant

machine learning intern

Uber

<div>We're looking for PhD candidates to work with the Competitive Intelligence Team as a Scientist intern during summer 2026 (12 weeks). As an intern, you will be embedded in a product team working on solving real-world Uber problems under the supervision of an analyst on that team, and will have the opportunity to partner closely with Scientists, Software Engineers, Product Managers, and other cross-functional partners.
 
 
About the Role
 
 
The Competitive Intelligence team works to understand the strategy and performance of Uber and other companies with similar products through a combination of external and internal data. Uber operates in a diverse array of markets and product categories filled with rapidly evolving competing options; assessing the success or failure of a product or strategy depends on understanding this context. Doing this, and doing it well, is an interesting and challenging problem. The team uses its data analysis, statistical modeling, economics, and business expertise to build scalable data products and ship actionable insights.
 
 
We are looking for candidates passionate about solving new and difficult problems with data. You will build out and own competitive metrics/models, provide key insights, conduct deep dive analysis to understand new opportunities and empower teams to make more informed business and strategy decisions with competitive intelligence.
 
 
What You'll Do
<ul><li>Work with a mentor closely to define a business problem, scope a project, develop, and prototype the solution using data-driven approaches
</li><li>Work with engineers and product managers to turn prototypes into scalable solutions
</li><li>Present findings to leaders to inform decisions
</li><li>Establish standard methodologies for science such as modeling, coding, analytics, optimization, and experimentation
</li></ul>Basic Qualifications
<ul><li>Pursuing a Ph.D. majoring in Statistics, Machine Learning, Economics, or other related quantitative fields
</li><li>Candidates should have at least one semester/quarter left of their education after finishing the internship
</li><li>Strong problem-solving and analytical abilities
</li></ul>Preferred Qualifications
<ul><li>Coding proficiency in areas such as R, Spark, SQL, Python
</li><li>Background in data visualization via open-source libraries/packages or third-party tools (i.e. Tableau, Mixpanel, Looker, or similar)
</li><li>Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, stochastic processes, economics, and analytics
</li><li>Experience in the following areas: Exploratory Data Analysis, Statistical Analysis, ML Model Development, Competitive Intelligence, Causal Inference, Operations Management, Transportation
</li><li>0-2 years of prior work experience in an analytical setting
</li><li>Organized, detail-oriented and able to work independently on multiple projects at once
</li><li>Ability to communicate effectively with both technical and business partners
</li><li>Open to feedback, excellent at implementing newly learned ideas and concepts
</li><li>Research mentality with a bias towards action to structure a project from idea to prototype to implementation
</li>Independence, self-starter mindset, excellent communication, and outstanding follow-through - you energetically tackle your work and love the responsibility of being individually empowered 
<li>
</li></ul> 
 
For San Francisco, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Seattle, WA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For all US locations, you will also be eligible for various benefits.</div>

2026 PhD Scientist Intern (Competitive Intelligence)

Juniper Square

<div>
 
 About Juniper Square
 
 
 
 Our mission is to unlock the full potential of private markets. Privately owned assets like commercial real estate, private equity, and venture capital make up half of our financial ecosystem yet remain inaccessible to most people. We are digitizing these markets, and as a result, bringing efficiency, transparency, and access to one of the most productive corners of our financial ecosystem. If you care about making the world a better place by making markets work better through technology &ndash; all while contributing as a member of a values-driven organization &ndash; we want to hear from you.
 
 
 Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.
 
 
 
 About Your Role
 
 
 
 We're looking for an AI Engineer Intern to join our team who is excited to help transform the private markets. In this role, you&rsquo;ll work alongside a talented and collaborative team focused on one of our top strategic initiatives - bringing cutting-edge AI innovation to a key product feature that will drive real change in the industry.
 
 
 As an intern, you&rsquo;ll have a hands-on role in designing, building, and testing new AI-driven product features. This isn&rsquo;t a side project - it's a core company priority with executive visibility and high impact. You&rsquo;ll work in close partnership with engineers, product leaders, and mentors who are invested in your growth and success.
 
