Sr. Machine Learning Engineer

• Design train and evaluate ML models for document classification entity extraction summarization and information retrieval.
• Fine-tune and optimize large language models for domain specific use cases optimizing their performance for accuracy efficiency and scalability.
• Work closely with data engineering teams to preprocess and engineer features from large datasets to enhance the performance of machine learning models.
• Build scalable production-ready ML services with strong observability monitoring and retraining capabilities.
• Contribute to Canoe's MLOps stack including CI/CD for models feature stores evaluation frameworks and data versioning.
• Collaborate with product managers software engineers and other stakeholders to integrate machine learning models into end-to-end solutions.
• Stay current with advancements in LLMs Agentic AI and ML and translate new research into practical improvements to Canoe's technology stack.
• Conduct code reviews to ensure code quality and provide mentorship to junior members of the machine learning team.

• Minimum of 5 years of experience in applied ML engineering with a focus on NLP information extraction or LLMs.
• Proficiency in Python and relevant machine learning libraries (e.g. TensorFlow PyTorch).
• Strong understanding of MLOps (Docker Kubernetes CI/CD for ML experiment tracking).
• Proficiency with AI-assisted development tools (e.g. GitHub Copilot Claude Code agent) to accelerate software development prototyping testing and deployment of ML solutions.
• Problem-solver with a product mindset and bias toward outcomes.
• Excellent communication skills; able to partner across engineering product and business teams.
• Comfortable in fast-paced agile startup environments.
• Bachelor's degree in computer science or related field.

• Master Degree or PhD in computer science or related field
• Experience in training and deploying large language models.
• Familiarity with cloud computing platforms and distributed computing.
• Familiarity with modern ML Ops tools such as Modal Weights and Biases Sagemaker etc.
• Experience with LLM fine-tuning techniques such as LoRA QLoRA or parameter-efficient training frameworks (e.g. Unsloth).

• Medical dental vision benefits
• Flexible PTO
• 401(k)
• Flexible work from home policy
• Home office stipend
• Employee Assistance Program
• Gym/Wifi reimbursement
• Education assistance
• Parental Leave

• Client First -> Listen and deliver client-centric solutions
• Be An Owner -> Take initiative improve situations drive positive outcomes
• Excellence -> Always set the highest standard for yourself and others
• Win Together -> 1 + 1 = 3

What We Do

Canoe offers first-of-its kind AI technology powering the future of alternative investments. Canoe has reimagined the future of alternative investments with cloud-based machine-learning technology for document collection data extraction and data science initiatives. We transform complex documents into actionable intelligence within seconds and empower allocators with tools to unlock new efficiencies for their business. Since the beginning we’ve maintained a focused client-first approach to building and enhancing our technology and will continue to do so. By introducing automation to alternatives document collection and data management workflows institutional investors wealth managers and general partners are seeing dramatic improvements in data accuracy and access team efficiency and client satisfaction.

Why Work With Us

At Canoe we look for people who are open-minded willing to roll up their sleeves and constantly ask questions. We believe that diverse backgrounds and perspectives foster conversation and innovation and collaborate to make each other better. Canoe's success is intertwined with each individual's success which is why we focus on the team.

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