Liberate Inc.
Machine Learning Engineer – LLM Engineering New Toronto, ON
Liberate Inc., Boston, Massachusetts, United States, 02298
Toronto, ON
About Us Liberate is reimagining how the $2.7T insurance industry works. By starting with voice, the most valuable and complex channel in insurance, the company proved that even the hardest problems can be automated. Now expanding into full workflow automation across sales, servicing, and claims, Liberate is building toward a bold vision: reasoning agents capable of managing the entire spectrum of carrier and broker operations. Trusted by leading brokers and carriers and powered by a team with experience at Metromile, Google, Stripe, and other category-defining companies, Liberate is shaping the future of insurance.
About the role We’re looking for a
Machine Learning Engineer
to help us push the boundaries of
LLM-powered conversational AI
and automation pipelines for insurance related tasks.
Location: Boston, MA hybrid role, 2 days per week in-office
What You’ll Do
Build LLM-driven pipelines for information extraction and workflow automation in insurance.
Develop multi-turn, long-context agents that work seamlessly across modalities (voice, text, email).
Fine-tune and deploy models to deliver accurate, compliant, and high-impact solutions.
Work with cutting-edge speech, NLP, and multimodal AI technologies.
What We’re Looking For
Strong ML/NLP background with hands-on experience in LLMs.
Experience in working with Python, SQL
Experience of developing and deploying services and applications using AWS
Experience with conversational AI, speech-to-text, or text-to-speech systems.
Post training methods for LLMs such as supervised fine tuning and preference optimization
Nice to have:
PyTorch/TensorFlow
Working knowledge of AI frameworks (Hugging Face, LangChain, etc.).
Equal Employment Opportunity: Liberate is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected status. Applicants may voluntarily respond to optional self-identification questions to help us improve our hiring process.
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About Us Liberate is reimagining how the $2.7T insurance industry works. By starting with voice, the most valuable and complex channel in insurance, the company proved that even the hardest problems can be automated. Now expanding into full workflow automation across sales, servicing, and claims, Liberate is building toward a bold vision: reasoning agents capable of managing the entire spectrum of carrier and broker operations. Trusted by leading brokers and carriers and powered by a team with experience at Metromile, Google, Stripe, and other category-defining companies, Liberate is shaping the future of insurance.
About the role We’re looking for a
Machine Learning Engineer
to help us push the boundaries of
LLM-powered conversational AI
and automation pipelines for insurance related tasks.
Location: Boston, MA hybrid role, 2 days per week in-office
What You’ll Do
Build LLM-driven pipelines for information extraction and workflow automation in insurance.
Develop multi-turn, long-context agents that work seamlessly across modalities (voice, text, email).
Fine-tune and deploy models to deliver accurate, compliant, and high-impact solutions.
Work with cutting-edge speech, NLP, and multimodal AI technologies.
What We’re Looking For
Strong ML/NLP background with hands-on experience in LLMs.
Experience in working with Python, SQL
Experience of developing and deploying services and applications using AWS
Experience with conversational AI, speech-to-text, or text-to-speech systems.
Post training methods for LLMs such as supervised fine tuning and preference optimization
Nice to have:
PyTorch/TensorFlow
Working knowledge of AI frameworks (Hugging Face, LangChain, etc.).
Equal Employment Opportunity: Liberate is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected status. Applicants may voluntarily respond to optional self-identification questions to help us improve our hiring process.
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