 
 You&rsquo;ll also gain valuable exposure to company leadership, access to world-class mentorship, and the opportunity to contribute meaningfully to a product that&rsquo;s reshaping how the private markets operate. For the right person, this internship can be a launchpad into a full-time role post-graduation.
 
 
 This opportunity is perfect for someone with a strong engineering foundation who is currently pursuing a master&rsquo;s degree in AI or a related field - and who&rsquo;s excited to innovate, learn fast, and make a real-world impact.
 
 
 
 This is a remote role based in the U.S. or Canada. The internship program runs for 11 weeks at 40 hours per week, with a scheduled start date of Monday, June 8th.
 
 
 
 
 There may be an opportunity to travel to our San Francisco office the final week to participate in the annual Hackathon.
 
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Collaborate with engineers and product managers to design and prototype AI-powered features that directly impact a key product area at the core of our business
 </li>
 <li>
 Contribute to the development, training, and evaluation of machine learning and natural language processing (NLP) models using industry-standard tools and frameworks
 </li>
 <li>
 Work with large and complex datasets - performing data preprocessing, feature engineering, and analysis to support model development
 </li>
 <li>
 Apply foundational machine learning and deep learning techniques to solve real-world problems in the private markets space
 </li>
 <li>
 Assist with integrating AI models into production systems, including testing, validation, and iteration in collaboration with the engineering team
 </li>
 <li>
 Support ongoing research and experimentation efforts, particularly around NLP and large language models (LLMs), to drive innovation in product development
 </li>
 <li>
 Partner closely with engineering, design, and product stakeholders to evaluate the technical feasibility and ensure alignment of proposed AI features with the overall product vision and strategy.
 </li>
 <li>
 Participate in regular team meetings, code reviews, and brainstorming sessions - bringing curiosity, ideas, and technical insight to the table
 </li>
 <li>
 Receive mentorship from experienced AI and engineering leaders, while gaining exposure to company leadership and strategic initiatives
 </li>
 <li>
 Contribute to documentation and knowledge sharing to help scale AI development efforts across the team
 </li>
 <li>
 Take ownership of meaningful projects with the potential to influence long-term company strategy and product direction
 </li>
 <li>
 Embrace a growth mindset - continuously learning new tools, methodologies, and concepts in the rapidly evolving field of AI
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Education &amp; Academic Background
 
 
 
 <ul>
 <li>
 Currently pursuing a Master&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related quantitative field (e.g., Mathematics, Statistics, Physics)
 </li>
 <li>
 Strong academic foundation with relevant coursework in algorithms, data structures, linear algebra, calculus, probability, and statistics
 </li>
 <li>
 Completed or currently enrolled in courses in machine learning, deep learning, NLP, or computer vision (highly desirable)
 
 
 </li>
 </ul>
 
 Technical Skills
 
 
 
 <ul>
 <li>
 Proficient in Python; experience with libraries such as TensorFlow, PyTorch, scikit-learn, NumPy, and Pandas is a plus
 </li>
 <li>
 Familiarity with data manipulation, preprocessing, and feature engineering techniques
 </li>
 <li>
 Exposure to databases (SQL/NoSQL) and data querying; experience with data visualization tools (e.g., Looker, Tableau, Power BI) is a bonus
 </li>
 <li>
 Understanding of foundational ML algorithms (e.g., regression, decision trees, clustering) and the underlying mathematical concepts
 </li>
 <li>
 A strong grasp of Large Language Model (LLM) mechanisms, including knowledge of sampling strategies, structured output generation, and function-calling capabilities. Hands-on experience with prompt engineering is a strong plus
 </li>
 <li>
 Exposure to cloud platforms (e.g., AWS, GCP) and cloud-based ML services (e.g., Amazon SageMaker, Google AI Platform) is beneficial
 </li>
 <li>
 Basic knowledge of software engineering practices, including version control (Git), Agile development, and API integration (REST, GraphQL)
 
