AI/ML Architect (Hybrid)

Redolent, Inc

Washington (District of Columbia)

On-site

USD 66,000 - 74,000

Part time

14 days+

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Job summary

Redolent, Inc is looking for a Senior ML Architect to lead the design of advanced machine learning algorithms and integrate cutting-edge generative AI technologies. This role involves mentoring teams and collaborating to deliver high-quality ML solutions focused on observability data and AIOps.

Qualifications

Strong experience in machine learning algorithms and deep learning applications.
Background in time series forecasting and anomaly detection.
Experience in integrating LLMs and generative AI.

Responsibilities

Architect advanced machine learning algorithms for various purposes.
Develop and implement deep learning systems for observability data.
Lead a team and collaborate across departments.

Skills

Python

TensorFlow

PyTorch

scikit-learn

generative AI

collaboration

agile development

Tools

Figma

Adobe XD

Microsoft Azure

Google Cloud

Job description

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This range is provided by Redolent, Inc. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$75.00/hr - $80.00/hr

Job Description:

We are seeking a highly skilled Senior ML Architect with extensive experience in designing and developing machine learning algorithms and deep learning applications, particularly for observability data (AIOps). The ideal candidate will have a strong background in time series forecasting, anomaly detection, event classification, and correlation ML algorithms. Additionally, experience in integrating with large language models (LLMs) and generative AI (GenAI) for effective summarization and other applications is essential.

Key Responsibilities:

Architect and design advanced machine learning algorithms for time series forecasting, anomaly detection, event classification, and correlation.
Develop and implement deep learning applications and systems for observability data (AIOps).
Integrate with large language models (LLMs) and generative AI (GenAI) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques.
Implement MCP client and server within the Grafana ecosystem or similar platforms.
Collaborate with cross-functional teams to ensure seamless integration and deployment of ML models.
Lead and mentor a team of engineers, both onshore and offshore.
Provide strategic guidance on AI/ML best practices and emerging technologies.

Required Skills and Experience:

Programming Languages: Proficiency in Python and R.
ML Frameworks: Extensive experience with TensorFlow, PyTorch, and scikit-learn.
Cloud Platforms: Working knowledge of Google Cloud and Azure.
Design Tools: Proficiency in Figma, Adobe XD, or Sketch.
Databases: Knowledge of MySQL, MongoDB, and PostgreSQL.
Server-Side Languages: Familiarity with Python, Node.js, and Java.
Version Control: Experience with Git and other version control systems.
Testing: Knowledge of testing frameworks and methodologies.
Agile Development: Experience with agile development methodologies.
Communication and Collaboration: Strong communication and collaboration skills.
GenAI Experience: Proven experience in integrating and leveraging generative AI models for various applications, including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).