Machine Learning Engineer, Integrity
Deploys state-of-the-art ML models and fine-tunes LLMs in production to enhance platform integrity and safety against adversarial threats. Requires Master's/PhD, deep learning expertise, PyTorch/TensorFlow proficiency.
About the job
Responsibilities
- Design and deploy advanced machine learning models to solve real-world problems.
- Collaborate with researchers, software engineers, and product managers on AI-powered solutions.
- Implement scalable data pipelines and optimize models for production.
- Engage with latest ML/AI developments, participate in code reviews, and maintain engineering practices.
- Monitor and maintain deployed models.
Requirements
- Master's/PhD in Computer Science, Machine Learning, Data Science, or related field.
- Experience in deep learning and transformers models.
- Proficiency in PyTorch or TensorFlow.
- Strong foundation in data structures, algorithms, and software engineering.
- Familiarity with training/fine-tuning LLMs (distillation, supervised fine-tuning, policy optimization).
- Excellent problem-solving, analytical skills, and ability to work cross-functionally in fast-paced environment.
Nice-to-Haves
- Experience with search relevance, ads ranking, or LLMs.
Skills
PyTorch, TensorFlow, Deep Learning, Transformers, LLMs, Llm Fine-Tuning, Data Pipelines, Data Structures, Algorithms, Supervised Fine-Tuning
Similar jobs
ML Engineering jobs
OpenAI
San Francisco, CA
Build research infrastructure and tooling that enables AI models to design silicon, including reinforcement learning environments, EDA integrations, evaluations, and experiment workflows. The role requires strong software engineering fundamentals and comfort working across research, tooling, and chip-design systems.
OpenAI
San Francisco, CA
Build and optimize the production LLM inference runtime for frontier models on OpenAI’s custom silicon. The role spans scheduling, distributed execution, memory and KV-cache management, performance tooling, and hardware-software co-design.
Hyperbound
San Francisco, CA
Build and operate machine learning models for sales roleplay, scoring, and coaching products, owning the lifecycle from fine-tuning and evaluation through production and on-device deployment. The role emphasizes open-source models, latency and privacy optimization, and rigorous model testing.
Anthropic
San Francisco, CABuild and deploy LLM-powered tools, agents, and ecosystem infrastructure with life sciences research institutions. The role requires deep scientific or biomedical research experience, production software development expertise, and the ability to translate partner workflows into scalable AI systems.
OpenAI
San Francisco, CA
Build and optimize OpenAI’s inference stack for AWS Trainium across high-performance kernels, compilers, runtimes, and model execution. The role requires systems programming and accelerator experience, with opportunities to solve end-to-end performance problems for frontier-scale AI models.