 
 </li>
 </ul>
 
 Soft Skills &amp; Mindset
 
 
 
 <ul>
 <li>
 Strong analytical and problem-solving skills with a high attention to detail
 </li>
 <li>
 Eagerness to learn and apply new AI concepts in a fast-paced, evolving environment
 </li>
 <li>
 Clear and effective communication skills, both written and verbal
 </li>
 <li>
 Collaborative mindset with the ability to contribute meaningfully to team discussions and technical problem-solving
 </li>
 <li>
 Self-starter with curiosity, initiative, and a proactive approach to innovation
 
 
 </li>
 </ul>
 
 Bonus Points
 
 
 
 <ul>
 <li>
 Personal AI/ML projects (e.g., GitHub portfolio)
 </li>
 <li>
 Participation in AI/ML competitions or hackathons
 </li>
 <li>
 Research experience or academic publications in AI-related areas
 </li>
 <li>
 Contributions to open-source projects
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 Compensation for this position includes an hourly rate. The U.S. hourly rate is $50.00 USD and the Canadian hourly rate is $57.00 CAD.
 
 
 #Juniper-US
 
 
 #Juniper-Canada
 
 
 #emergingtalent
 
 
</div>

AI Engineer (Intern)

Call For Referral

<div>
 
 
 Machine Learning Engineer
 
 
 
 
 Work Mode:
 
 
 Remote
 
 
 
 
 Compensation:
 
 
 $100&ndash;$120 per hour
 
 
 
 
 Work Type:
 
 
 Hourly, Independent
 
 
 
 
 Role Overview
 
 
 
 This role supports the evaluation of
 
 advanced machine learning systems
 
 in collaboration with
 
 leading AI research initiatives
 
 . It is intended for
 
 experienced machine learning engineers and researchers
 
 who can contribute to the development of
 
 high-quality evaluation suites
 
 that measure AI performance on
 
 real-world machine learning engineering tasks
 
 .
 
 
 The work focuses on translating
 
 practical ML research and engineering workflows
 
 into
 
 structured benchmarks
 
 for
 
 frontier models
 
 . This is a
 
 project-based, fully remote
 
 opportunity for professionals with
 
 strong hands-on ML research and engineering experience
 
 .
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 
 Design and develop
 
 detailed evaluation suites for machine learning engineering tasks
 </li>
 <li>
 
 Evaluate AI-generated solutions
 
 across model training, debugging, optimization, and experimentation workflows
 </li>
 <li>
 
 Analyze and document
 
 system behavior, performance characteristics, and limitations
 </li>
 <li>
 
 Contribute to the creation of benchmarks
 
 that reflect real-world ML engineering practices
 </li>
 <li>
 
 Maintain high standards
 
 of technical accuracy, clarity, and consistency in all deliverables
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 
 3+ years
 
 of experience in machine learning engineering or applied ML research
 </li>
 <li>
 
 Hands-on experience
 
 with model development, experimentation, and evaluation
 </li>
 <li>
 
 Background in ML research
 
 in an industry or academic setting (strongly preferred)
 </li>
 <li>
 
 Strong ability
 
 to reason about ML system design choices and technical trade-offs
 </li>
 <li>
 
 Excellent written communication skills
 
 and
 
 high attention to technical detail
 
 </li>
 </ul>
 
 
 Work &amp; Payment Details
 
 
 <ul>
 <li>
 You will operate as an
 
 independent professional
 
 </li>
 <li>
 This is a
 
 fully remote
 
 role with a
 
 flexible schedule
 
 </li>
 <li>
 Projects may be
 
 extended, shortened, or concluded
 
 based on needs and performance
 </li>
 <li>
 The work does
 
 not involve access to confidential or proprietary information
 
 from any employer, client, or institution
 </li>
 <li>
 
 Payments are made weekly
 
 via
 
 Stripe or Wise
 
 , based on services delivered
 </li>
 <li>
 Candidates requiring
 
 H1-B or STEM OPT
 
 sponsorship are
 
 not supported
 
 at this time
 </li>
 </ul>
 
 
 Application &amp; Onboarding Process
 
 
 <ul>
 <li>
 
 Upload your resume
 
 </li>
 <li>
 
 AI interview:
 
