Machine Learning Engineer Intern (Conversational AI) - 2027 Start (PhD)

TikTok; Seattle (WA); On-site; USD 42,000 - 54,000; Part time

Benefits offered by this job

Health insurance

Wellbeing benefits

Paid holidays

Job summary

TikTok is seeking a Machine Learning Engineer Intern (Conversational AI) for a 2027 start in Seattle. You will help build agent runtimes, memory, and context handling for multi-turn conversations, and contribute to production-safe prompts and guardrails.

Strong Python plus exposure to C++/Go/Rust/Java is expected. Responsibilities span post-training data flywheels, tool search governance, and evaluation pipelines using LLM-as-judge concepts.

Qualifications

• Pursuing a PhD in a technical field (CS/Engineering/OR).
• Strong Python with one of C++, Go, Rust or Java.
• Solid ML/DL/NLP fundamentals with hands-on LLM/agent experience.
• Ability to interpret research into production-ready code.
• Reading papers/blogs and turning insights into working implementations.

Responsibilities

• Architect agent runtime: manage skills, tools, context, and guardrails; implement safe fallbacks.
• Design memory and context strategies for long multi-turn agents.
• Lead post-training data workflows: SFT/DPO/RLHF/RLAIF through distillation.
• Develop tools, MCP, and tool search with governance for scalable context.
• Evaluate via LLM-as-judge with rigorous calibration and test splits.
• Build auditable loops: candidate registry, runtime traceability, and change lineage.
• Execute online experimentation: shadow/canary, A-B tests, and counterfactual eval.

Skills

Python

C++

Go

Rust

Java

Education

PhD candidate in Computer Science/Engineering/Operations Research

Job description

Machine Learning Engineer Intern (Conversational AI) - 2027 Start (PhD)

Location:

Seattle

Employment Type:

Intern

Job Code:

A218361A

Responsibilities

• Agent runtime (harness / agent loop). Orchestrate skills, tools, and context; implement loop control & intervention, progressive disclosure, and behavior-level guardrails. Build the production safety layer — pre-flight budgets and timeout truncation, serve-time gates, shadow / swap-in answer delivery, and safe fallback paths.
• Context & memory for long multi-turn agents. Agentic memory (structured note-taking), context compaction / summarization, context editing / observation masking, and just-in-time (retrieve-then-load) retrieval. Treat context as an evolving, itemized playbook — with structured diffs and a deterministic curator — rather than an ever-growing prompt.
• Post-training & the data flywheel. SFT / DPO / RL to internalize rules into weights (so the prompt gets shorter, not longer), plus distillation to smaller serving models. Turn served conversations into training / eval / retrieval signals.
• Tools, Skills, and MCP. Tools-as-APIs, connectors, skill / tool search for large inventories, and skill-library governance — description conflicts, trigger evals, cross-skill mis-fire matrices, and on-demand loading instead of dumping every definition into context.
• Evaluation you can bet a launch on. LLM-as-judge with human-agreement calibration; statistical rigor — paired comparison, confidence intervals, repeated sampling, pass^k; held-out and time-rolling eval splits with overfitting alarms; cascaded scoring and cross-family judge panels to make evaluation affordable at scale.
• The self-evolving loop. Case mining → automatic root-cause → constrained candidate generation → replay verification against frozen regression sets → canary → flywheel. Build the plumbing that makes it auditable: candidate registry with exact runtime read-back, change lineage, and an archive of rejected candidates you can sample from next round.
• Online experimentation & causal readout. Shadow / canary / A-B, non-inferiority gates, traffic-split health, metric definitions that survive scrutiny, and off-policy counterfactual evaluation where live A/B isn't possible.

Qualifications

• Currently pursuing a PhD in Computer Science, Engineering, Operations Research or a related technical discipline
• Strong Python plus one of C++ / Go / Rust / Java
• Solid ML / DL / NLP fundamentals, with genuine hands-on experience with LLMs or agents (coursework, research, internship, competition, open-source, or a serious side project)
• Basic statistical literacy — you can compute a confidence interval, explain what a p-value does and doesn't mean, and tell the difference between "the number went up" and "the system got better"
• Able to read a paper or an engineering blog and turn it into working code
• Preferred Qualifications- Hands-on experience in any one of the following — depth in one is enough, breadth welcome:
• Post-training: SFT / DPO / RLHF / RLAIF / RLVR, reward modeling, reward hacking and how to defend against it
• Agent systems: harness, context engineering, MCP / Skills, sub-agents, tool search
• Evaluation & experimentation: LLM-as-judge and judge calibration, pass^k, regression suites, A/B and non-inferiority testing, off-policy evaluation
• Self-improving / evolutionary systems: evolutionary program search, candidate archives and parent sampling, automatic prompt / context optimization, multi-objective (Pareto) selection and credit assignment
• Publications (for PhD), strong competition results (ACM-ICPC / Kaggle / ML competitions), or notable open-source contributions
• E-commerce or multilingual experience is a plus, not required

Job Information

The base salary range for this position in the selected city is $57 - $57annually.

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year).

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

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
• Exercising sound judgment.

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

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.

TikTok Accommodation

TikTok 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/RA-request