Staff Machine Learning Engineer (LLM)

Alldus; United States; On-site; USD 200,000 - 230,000; Full time

Job summary

Alldus, a dynamic FinTech start-up, is seeking a Staff Machine Learning Engineer to develop cutting-edge conversational AI solutions. This role involves designing RAG models and collaborating with cross-functional teams to enhance customer experiences. Ideal candidates will have a strong background in machine learning, especially in NLP, NLU, and NLG techniques.

Benefits

Medical insurance

Vision insurance

401(k)

Qualifications

• 5+ years of experience in ML engineering focused on conversational AI.
• Proven expertise in developing RAG models and fine-tuning LLMs.
• Strong communication skills to collaborate with cross-functional teams.

Responsibilities

• Design, develop, and optimize RAG models for conversational AI.
• Collaborate with engineers to integrate ML models into production.
• Stay abreast of advancements in ML and conversational AI.

Skills

Machine Learning

NLP

NLU

NLG

Python

TensorFlow

PyTorch

Problem Solving

Education

Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field

Tools

AWS

Azure

GCP

Docker

Kubernetes

Job description

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

Base pay range

$200,000.00/yr - $230,000.00/yr

Direct message the job poster from Alldus

Machine Learning, Data Science & Engineering Recruiter | Organizer of the AI in Action Podcast

We are a dynamic FinTech start-up revolutionizing the way financial services are delivered through innovative conversational AI solutions. Our mission is to enhance customer experience, streamline operations, and drive growth for financial institutions worldwide. We're seeking a highly skilled Staff Machine Learning Engineer to join our passionate team and contribute to the development of cutting-edge RAG models and large language models, leveraging advanced techniques in Natural Language Processing (NLP), Natural Language Understanding (NLU), and Natural Language Generation (NLG).

As a Staff Machine Learning Engineer specializing LLM/RAG you will play a pivotal role in architecting, developing, and deploying state-of-the-art models to power our conversational AI product suite. You will collaborate closely with cross-functional teams including product managers, software engineers, and data scientists to ensure the seamless integration of machine learning capabilities into our solutions.

Key Responsibilities:

• Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation in conversational AI systems.
• Utilize vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts.
• Fine-tune and optimize large language models such as GPT (Generative Pre-trained Transformer) for specific use cases in the FinTech domain.
• Implement and experiment with cutting-edge NLP, NLU, and NLG techniques to enhance the capabilities and performance of our conversational AI products.
• Collaborate with software engineers to integrate machine learning models into production systems, ensuring scalability, reliability, and performance.
• Conduct research and stay abreast of the latest advancements in machine learning, NLP, and conversational AI to drive innovation and maintain competitive advantage.
• Provide technical leadership and mentorship to junior members of the machine learning team, fostering a culture of continuous learning and growth.

Qualifications:

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field. Advanced degree preferred.
• 5+ years of experience in machine learning engineering, with a focus on building and deploying conversational AI solutions.
• Proven expertise in developing RAG models, working with vector databases, and fine-tuning large language models.
• Strong programming skills in Python and proficiency with machine learning libraries such as TensorFlow, PyTorch, or JAX.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Solid understanding of NLP fundamentals and experience with NLU/NLG techniques such as sentiment analysis, entity recognition, and text generation.
• Excellent problem-solving abilities and a pragmatic approach to building scalable and robust machine learning systems.
• Strong communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to non-technical stakeholders.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research and Engineering

• Industries

  Financial Services and Software Development

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Inferred from the description for this job

Medical insurance

Vision insurance

401(k)

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