 A short
 
 15-minute
 
 conversational session to understand your background, experience, and interest in the role
 </li>
 <li>
 
 Follow-up communication
 
 within a few days with next steps and onboarding details
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer (Remote)  $100 –$120/hr

Docusign

<div>
 
 Company Overview
 
 
 
 Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people&rsquo;s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign&rsquo;s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).
 
 
 What you'll do
 
 
 Docusign is looking for a passionate, talented, and collaborative Machine Learning Engineer to join our AI Infrastructure team. Our team is responsible for building Docusign&rsquo;s centralized platform to create, manage and deploy advanced AI/ML solutions to make customer journeys throughout the Docusign Agreement Cloud more efficient. As a Machine Learning engineer, you will help support all aspects of the machine learning lifecycle, including the research platform, training and deployment pipelines, labeling and serving infrastructure. You will partner with a team of expert applied researchers who specialize in various domains, including document understanding, natural language processing (NLP), computer vision, and more to prototype and productionize solutions for real business use-cases at scale.
 
 
 This position is an individual contributor role reporting to the Senior Manager, Machine Learning.
 
 
 
 Responsibility
 
 
 
 <ul>
 <li>
 Write clean, maintainable, and well-tested code for AI infrastructure services and data pipelines under the guidance of senior engineers
 </li>
 <li>
 Assist in building and maintaining CI/CD pipelines and workflows that automate model training and deployment
 </li>
 <li>
 Help monitor the performance of deployed AI services by implementing logging, metrics, and alerting (observability) to ensure system reliability
 </li>
 <li>
 Partner with Applied Scientists and Product Managers to understand requirements and help operationalize ML models for document understanding and NLP tasks
 </li>
 <li>
 Author unit and integration tests for your code components to ensure high quality and stability of the AI platform
 </li>
 <li>
 Develop scripts and small tools to support data labeling processes and ensure data governance standards are met
 </li>
 <li>
 Learn about new ML technologies (LLMs, Triton Inference Server, Kubernetes) and engineering best practices through code reviews and mentorship actively
 
 
 </li>
 </ul>
 Job Designation
 
 
 
 Hybrid:
 
 Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)
 
 
 Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law.
 
 
 What you bring
 
 
 
 Basic
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, or a related technical field (or equivalent experience)
 </li>
 <li>
 Experience with internships or applicable academic projects
 </li>
 <li>
 Experience with at least one major programming language, preferably Python or C#
 </li>
 <li>
 Experience with data structures, algorithms, and software engineering fundamentals
 </li>
 <li>
 Experience with version control systems (e.g., git) and writing unit tests
 </li>
 <li>
 Experience with RESTful APIs and how web services work
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Previous internship experience in software engineering, data engineering, or machine learning
 </li>
 <li>
 Coursework or academic projects related to Machine Learning, Natural Language Processing (NLP), or Computer Vision
 </li>
 <li>
 Familiarity with containerization technologies like Docker or Kubernetes
 </li>
 <li>
 Exposure to cloud platforms (AWS, Azure, or GCP)
 </li>
 <li>
 Interest in Large Language Models (LLMs) and Generative AI
 </li>
 <li>
 Experience with SQL or data processing libraries (e.g., Pandas, NumPy)
 
 
 </li>
 </ul>
 Wage Transparency
 
 
 Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.
 
