DeepRec.ai
Boston, Massachusetts
Machine Learning Engineer (LLM) Compensation: $170,000 - $200,000+ (DOE) Location: Boston or Berkeley, flexible 2-3 days per week in office 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 Essential Skills & Experience Strong proficiency in Python and ML frameworks (e.g., scikit learn, TensorFlow, PyTorch). Hands on experience fine tuning and training LLMs. Experience with PEFT, DPO, Prefence 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. Desirable Skills & Experience 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. For additional information or to apply, please get in touch or apply directly. Seniority level Not Applicable Employment type Full time Job function Information Technology
Machine Learning Engineer (LLM) Compensation: $170,000 - $200,000+ (DOE) Location: Boston or Berkeley, flexible 2-3 days per week in office 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 Essential Skills & Experience Strong proficiency in Python and ML frameworks (e.g., scikit learn, TensorFlow, PyTorch). Hands on experience fine tuning and training LLMs. Experience with PEFT, DPO, Prefence 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. Desirable Skills & Experience 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. For additional information or to apply, please get in touch or apply directly. Seniority level Not Applicable Employment type Full time Job function Information Technology