- Страна
- США
- Зарплата
- 175 000 $ – 250 000 $
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Senior Software Engineer, Machine Learning
Исключительная вакансия в топовой инвестиционной компании с очень высокой зарплатой и полным пакетом льгот. Работа с передовым стеком технологий (LLM, GNN, Rust) делает позицию крайне привлекательной для профессионального роста.
Сложность вакансии
Высокая сложность обусловлена необходимостью глубоких знаний как в программной инженерии (gRPC, Rust/Axum), так и в специфических ML-технологиях (GNN, квантование LLM). Требуется опыт работы с высоконагруженными системами и сложной облачной инфраструктурой.
Анализ зарплаты
Предлагаемый диапазон $175k-$250k полностью соответствует и даже несколько превышает рыночные стандарты для Senior ML Engineer в Нью-Йорке. Верхняя граница в $250k является очень конкурентоспособной для финансового сектора, не считая бонусов.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Software Engineer, Machine Learning position at Point72. With over five years of experience in building robust MLOps frameworks and large-scale data pipelines, I am particularly drawn to your team's focus on Knowledge Graph Intelligence and event-driven architectures. My background in optimizing LLM inference and managing complex infrastructure with Terraform aligns perfectly with your mission-critical requirements.
In my previous roles, I have successfully implemented end-to-end ML lifecycles using Spark, Kubernetes, and MLflow, ensuring high-performance model deployment and monitoring. I am excited about the opportunity to leverage my expertise in GNNs and high-performance API frameworks like FastAPI and Axum to enhance Point72's surveillance capabilities. I am committed to the highest ethical standards and look forward to contributing to your investor-led culture.
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Откликнитесь в point72 уже сейчас
Присоединяйтесь к команде Point72 и создавайте будущее интеллектуальных систем на базе графовых технологий в ведущей инвестиционной фирме!
Описание вакансии
Software Engineer, Machine Learning (MLOps & Data)
A Career with Point72’s Surveillance Team
On the Knowledge Graph Intelligence team, you’ll work alongside product managers, engineers, and data scientists to build the next generation of intelligent systems through graph technology. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision-making and enhance how we build and operate our platforms and applications.
What you’ll do
In this data-heavy role, you will design and build mission-critical infrastructure that powers our machine learning lifecycle, from large-scale data processing and feature engineering to model training, real-time deployment, and monitoring. Specifically, you will:
- Architect and implement the full lifecycle of ML models, from data ingestion to production inference, contributing to the design of our next-generation, event-driven architecture, using technologies like gRPC, Kafka, and high-performance API frameworks, like FastAPI, Spring WebFlux, and Axum.
- Engineer and automate robust, large-scale data processing pipelines (ETL/ELT) using tools like Spark, dbt, and workflow orchestrators, and lead the design and implementation of our Feature Store strategy.
- Own the MLOps framework for model training, versioning, and deployment, including CI/CD pipelines, automated workflows, and experiment tracking and evaluation tooling.
- Implement sophisticated deployment strategies, including canary, blue-green, shadow, and A/B testing, to ensure safe, zero-downtime releases, and optimize inference performance for LLMs and other large models.
- Leverage cutting-edge tools and techniques like quantization and compilation to maximize throughput and minimize latency.
- Collaborate with data scientists to develop models and optimize model performance for low-latency serving using techniques like Python performance tuning.
- Define, provision, and manage our cloud infrastructure using Terraform, working hands-on with a wide array of cloud services across compute, storage, and machine learning platforms.
What’s REQUIRED
- 5+ years of experience in a software, data, or ML engineering role.
- Strong proficiency in SQL.
- Experience building and orchestrating data pipelines using tools such as Spark, dbt, and Dagster/Airflow, as well as data warehouses like Snowflake, Redshift, BigQuery.
- Understanding of infrastructure as code, including experience with Terraform.
- Proficiency with containerization and orchestration including Docker and Kubernetes.
- Hands-on experience with CI/CD tools and ML lifecycle tools, including Jenkins, MLflow, Kubeflow, and W&B.
- Experience with AWS and its core services including S3, EC2, Lambda, RDS, and EMR, and practical experience with Boto3 and AWS ML services SageMaker and Bedrock.
- Understanding of modern ML models and ability to discuss the performance characteristics and engineering trade-offs that influence deployment decisions.
- Experience with systems incorporating Graph Neural Networks (GNNs), recommendation systems, anomaly detection, and complex time-series models.
- Commitment to the highest ethical standards.
We take care of our people
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
- Fully-paid health care benefits
- Generous parental and family leave policies
- Volunteer opportunities
- Support for employee-led affinity groups representing women, people of color and the LGBT+ community
- Mental and physical wellness programs
- Tuition assistance
- A 401(k) savings program with an employer match and more
About point72
Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit https://point72.com/.
The annual base salary range for this role is $175,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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Навыки
- Python
- SQL
- Spark
- dbt
- Kafka
- gRPC
- FastAPI
- Terraform
- Docker
- Kubernetes
- AWS
- MLflow
- Snowflake
- PyTorch
- Rust
- SageMaker
Возможные вопросы на собеседовании
Проверка опыта работы с высоконагруженными системами и современными протоколами связи.
Расскажите о вашем опыте проектирования event-driven архитектур с использованием Kafka и gRPC для ML-сервисов.
Вакансия делает упор на графовые технологии. Важно понять практический опыт кандидата.
Какие основные сложности вы встречали при внедрении Graph Neural Networks (GNN) в продакшн?
Роль включает владение MLOps циклом.
Как вы организуете процесс CI/CD для моделей машинного обучения, чтобы обеспечить zero-downtime при использовании canary-деплоя?
Необходимо оценить навыки оптимизации производительности.
Какие методы оптимизации инференса LLM (например, квантование или компиляция) вы применяли на практике для снижения задержек?
Проверка навыков управления инфраструктурой.
Опишите ваш подход к структурированию Terraform модулей для управления сложной ML-инфраструктурой в AWS.
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- Страна
- США
- Зарплата
- 175 000 $ – 250 000 $