 
 Based on applicable legislation, the below details pay ranges in the following locations:
 
 
 California: $100,300.00 - $154,900.00 base salary
 
 
 Washington, Maryland, New Jersey and New York (including NYC metro area): $94,600.00 - $137,875.00 base salary
 
 
 
 This Role Is Also Eligible For The Following
 
 
 
 <ul>
 <li>
 Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
 </li>
 <li>
 Stock: This role is eligible to receive Restricted Stock Units (RSUs).
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 Global benefits provide options for the following:
 
 
 <ul>
 <li>
 Paid Time Off: earned time off, as well as paid company holidays based on region
 </li>
 <li>
 Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
 </li>
 <li>
 Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
 </li>
 <li>
 Retirement Plans: select retirement and pension programs with potential for employer contributions
 </li>
 <li>
 Learning and Development: options for coaching, online courses and education reimbursements
 </li>
 <li>
 Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events
 
 
 </li>
 </ul>
 
 Work Authorization Notice:
 
 Please note that we do not provide visa sponsorship or immigration support for this position. Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship.
 
 
 Life at Docusign
 
 
 
 Working here
 
 
 
 Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what&rsquo;s right, every day. At Docusign, everything is equal.
 
 
 We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you&rsquo;ll be loved by us, our customers, and the world in which we live.
 
 
 
 Accommodation
 
 
 
 Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com.
 
 
 If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance.
 
 
 Applicant and Candidate Privacy Notice
 
 
 States Not Eligible for Employment
 
 
 This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.
 
 
 Equal Opportunity Employer
 
 
 It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category.
 
 
 EEO Know Your Rights poster
 
 
</div>

Machine Learning Engineer

TikTok

Technology
 
Machine Learning Engineer, E-Commerce Risk Control - USDS
 
Location
 :
 
Seattle
 
Employment Type
 :
 
Regular
 
Job Code
 :
 
A148522
 
Responsibilities
 
About the team
 The E-Commerce Risk Control team works to minimize the damage of inauthentic behaviors on Tiktok E-Commerce platforms, covering multiple classical and novel business risk areas such as account integrity, incentive abuse, malicious behaviors, brushing, click-farm, information leakage, etc.
 
In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles - You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolution of a phenomenal product eco-system. The work needs to be fast, transferable, while still down to the ground to make quick and solid differences.
 
Responsibilities: 
<ul>
<li>Invent, implement, and deploy state-of-the-art machine learning algorithms, build prototypes, and explore entirely new conceptual solutions to address and mitigate business risks in TikTok e-commerce/platforms, including but not limited to fraudulent merchants, cheating influencers, malicious users, information security issues, and cross-domain risk challenges.</li>
<li>Utilize techniques such as representation learning, graph models, deep learning, transfer learning, and multi-task learning to improve the efficiency of problem detection, enabling rapid risk mitigation and optimizing various metrics of the e-commerce community ecosystem.</li>
<li>Monitor and attribute key metrics to promptly perceive changes in risk and business, proactively identify potential attacks, continuously optimize and adjust risk control strategies, and drive the development of risk governance and business model adjustments.</li>
<li>Mine and analyze massive e-commerce content and user behavior data to build both short-term and long-term user profiles, improving model accuracy and recall, as well as enhancing robustness, automation, and generalization capabilities.</li>
<li>Advance risk machine learning capabilities in privacy/compliance, interpretability, risk perception, and analysis; innovate models and algorithms tailored to the characteristics of content e-commerce, building an industry-leading content e-commerce risk control algorithm system.</li>
</ul>
Qualifications
 
