8 часов назад
Machine Learning Engineer (Ad Sciences)
172 500 - 210 000$
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Machine Learning Engineer (Ad Sciences) (AI/AdTech): Building and optimizing training pipelines, open-source LLM infrastructure, and inference systems for large-scale advertising models with an accent on distributed data systems, accelerator-based computing, and cost-efficient serving. Focus on adapting DeepSpeed and OpenRLHF, optimizing GPU/TPU inference, designing monitoring and evaluation solutions, and collaborating on reinforcement learning and ad science experiments.
Location: San Mateo, California, United States
Salary: $172,500–$210,000 USD annual base salary for California and New York offices; final compensation varies by location and region.
Company
is a global advertising technology company using AI, machine learning, and privacy-first data to connect brands, publishers, and consumers at large scale.
What you will do
- Build and support training pipelines and machine learning model implementations to accelerate experimentation.
- Adapt open-source LLM infrastructure, including DeepSpeed and OpenRLHF, for post-training requirements.
- Optimize online and batch inference for low latency and cost efficiency.
- Build monitoring and evaluation systems for reliable infrastructure and model quality.
- Improve data pipelines and training and inference features using data from across the product portfolio.
- Explore accelerator platforms such as JAX on TPUs and collaborate with Applied Scientists on experiment design and modeling.
Requirements
- Master’s degree in machine learning or a related field.
- At least 3 years of experience building large-scale machine learning or deep learning systems.
- Expertise in distributed data systems, relational and key-value stores, Airflow, and Spark.
- Expertise in Python and PyTorch or a similar ecosystem.
- Experience with Triton, ONNX, TensorRT, cloud platforms, and Kubernetes.
- Role location: San Mateo, California, United States.
Nice to have
- PhD in machine learning or a related field.
- Java experience, particularly with high-performance serving systems.
- Knowledge of deep recommender systems, reinforcement learning, and post-training feedback loops.
- Understanding of the advertising ecosystem, including OpenRTB, SSPs, DSPs, ad exchanges, and MMPs.
Culture & Benefits
- Entrepreneurial environment with autonomy, accountability, and a focus on high-impact problems.
- Continuous learning and career development through the Live Your Potential program.
- Medical, dental, and vision insurance with a company-matched HSA, plus a 401(k) company match.
- Vacation, sick days, special occasion time, company holidays, and parental leave.
- RSU grants where applicable, wellness support, employee assistance, and pet insurance.
- Flexible working hours, free office lunch, and pet-friendly offices.
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