Internship

Machine Learning Ops Intern

Posted on 9/27/2024

Blockhouse

Blockhouse

11-50 employees

Develops decentralized security and privacy technologies

Fintech
Cybersecurity
Crypto & Web3

New York, NY, USA

Candidates must attend standup meetings at 10am EST.

Category
Applied Machine Learning
AI & Machine Learning
Operations & Logistics
Required Skills
Python
Tensorflow
Git
Pytorch
AWS
Data Analysis
Google Cloud Platform
Requirements
  • 1+ Years of MLOps Experience: Demonstrable experience in building and scaling machine learning pipelines with a focus on high-frequency data and real-time model performance.
  • Mastery of Real-Time Systems: Expertise in building and optimizing real-time dashboards, streaming data pipelines, and infrastructure for high-throughput, low-latency environments. Hands-on experience with ClickHouse and Redpanda (or similar technologies) is critical to succeed in this role.
  • Proficiency in Python & ML Frameworks: Deep expertise in Python and machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn. Ability to deploy these models in real-time production environments.
  • Infrastructure & Cloud Expertise: Mastery of cloud platforms like AWS or GCP, with experience deploying and managing machine learning models using tools like SageMaker, Lambda, EKS, or similar.
  • CI/CD & Automation: Extensive experience building automated CI/CD pipelines for model deployment, using tools such as Jenkins, GitLab CI, or equivalent.
  • Monitoring at Scale: Experience with monitoring and alerting tools like Prometheus, Grafana, CloudWatch, or similar, and the ability to implement real-time monitoring for machine learning systems.
  • World-Class Collaboration: A collaborative mindset with the ability to work across teams and drive results in a fast-paced, high-performance environment.
Responsibilities
  • Build Real-Time Dashboards: Develop, design, and optimize real-time dashboards to visualize the performance of high-frequency machine learning models, providing instant insights and decision-making capabilities.
  • High-Frequency Model Pipelines: Build and maintain machine learning pipelines that enable continuous, low-latency model training, serving, and monitoring at scale.
  • Advanced Data Integration: Design and implement seamless data integration between high-frequency models and real-time streaming architectures using Redpanda (or similar technologies) for event-driven processing and ClickHouse (or similar technologies) for OLAP analytics.
  • Real-Time Monitoring & Optimization: Create highly resilient monitoring systems with real-time feedback loops to ensure that machine learning models perform at optimal levels. Automate retraining and performance alerts using state-of-the-art monitoring tools.
  • Cloud Infrastructure & CI/CD Automation: Develop automated CI/CD pipelines for the deployment and lifecycle management of machine learning models on cloud-native infrastructure (AWS, GCP). Focus on creating scalable, robust systems that can handle real-time loads.
  • Collaborate with Elite Teams: Work closely with a team of world-class engineers and data scientists to ensure seamless collaboration between data pipelines, machine learning model development, and production deployments.

Blockhouse develops decentralized technologies that prioritize security and privacy in digital systems. The company focuses on the blockchain and trusted execution environments (TEEs) markets, catering to a diverse clientele that includes academic institutions and tech enterprises. Blockhouse's main product is a distributed platform made up of hardened microservices that operate within TEEs, providing high-level security while maintaining performance. Unlike many competitors, Blockhouse emphasizes the combination of trusted and trustless computing, allowing users to have personal control over their data. The company's goal is to create a secure digital society by enabling individuals to manage their data in a decentralized environment.

Company Stage

N/A

Total Funding

N/A

Headquarters

Oxford, United Kingdom

Founded

2018

Growth & Insights
Headcount

6 month growth

36%

1 year growth

36%

2 year growth

36%
Simplify Jobs

Simplify's Take

What believers are saying

  • Confidential computing is gaining traction among enterprises for enhanced data security.
  • Zero-trust architecture adoption is increasing demand for robust security measures like TEEs.
  • EU's Digital Services Act drives demand for technologies enhancing user data control.

What critics are saying

  • Emerging blockchain startups could dilute TBTL's market share.
  • Vulnerabilities in TEEs may undermine client trust in TBTL's offerings.
  • Quantum computing evolution poses a threat to blockchain security.

What makes Blockhouse unique

  • TBTL specializes in decentralized technologies ensuring security and privacy in digital systems.
  • The company offers a distributed platform with hardened microservices in TEEs.
  • TBTL's business model includes partnerships, licensing, and key management services.

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