Minimum Qualifications
 <ul>
<li>Master’s degree in Computer Science, Mathematics, Machine Learning, or other relevant STEM fields.</li>
<li>1+ years of hands-on experience building and delivering machine learning models for large-scale projects in internet companies.</li>
<li>Proficient in C++/Java/Python with strong coding skills, and familiarity with at least one common machine learning/deep learning platform.</li>
<li>Experience in e-commerce/internet companies in fraud or risk control roles, with a track record of building fraud detection, anomaly detection, or other risk control models using relevant algorithms.</li>
<li>Strong critical, objective, and thinking skills; able to reason and communicate in a results-oriented, data-driven manner with high autonomy.</li>
</ul>
Preferred Qualifications: 
<ul>
<li>PhD in Computer Science, Machine Learning, Statistics, Operations Research, or related fields.</li>
<li>5+ years of hands-on experience in building and delivering large-scale risk control projects in internet/e-commerce companies, with proven success in large-scale anti-fraud data mining; strong coding (backend, infrastructure, algorithms) and system design skills.</li>
<li>Strong technical leadership combined with hands-on data mining and machine learning expertise; passionate about tackling TikTok’s data scale and business complexity; able to identify, plan, and lead both quick-win tactics and long-term strategies, guiding teams to counteract malicious actors on the platform.</li>
<li>High sense of ownership, excellent communication and collaboration skills; able to end-to-end manage one or more critical, highly adversarial, constantly expanding, and cross-functional platform/community security business areas.</li>
</ul>
Job Information
 
【For Pay Transparency】Compensation Description (Annually)
 
The base salary range for this position in the selected city is $129960 - $246240 annually.
 
​
 
Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
 
​
 
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
 
​
 
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 USDS
 
TikTok USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps we operate. The Joint Venture has been established in compliance with the Executive Order signed by President Trump on September 25, 2025. Our foundation is a comprehensive data privacy and cybersecurity program we operate under defined safeguards to protect national security and secure U.S. user data, apps and the algorithm. We safeguard the U.S. content ecosystem, holding decision-making authority for trust and safety policies and moderation. USDS Joint Venture helps ensure Americans can continue to express their creativity, discover new hobbies and interests, and build thriving communities and businesses on a global scale.
 
​
 
​
 
On-site presence across teams allows the company to operate with greater speed, alignment, and agility — especially in areas like real-time decision-making, team development, and integrated execution. As such, the company is shifting from a hybrid work model to a fully in-person schedule up to 5 days a week.
 
​
 
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.
 
​
 
USDS Reasonable Accommodation
 
USDS 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
 
https://tinyurl.com/USDS-RA

Machine Learning Engineer, E-Commerce Risk Control - USDS

Scowtt

<div>
 
 About Scowtt
 
 
 
 Scowtt is an early-stage startup transforming the way businesses convert leads into customers through AI/ML marketing optimization and fully autonomous sales experiences. By integrating CRM, web signals, and product interaction data into a real-time conversion model, we help businesses turn interest into action&mdash;immediately. We&rsquo;re growing fast, and onboarding new customers quickly and cleanly is core to our success.
 
 
 
 About The Role
 
 
 
 We are looking for a motivated, entry-level Machine Learning Engineer to help build, train, and deploy ML models that power our Marketing AI and AI Sales Agent products. This role is ideal for new graduates or early-career engineers who want hands-on experience working on real ML systems in a fast-paced, collaborative startup environment.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Assist in training, evaluating, and deploying ML models
 </li>
 <li>
 Work with structured and behavioral data used in marketing and sales systems
 </li>
 <li>
 Help automate and maintain data and ML pipelines
 </li>
 <li>
 Collaborate with engineers to integrate ML models into AI agents
 </li>
 <li>
 Debug, optimize, and improve model and pipeline performance
 </li>
 <li>
 Learn how ML systems operate in real production environments (cloud, monitoring, iteration)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Must Have
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, ML, Data Science, or equivalent
 </li>
 <li>
 1-3 years of experience in data structures, algorithms
 </li>
 <li>
 1-3 years of experience with machine learning concepts and workflows
 </li>
 <li>
 1-3 years of experience in coding using Python with demonstrated strong coding skills
 
 
 </li>
 </ul>
 
 Should Have
 
 
 
