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Senior Machine Learning Engineer

Little Ferry, NJ, United States

Role Details:

Senior MLOps Engineer - Python

Intellectual Point is currently seeking a qualified MLOps Engineer to join our dynamic team. This role focuses on enhancing and maintaining state-of-the-art machine learning operations that support large language models (LLMs) across various platforms.

$100K-180K + Quarterly Bonuses (Performance Based)

️ Flexible PTO & 50% Coverage: Health, Vision, and Dental

Remote Only OR Hybrid OR Sterling, VA OR Reston, VA

Fully Funded IT Certifications & Internal Education

Accelerated Career Growth w/ Smaller Engineering Team

Work Issued - Latest M1 Macbook Pro

You will report to our SVP, Software Engineering.

Key Responsibilities:

On-Premise Architecture Development: Design and implement robust architecture using Nvidia GPUs for self-hosted LLMs, ensuring system resilience and efficiency.

Pipeline Optimization: Enhance ML pipelines with a focus on reducing latency and increasing concurrency, especially for Retrieval-Augmented Generation (RAG) systems.

Private Cloud Deployment: Execute deployments of LLMs on-premise on home-owned hardware DGX/HGX/XE9840, with an emphasis on scalability and hardware-efficiency.

MLOps Orchestration: Merge MLOps and DevOps principles to refine workflows, enhance monitoring, and improve system visibility.

Operational Efficiency: Apply MLOps and DevOps strategies to boost team productivity and streamline operations.

Deployment Automation: Seamlessly transition research models into deployment pipelines, ensuring smooth integrations.

Scalable Development: Work collaboratively to scale research code from the training phase to inference, optimizing performance.

Monitoring, Logging, and Governance: Maintain rigorous monitoring and logging practices to track system performance and adhere to strict governance standards.

️ Qualifications:

Programming Experience: At least 2 to 3 years of proficiency in Python and NodeJs.

Educational Background: Bachelor’s degree in Computer Science or a related field, or an equivalent professional experience.

MLOps/DevOps Experience: 3-5 years of experience in MLOps or DevOps roles, preferably within a production environment.

Infrastructure: Strong skills in IaaC, Docker, Kubernetes, and continuous integration/continuous deployment (CI/CD) pipelines.

Security and Compliance: Comprehensive understanding of security practices related to MLOps, including proactive data protection measures.

️ Preferred Skills:

Framework Proficiency: Familiarity with TensorFlow, PyTorch, and RAG systems.

Monitoring Tools: Experience with Prometheus, Grafana, or ELK Stack.

Agile Methodologies: Proficiency in Agile development practices.

Database Knowledge: Experience with various databases, including SQL, NoSQL, or data lakes.

Who you are:

You enjoy learning new things.

You love to ship code fast.

You strive to make things simple.

You have an eye for modern full-stack design.

You have incredibly high urgency & attention to detail.

You are clear communicator and can describe bottlenecks clearly.

You can comfortable in dealing with ambiguity and can make sure everyone is on the same page.

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