Applied Machine Learning Engineer - USDS
Responsibilities
About the Team
You'll be an integral part of the USDS Cyber Defense & Engineering team, responsible for enhancing security tools and identifying vulnerabilities, with a specific focus on content assurance and the application of large language models (LLMs). You'll collaborate cross-functionally with partners inside and outside TikTok to fortify our products and users' security, helping to establish TikTok as the most trusted platform.
We are seeking a versatile, forward-thinking, and outcome-driven Content Assurance Specialist to propel our projects forward. In this capacity, you will engage with diverse technical and non-technical teams across various regions, contributing to the development of innovative, AI-driven solutions to complex content moderation challenges. If you thrive in a dynamic environment and relish the opportunity to shape the strategic trajectory of a large global organization, this role offers an exciting prospect.
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
About the Role
The ideal candidate will possess demonstrated problem-solving abilities, sound business acumen, and a track record of collaborating with multiple teams to successfully deliver projects. They should exhibit a genuine passion for safeguarding the security and privacy of our users, and a strong understanding of how to leverage cutting-edge technology, like LLMs, to achieve that goal.
Responsibilities
- Collaborate Across Teams: Work closely with data scientists, software engineers, machine learning engineers, and product managers to understand the recommendation engine.
- Deep Expertise in Recommender Systems: Leverage your expertise in machine learning and coding to gain an in-depth understanding of context-aware recommender systems.
- Understand Core System Components: Understanding of key modules in the recommender system, including recall, ranking, and reranking, ensuring high-quality, personalized recommendations at scale.
- End-to-End Ownership: In-depth understanding of the complete lifecycle of machine learning systems, from building and maintaining data pipelines and feature engineering, to training models and integrating them seamlessly into production environments.
- Ensure Security & Compliance: Work with cybersecurity teams to ensure that the recommender systems align with compliance standards and implement practices that enhance user trust and experience.
- Support Automation & Prototyping: Contribute to quick prototyping and proof-of-concept initiatives that automate rule reviews within the recommendation systems, ensuring both efficiency and compliance.
- Document & Ensure Accessibility: Build and maintain comprehensive documentation for data processes and machine learning models, ensuring transparency, accessibility, and consistency across teams.
Qualifications
Minimum Qualifications:
- Master's degree or PHD. in Computer Science, Engineering, Mathematics, or a related field along with Experience in Recommendation Systems: Proven track record of designing, developing, and optimizing recommendation systems, particularly at scale.
- Machine Learning Expertise: Experience working with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, MXNet, or similar tools to build and deploy models.
- Hands-on experience in one or more of the following areas: Large Language Models (LLM), Machine Learning, Deep Learning, Recommender Systems, Data Mining, or Natural Language Processing
- Strong Programming Skills: Excellent programming skills, data structure and algorithm skills, proficient in C/C++ or Python programming language, candidates with awards in ACM/ICPC, NOI/IOI, Top Coder, Kaggle and other competitions are preferred.
- Solid Understanding of Algorithms: Deep knowledge of data structures, algorithms, and optimization techniques to solve complex technical challenges along with Problem-Solving Mindset: Excellent troubleshooting and debugging skills, with an ability to quickly address issues that arise in live environments.
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- Collaboration & Communication: Strong teamwork and communication skills, with the ability to work effectively across interdisciplinary teams and clearly explain complex technical concepts.
Preferred Qualifications
- Advanced Techniques: Experience with advanced recommendation algorithms such as matrix factorization, collaborative filtering, or deep learning-based methods.
- Production-Ready Systems: Hands-on experience in deploying machine learning models in production environments, with an understanding of scaling and performance tuning.
- Model Evaluation: Familiarity with model evaluation metrics (e.g., precision, recall, NDCG) and A/B testing to assess and improve system performance.
- Cloud & Containerization Expertise: Knowledge of containerization tools (Docker, Kubernetes) and microservices architecture to support scalable, distributed systems.
- Security Awareness: Understanding of security and compliance best practices for handling user data in machine learning applications.
Job Information
[For Pay Transparency] Compensation Description (annually)
The base salary range for this position in the selected city is $136800 - $259200 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.
Perks and Benefits
Health and Wellness
- Health Insurance
- Dental Insurance
- Vision Insurance
- HSA
- Life Insurance
- Fitness Subsidies
- Short-Term Disability
- Long-Term Disability
- On-Site Gym
- Mental Health Benefits
- Virtual Fitness Classes
Parental Benefits
- Fertility Benefits
- Adoption Assistance Program
- Family Support Resources
Work Flexibility
- Flexible Work Hours
- Hybrid Work Opportunities
Office Life and Perks
- Casual Dress
- Snacks
- Pet-friendly Office
- Happy Hours
- Some Meals Provided
- Company Outings
- On-Site Cafeteria
- Holiday Events
Vacation and Time Off
- Paid Vacation
- Paid Holidays
- Personal/Sick Days
- Leave of Absence
Financial and Retirement
- 401(K) With Company Matching
- Performance Bonus
- Company Equity
Professional Development
- Promote From Within
- Access to Online Courses
- Leadership Training Program
- Associate or Rotational Training Program
- Mentor Program
Diversity and Inclusion
- Diversity, Equity, and Inclusion Program
- Employee Resource Groups (ERG)
Company Videos
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