Machine Learning Engineer (LLM)
Compensation: $170,000 - $200,000+ (DOE)
Location: Boston or Berkeley, flexible 2-3 days per week in office
Weโre working a fastโgrowing AI company on a mission to automate complex workflows in the financial services sector, starting with insurance. Their technology leverages cuttingโedge AI to simplify highโvalue processes, from multiโturn conversations to full workflow automation.
As an ML Engineer within LLMs, youโll be building and scaling advanced AI systems that power intelligent, multiโagent workflows. Youโll take ownership of designing, fineโtuning, and productionizing large language models, integrating them with backend systems, and optimizing their performance. Youโll collaborate closely with data science, DevOps, and leadership to shape the AI infrastructure that drives the companyโs automation solutions.
What Youโll Do
- Build, fineโtune, and productionize large language model (LLM) pipelines, including PEFT, RLHF, and DPO workflows.
- Develop APIs, data pipelines, and orchestration systems for multiโagent, multiโturn AI conversations.
- Integrate models with backend services, including voice orchestration platforms and transcript generation.
- Optimize model usage and efficiency, transitioning from external APIs to inโhouse solutions.
- Collaborate crossโfunctionally with data scientists, DevOps, and leadership to deliver scalable machine learning solutions.
What Weโre Looking For
Essential Skills & Experience
- Strong proficiency in Python and ML frameworks (e.g., scikitโlearn, TensorFlow, PyTorch).
- Handsโon experience fineโtuning and training LLMs.
- Experience with PEFT, DPO, Prefence Optimization, postโtraining, 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 multiโagent orchestration and conversational AI systems.
Desirable Skills & Experience
- Background in voice AI, speechโtoโtext, or textโtoโspeech systems.
- Exposure to financial services or insurance applications.
- Familiarity with optimizing models for longโcontext scenarios.
For additional information or to apply, please get in touch or apply directly.
Seniority level
Not Applicable
Employment type
Fullโtime
Job function
Information Technology