 <ul>
 <li>
 Exposure to ML frameworks through coursework, projects, or internships
 </li>
 <li>
 Curiosity, ownership mindset, and eagerness to learn
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Hands-on project or internship experience with real datasets
 </li>
 <li>
 Exposure to cloud platforms (GCP or AWS)
 </li>
 <li>
 Familiarity with tools like BigQuery, notebooks, or basic data pipelines
 
 
 </li>
 </ul>
 
 What Success Looks Like
 
 
 
 <ul>
 <li>
 You contribute to shipping ML models with guidance
 </li>
 <li>
 You learn to debug data and model issues
 </li>
 <li>
 You steadily increase independence and ownership
 </li>
 <li>
 You build strong foundations in applied ML engineering
 
 
 </li>
 </ul>
 
 Pay Range And Compensation Package
 
 
 
 Based on the level hired at, the cash compensation for this role ranges between $100,000 to $150,000. Selected candidate/s will be eligible for standard benefits and startup equity.
 
 
 
 Equal Opportunity &amp; E-Verify Employer
 
 
 
 Scowtt is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. We are committed to providing a workplace free of discrimination and harassment.
 
 
 This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. For more information, please visit www.e-verify.gov.
</div>

Machine Learning Engineer I

Wayfair

<div>Who We Are:

Wayfair is an online retail platform with the mission to enable everyone to live in a home they love. To do this Wayfair builds and leverages cutting edge Machine Learning and AI products and we are looking for talented individuals to join us. You will be part of a cross-functional, collaborative team driving development of world-class ML systems that drive real-world impact.

What You&rsquo;ll Do:
<ul>
<li>Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers</li>
<li><div>
Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions</div></li>
<li><div>
Collaborate closely with various engineering, infrastructure, and ML platform teams to ensure adoption of best-practices in how we build and deploy scalable ML services</div></li>
<li><div>
Build robust monitoring, alerting, edge-case handling mechanism</div></li>
<li><div>
Identify new opportunities and insights from the data (where can the models be improved? what is the projected ROI of a proposed modification?)</div></li>
<li>
Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on</li>
</ul>
We Are a Match Because You Have:
<ul>
<li>Minimum 0-1 years of experience with PhD, or 3+ years of industry experience with MSc/BaSc in STEM - engineering, computer science, economics, etc.</li>
<li><div>
Proficiency in Python or one other high-level programming language</div></li>
<li><div>
Must have a strong theoretical understanding and solid hands-on expertise deploying machine learning solutions into production.</div></li>
<li><div>
Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity</div></li>
<li>
Intellectual curiosity and enthusiastic about continuous learning</li>
</ul>
Nice to Have:
<ul>
<li>Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)</li>
<li>
Familiarity with GCP (or AWS, Azure), ML model development frameworks, ML orchestration tools (Airflow, Kubeflow or MLFlow)
</li><li>Experience with Spark, Kubernetes, Docker are nice to have</li></ul> 
<div></div>
<div> 
</div><div>Please note: this is a hybrid position based in Seattle, WA. Wayfair employee's are in-office Tuesday-Thursday with remote flexibility on Monday and Friday.</div><div>

Assistance for Individuals with Disabilities 
Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form. 
 
Need Technical Assistance? 
For more information about applying for a career at wayfair, visit our FAQ page here. 
 
About Wayfair Inc. 
Wayfair is one of the world&rsquo;s largest online destinations for the home. Whether you work in our global headquarters in Boston, or in our warehouses or offices throughout the world, we&rsquo;re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you&rsquo;re looking for rapid growth, constant learning, and dynamic challenges, then you&rsquo;ll find that amazing career opportunities are knocking.

No matter who you are, Wayfair is a place you can call home. We&rsquo;re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair &ndash; and world &ndash; for all. Every voice, every perspective matters. That&rsquo;s why we&rsquo;re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic.

Your personal data is processed in accordance with our Candidate Privacy Notice (https://www.wayfair.com/careers/privacy). If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at dataprotectionofficer@wayfair.com.</div></div>

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