Machine Learning Engineer for Cloud Native AI SAAS

Responsibilities

:

• Design, develop, and validate ML models for account scoring, lead scoring, and predictive analytics
• Experience with one or more deep learning libraries and platforms (e.g., TensorFlow, Jax, or PyTorch)

• Streamline model deployment and maintenance by implementing automated pipelines for training and deployment

• Integrate large language models (LLMs) into APIs and AI agents for data summarization and actionable insights.

• Analyze large datasets to inform model development and ensure data quality.

• Natural Language Processing, Vector Databases

• Monitor and optimize model performance in production through A/B testing and other evaluation techniques

• Align models with business objectives and provide data-driven recommendations to enhance product features

Education: Bachelors or Masters in Computer Science or Engineering is preferred

Why Join the Team?

You’ll work on impactful projects, pushing the boundaries of AI and machine learning.

Join a team that values innovation, collaboration, and the transformative power of technology.

Apply Now:
Bring your expertise in machine learning and LLM integration.

Let’s build the future together!

Some information about the company:

1. Proven Leadership and Track Record:
The leadership team brings a wealth of experience across various startups, demonstrating adaptability and success in creating high-growth companies. This track record of success, coupled with strong ties to venture capital, ensures a solid foundation for new ventures.

2. Backed by Major Venture Capitalists:
Having financial support from well-established venture capitalists positions the company to scale quickly while maintaining financial stability. This partnership provides both capital and strategic guidance for navigating the complexities of growth.

3. Customizing Existing Models:
Instead of starting from scratch, the company focuses on adapting and optimizing existing LLMs to maximize success in specific markets and industries.

4. Targeted Success:
Rather than taking a broad, one-size-fits-all approach, the company tailors its strategies to the unique demands of each market and target customer segment.

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