3 дня назад
Senior Staff ML Engineer (AI)
150 000 - 300 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Staff ML Engineer (AI): Architecting a centralized, real-time multimodal fraud defense ecosystem that unifies claims, payment, and identity risk assessment with an accent on scalable ML platforms, end-to-end AIML pipelines, and production model lifecycle management. Focus on designing distributed serving architectures, implementing monitoring and automated retraining, and solving complex cross-functional reliability, interpretability, fairness, and regulatory challenges.
Location: Palo Alto, California, United States
Annual salary: $150,000–$300,000
Company
is a large United States auto insurer and a member of the Berkshire Hathaway family, using artificial intelligence to transform insurance and protect customers from fraud.
What you will do
- Architect scalable, high-performance machine learning platforms and real-time decisioning systems for large data volumes.
- Design end-to-end AIML pipelines covering ingestion, feature engineering, training, deployment, monitoring, and retraining.
- Set technical direction across multiple ML feature teams and provide hands-on guidance through design reviews, code assessments, and performance tuning.
- Prototype advanced ML algorithms and integrate current AIML frameworks into production solutions.
- Partner with data scientists, software engineers, operations, and product teams to integrate ML systems into production.
- Ensure model reliability, security, interpretability, fairness, and regulatory compliance throughout the ML lifecycle.
Requirements
- 15+ years of relevant hands-on experience designing, implementing, and optimizing production AIML systems.
- Bachelor’s degree in machine learning, computer science, statistics, mathematics, or a related field.
- Expertise in large-scale data pipelines, real-time AIML serving architectures, and complete ML lifecycle management.
- Strong programming skills in Python, Java, or similar languages.
- Experience with distributed systems and tools including Airflow, DBT, Kubernetes, Spark, MongoDB, Snowflake, Neo4j, or Redis.
- Experience with cloud platforms and ML services such as AWS, Azure, SageMaker, or Azure ML, plus TensorFlow, PyTorch, or Scikit-learn.
Nice to have
- Experience in fraud detection, risk modeling, trust and safety, or digital identity.
- Production experience with LLMs, RAG, fine-tuning, or graph neural networks.
- Experience with model governance, explainability, and bias mitigation in regulated industries.
- Master’s degree or Ph.D.
Culture & Benefits
- Inclusive, collaborative culture focused on shared success.
- Personalized development programs, mentorship, and certification assistance.
- Competitive pay, benefits, and flexibility supporting employee well-being.
- will consider sponsoring a qualified new applicant for employment authorization.
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