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Machine Learning Engineer (LLM)
Machine Learning Engineer (LLM)DeepRec.ai • Boston, MA, United States
Machine Learning Engineer (LLM)

Machine Learning Engineer (LLM)

DeepRec.ai • Boston, MA, United States
30+ days ago
Job type
  • Full-time
Job description

This range is provided by DeepRec.ai. 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 - $220,000.00 / yr

Direct message the job poster from DeepRec.ai

US Recruitment Consultant : Guiding GenAI professionals towards their dream careers

$200,000 - $220,000+ (DOE)

We’re working a fast-growing AI company on a mission to automate complex workflows in the financial services sector, starting with insurance. Their technology leverages cutting‑edge AI to simplify high‑value processes, from multi‑turn conversations to full workflow automation.

As an ML Engineer within LLMs, you’ll be building and scaling advanced AI systems that power intelligent, multi‑agent workflows. You’ll take ownership of designing, fine‑tuning, and productionizing large language models, integrating them with backend systems, and optimizing their performance. You’ll collaborate closely with data science, DevOps, and leadership to shape the AI infrastructure that drives the company’s automation solutions.

What You’ll Do :

  • Build, fine‑tune, and productionize large language model (LLM) pipelines, including PEFT, RLHF, and DPO workflows.
  • Develop APIs, data pipelines, and orchestration systems for multi‑agent, multi‑turn AI conversations.
  • Integrate models with backend services, including voice orchestration platforms and transcript generation.
  • Optimize model usage and efficiency, transitioning from external APIs to in‑house solutions.
  • Collaborate cross‑functionally with data scientists, DevOps, and leadership to deliver scalable machine learning solutions.

What We’re Looking For :

  • Strong proficiency in Python and ML frameworks (e.g., scikit‑learn, TensorFlow, PyTorch).
  • Hands‑on experience fine‑tuning and training LLMs.
  • PEFT, DPO, Preference Optimization, post‑training, supervised fine tuning, RLHF.
  • Familiarity with AWS suite and deploying ML models to production.
  • Ability to reason deeply about ML principles, architectures, and design choices.
  • Knowledge of multi‑agent orchestration and conversational AI systems.
  • Background in voice AI, speech‑to‑text, or text‑to‑speech systems.
  • Exposure to financial services or insurance applications.
  • Familiarity with optimizing models for long‑context scenarios.
  • If you’d like to hear more, please apply or get in touch!

    Seniority level

  • Not Applicable
  • Employment type

  • Full-time
  • Job function

  • Information Technology
  • #J-18808-Ljbffr

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    Machine Learning Engineer • Boston, MA, United States

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